Ranking of low-moisture foods in support of microbiological risk management: meeting report and systematic review

26 Low-moisture foods (LMF) are foods that are naturally low in moisture or are produced from higher moisture foods through drying or dehydration processes. These foods typically have a long shelf life and have been perceived for many years to not represent microbiological food safety risk hazards. However, in recent years, a number of outbreaks of foodborne illnesses linked to LMF has illustrated that despite the fact that microorganisms cannot grow in these products, bacteria do have the possibility to persist for long periods of time in these matrices. Responding to a request from the Codex Committee on Food Hygiene (CCFH), the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) implemented a series of activities aimed at collating and analysing the available information on microbiological hazards related to LMF and ranking the foods of greatest concern from a microbiological food safety perspective. Seven categories of LMF which were ultimately included in the ranking process, and the output of the risk ranking, in descending order was as follows: cereals and grains; dried protein products; spices and dried herbs; nuts and nut products; confections and snacks; dried fruits and vegetables; and seeds for consumption. ISSN 1726-5274 Ranking of low-moisture foods in support of microbiological risk management MICROBIOLOGICAL RISK ASSESSMENT SERIES 26 MEETING REPORT AND SYSTEMATIC REVIEW Attributing illness caused by Shiga toxin-producing Escherichia coli (ST C) to specific foods MICROBIOLOGICAL RISK ASSESSMENT SERIES 32 REPORT R a n k in g o f lo w -m o is tu re fo o d s in s u p p o rt o f m ic ro b io lo g ic a l ris k m a n a g e m e n t: M E E T IN G R E P O R T A N D S Y S T E M A T IC R E V IE W F A O /W H O Food Systems and Food Safety - Economic and Social Development jemra@fao.org http://www.fao.org/food-safety Food and Agriculture Organization of the United Nations Viale delle Terme di Caracalla 00153 Rome, Italy Department of Nutrition and Food Safety jemra@who.int https://www.who.int/health-topics/food-safety/ World Health Organization 20 Avenue Appia 1211 Geneva 27, Switzerland CC0763EN/1/07.22 ISBN 978-92-5-136559-5 ISSN 1726-5274 9 7 8 9 2 5 1 3 6 5 5 9 5 iMICROBIOLOGICAL RISK ASSESSMENT SERIES 26 Ranking of low-moisture foods in support of microbiological risk management MEETING REPORT AND SYSTEMATIC REVIEW Food and Agriculture Organization of the United Nations World Health Organization Rome, 2022 Required citation: FAO and WHO. 2022. Ranking of low moisture foods in support of microbiological risk management: meeting report and systematic review. Microbiological Risk Assessment Series No. 26. Rome. https:// doi.org/10.4060/cc0763en The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) or the World Health Organization (WHO) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO or WHO in preference to others of a similar nature that are not mentioned. 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This work is available under a CC BY-NC-SA 3.0 IGO licence Cover picture © Dennis Kunkel Microscopy, Inc iii Contents Acknowledgements xi Contributors xii Declaration of interests xiv Abbreviations and acronyms xv Executive summary xvi Background 1 Objectives and approach 4 2.1 Identification of categories of low-moisture food (LMF) 4 2.2 Collection and review of key data 6 2.3 Selection of categories for ranking purposes 8 2.4 Development of ranking approach 9 Development and application of ranking model 11 3.1 Step 1: Identification of fundamental objectives 11 3.2 Step 2: Definition of evaluation criteria 12 3.3 Step 3: Definition of attributes 12 3.4 Step 4: Evidence gathering about impacts 14 3.5 Step 5: Evaluation of normalized impacts 20 3.6 Step 6: Elicitation of criteria weights 23 3.7 Step 7: Prioritization of LMF categories (results) 24 3.8 Step 8: Robustness analysis 28 Discussion and conclusions 33 4.1 Ranking results 33 4.2 Knowledge synthesis and data collection to support decision-making 34 4.3 Multi-criteria decision analysis (MCDA) as a ranking approach for food safety issues 36 4.4 Challenges and benefits of process 37 4.5 Conclusions 38 References 40 Glossary 44 1 2 4 3 5 iv ANNEXES Annex 1 Rapid scoping and systematic review meta – analysis of research knowledge 48 A1.1 Introduction and objectives 48 A1.2 Review methods 48 A1.2.1 Review approach 48 A1.2.2 Review protocol and team 49 A1.2.3 Review questions 49 A1.2.4 Definitions and eligibility criteria 49 A1.2.5 Search strategy 51 A1.2.6 Relevance screening 52 A1.2.7 Relevance confirmation and article characterization 52 A1.2.8 Data extraction 53 A1.2.9 Data analysis 53 A1.2.10 Review management 54 A1.2.11 Summary cards 55 A1.3 References cited in A1.1 and A1.2 59 A1.4 Review evidence summary 62 A1.5 Summary card: cereals and grains 68 A1.5.1 Low-moisture food category description 68 A1.5.2 Evidence summary 68 A1.5.3 Burden of illness 68 A1.5.4 Prevalence 72 A1.5.5 Interventions 75 A1.5.6 References in A1.5 80 A1.6 Summary card: confections and snacks 92 A1.6.1 Low-moisture food category description 92 A1.6.2 Evidence summary 92 A1.6.3 Burden of illness 92 A1.6.4 Prevalence 93 A1.6.5 Interventions 99 A1.6.6 References in A1.6 102 A1.7 Summary card: dried fruits and vegetables 109 A1.7.1 Low-moisture food category description 109 A1.7.2 Evidence summary 109 A1.7.3 Burden of illness 109 A1.7.4 Prevalence 110 A1.7.5 Interventions 114 vA1.7.6 References in A1.7 117 A1.8 Summary card: dried protein products 122 A1.8.1 Low-moisture food category description 122 A1.8.2 Evidence summary 122 A1.8.3 Burden of illness 122 A1.8.4 Prevalence 124 A1.8.5 Interventions 125 A1.8.6 References in A1.8 131 A1.9 Summary card: honey and preserves 138 A1.9.1 Low-moisture food category description 138 A1.9.2 Evidence summary 138 A1.9.3 Burden of illness 138 A1.9.4 Prevalence 140 A1.9.5 Interventions 143 A1.9.6 References 143 A1.10 Summary card: nuts and nut products 150 A1.10.1 Low-moisture food category description 150 A1.10.2 Evidence summary 150 A1.10.3 Burden of illness 150 A1.10.4 Prevalence 151 A1.10.5 Interventions 155 A1.10.6 References in A1.10 162 A1.11 Summary card: seeds for consumption 172 A1.11.1 Low-moisture food category description 172 A1.11.2 Evidence summary 172 A1.11.3 Burden of illness 172 A1.11.4 Prevalence 173 A1.11.5 Interventions 176 A1.11.6 References in A1.11 179 A1.12 Summary card: spices, dried herbs and tea 183 A1.12.1 Low-moisture food category description 183 A1.12.2 Evidence summary 183 A1.12.3 Burden of illness 183 A1.12.4 Prevalence 187 A1.12.5 Interventions 193 A1.12.6 References in A1.12 197 A1.13 Appendices 209 Appendix A. LMF product categories and subcategories 209 Appendix B. Final search algorithm 211 vi Appendix C. Final search algorithm 213 Appendix D. Relevance confirmation and article characterization form 214 Appendix E. Data extraction forms 216 Appendix F. Summary card evidence charts 226 Appendix G. Spice classification table 230 Appendix H. Articles reporting non-extractable concentration data and prevalence in batch samples for spices, dried herbs and tea 231 Annex 2 Summary of recall data on low-moisture foods 234 References in Annex 2 237 Annex 3 Technical details of the MCDA ranking approach 238 A3.1 Step 1: Identification of fundamental objectives 238 A3.2 Step 2: Definition of evaluation criteria 240 A3.3 Step 3: Definition of attributes 240 A3.4 Step 4: Evidence gathering about impacts 240 A3.5 Step 5: Evaluation of normalized impacts 241 A3.6 Step 6: Elicitation of criteria weights 241 A3.6.1 Elicitation of the weights for subcriteria under food consumption (C3) 241 A3.6.2 Elicitation of the weights for subcriteria under food production (C4) 242 A3.6.3 Elicitation of the weights for the main criteria 243 A3.7 Step 7: Robustness analysis 245 A3.7.1 Sensitivity to criteria weights – subcriteria of the model 245 A3.7.2 Sensitivity to the estimation of impacts 250 A3.8 References in Annex 3 254 Annex 4 Trade data 255 Reference in Annex 4 256 Annex 5 Calculation of disability-adjusted life years (DALYs) 257 References in Annex 5 258 Annex 6 Consumption data 259 A6.1 Average serving 260 A6.2 Vulnerable consumers 265 A6.3 References in Annex 6 273 Annex 7 Elicitation survey and results 274 A7.1 Objectives 274 A7.2 Results of the elicitation process 277 Annex 8 Calculation of prevalence 279 vii TABLES Table 2.1 Categorization of LMF 5 Table 3.1 Criteria, subcriteria, and attributes for the evaluation of LMF categories 13 Table 3.2 Values for international trade criteria for each of the seven LMF categories 15 Table 3.3 Impacts for the burden of disease criterion 15 Table 3.4 Values for each of the subcriteria used to describe the criterion on vulnerabilities due to food consumption 17 Table 3.5 Values for each of the subcriteria used to describe the criterion on vulnerabilities due to food production 19 Table 3.6 Normalized impacts for criterion C1 (international trade) and C2 (burden of disease) 20 Table 3.7 Normalized impacts for the criterion C3 (consumption) 21 Table 3.8 Normalized impacts for criterion C4 (production) 22 Table 3.9 Overview of the swing weights and their ranges assigned to each of the four main criteria through expert elicitation 23 Table 3.10 Normalized aggregated impact on food consumption (C3) for each LMF category 25 Table 3.11 Normalized impact on food production (C4) for each LMF category 25 Table 3.12 Overall impact for each LMF category and final ranking of LMF categories 27 Table A1.1 Summary of the burden of illness related to LMF outbreaks attributed to select microbial hazards 65 Table A1.2 Average prevalence of Salmonella spp. across all LMF product categories 67 Table A1.3 Summary of globally reported outbreaks related to cereals and grains 70 Table A1.4 Prevalence of selected microbial hazards within cereal and grain categories 74 Table A1.5 Forest plot of the prevalence of selected microbial hazards within cereal and grain categories 76 Table A1.6 Summary table of experimental studies evaluating the effects of interventions to reduce contamination of selected microbial hazards in cereals and grains 78 Table A1.7 Summary of globally reported outbreaks related to confections and miscellaneous snacks 94 Table A1.8 Prevalence of selected microbial hazards within confection and snack categories 97 Table A1.9 Forest plot of the prevalence of selected microbial hazards within confection and snack categories 98 Table A1.10 Summary table of experimental studies evaluating the effects of interventions to reduce contamination of selected microbial hazards in confections and snacks 100 Table A1.11 Summary table of globally reported outbreaks on dried fruits and vegetables 110 viii Table A1.12 Prevalence of selected microbial hazards within dried fruit and vegetable categories 112 Table A1.13 Forest plot of the prevalence of selected microbial hazards within dried fruit and vegetable categories 113 Table A1.14 Summary table of experimental studies evaluating the effects of interventions to reduce contamination of selected microbial hazards in dried fruits and vegetables 115 Table A1.15 Summary table of globally reported outbreaks on dried protein products 123 Table A1.16 Prevalence of selected microbial hazards within dried protein product categories 126 Table A1.17 Forest plot of the prevalence of selected microbial hazards within dried protein product categories 128 Table A1.18 Summary table of experimental studies evaluating the effects of interventions to reduce contamination of selected microbial hazards in dried protein products 129 Table A1.19 Summary table of globally reported case reports and outbreaks on honey and preserves 139 Table A1.20 Prevalence of selected microbial hazards in honey and preserves 141 Table A1.21 Forest plot of the prevalence of selected microbial hazards in honey and preserves 142 Table A1.22 Summary of globally reported outbreaks related to nuts and nut products 152 Table A1.23 Prevalence of selected microbial hazards within nut categories 154 Table A1.24 Forest plot of the prevalence of selected microbial hazards within nut categories 156 Table A1.25 Summary table of experimental studies evaluating the effects of interventions to reduce contamination of selected microbial hazards in nuts and nut products 158 Table A1.26 Summary table of globally reported outbreaks on seeds 173 Table A1.27 Prevalence of selected microbial hazards within seed categories 175 Table A1.28 Forest plot of the prevalence of selected microbial hazards within seed categories 177 Table A1.29 Summary table of experimental studies evaluating the effects of interventions to reduce contamination of selected microbial hazards in seeds 178 Table A1.30 Summary table of globally reported outbreaks on spices 184 Table A1.31 Summary of globally reported outbreaks related to tea 186 Table A1.32 Prevalence of selected microbial hazards within spice categories 189 Table A1.33 Summary of studies reporting the concentration of selected microbial hazards in spices and tea with an associated measure of variability 191 Table A1.34 Forest plot of the prevalence of selected microbial hazards within spice categories 192 Table A1.35 Summary table of experimental studies evaluating the effects of interventions to reduce contamination of selected microbial hazards in spices, dried herbs and tea 194 Table A1.36 LMF product categories and subcategories 209 ix Table A1.37 Final search algorithm 211 Table A1.38 Final search algorithm 213 Table A1.39 Relevance confirmation and article characterization form 214 Table A1.40 Burden of illness extraction form 216 Table A1.41 Prevalence extraction form 218 Table A1.42 Interventions extraction form 222 Table A1.43 Spice classification table 230 Table A1.44 Articles reporting non-extractable concentration data for selected microbial hazards in spices 231 Table A1.45 Articles reporting the prevalence of selected microbial hazards in batch/shipment samples of spices 233 Table A2.1 EU-RASFF–Recall/border rejections of LMF as a result of contamination with microbiological hazards (2010 to June 2014) (EU, 2014) 234 Table A2.2 USFDA Recalls (USA market) of LMF from 2009 up to June 2014 related to microbial hazards (USFDA, 2014a) 235 Table A2.3 USFDA Import Refusals of LMF as a result of microbial contamination frequency (USA) from 2012 up to 2014. Note that product is the most routinely sampled and tested for Salmonella spp. Sampling for other microbes is determined by the product’s risk category (USFDA, 2014b) 236 Table A4.1 Export value in US dollars of each of the categories of LMF based on the data available for 2011 in FAOSTAT 255 Table A5.1 Calculation of the DALY for each of the microorganisms under consideration based on DALY per 1 000 cases of illness in the Netherlands (Havelaar et al., 2012) and cases of illness per organism and per LMF category identified in the structured scoping review (Annex 1) 257 Table A5.2 Total DALY for each of the categories of LMF taking into consideration all the microorganisms under consideration 258 Table A6.1 Food consumption surveys considered for the calculation of consumption data of LMF 260 Table A6.2 Daily consumption of LMF per population groups 262 Table A6.3 Proportion of vulnerable consumers (toddlers and elderly) 265 Table A6.4 The types of low-moisture foods included in each major food category for the purposes of compiling the data on consumption 267 Table A7.1 Expert estimates for criterion 4.2 proportion without a kill step (most likely values) 277 Table A7.2 Expert estimates for criterion 4.1 increased risk of contamination (most likely values) 278 Table A7.3 Expert estimates for criterion 3.3 consumer mishandling (most likely values) 278 Table A8.1 Overview of prevalence data from knowledge synthesis and after application of correction factors to account for levels above a certain threshold of toxin producers before a risk of illness exists 279 Table A8.2 Overview of correction factors applied to toxin producers in each of the categories to account for the need to reach a threshold before the possibility to cause illness exists 282 xFIGURES Figure 2.1 Flow chart of the steps involved in the data collection and ranking exercise 5 Figure 2.2 Steps in the multi-criteria prioritization of LMF categories 10 Figure 3.1 Value tree for the prioritization of LMF categories 12 Figure 3.2 Overall impact of LMF categories 28 Figure 3.3 Sensitivity analysis for the weight of criterion a) C1, international trade; b)C2, burden of disease; c) C3, food consumption; d) C4 food production 29 Figure A1.1 Review flow chart 62 Figure A1.2 Evidence chart: LMF products investigated by research focus 63 Figure A1.3 Evidence chart: microbial hazards investigated by research focus 64 Figure A1.4 The number of LMF outbreaks in each category, grouped by size of the outbreak (number of cases: 0–4, 5–49, 50–500, >500) and microbial hazard 65 Figure A3.1 Means-end network of objectives for managing LMF risks 239 Figure A3.2 Hypothetical LMF categories for the elicitation of weights for the subcriteria under C3 242 Figure A3.3 Hypothetical LMF categories for the elicitation of weights for the subcriteria under C4 243 Figure A3.4 Hypothetical LMF categories for the elicitation of weights for main criteria 244 Figure A3.5 Sensitivity analysis for the weight of criterion C3.1 (average serving) 245 Figure A3.6 Sensitivity analysis for the weight of criterion C3.2 (vulnerability of consumers) 246 Figure A3.7 Sensitivity analysis for the weight of criterion C3.3 (consumer mishandling) 247 Figure A3.8 Sensitivity analysis for the weight of criterion C4.1 (risk of contamination) 248 Figure A3.9 Sensitivity analysis for the weight of criterion C4.2 (proportion without kill step) 248 Figure A3.10 Sensitivity analysis for the weight of criterion C4.3 (prevalence of pathogen) 249 Figure A3.11 Sensitivity analysis for the input estimates – criterion C3.3 250 Figure A3.12 Sensitivity analysis for the input estimates – criterion C4.1 251 Figure A3.13 Sensitivity analysis for the input estimates – criterion C4.2 252 Figure A3.14 Sensitivity analysis for the input estimates – criteria C3.3, C4.1 and C4.2 253 Figure A3.15 Sensitivity analysis for the input estimates – criterion C3.1 254 Figure A7.1 Elicitation survey spreadsheet 276 xi Acknowledgements The Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) would like to express their appreciation to all those who contributed to the preparation of this report through their participation in the expert consultation process and the provision of their time, expertise, data and other relevant information throughout the process. All contributors are listed on the following pages. Particular appreciation is expressed to Dr Ian Young and Ms Lisa Waddell, who undertook the structured scoping review, and the Public Health Agency of Canada for providing the time for them to undertake this task. Appreciation is also extended to all those who responded to the calls for data that were issued by FAO and WHO and brought to our attention data in official documentation or not readily available in the mainstream literature. xii Contributors EXPERTS Mike BATZ, Emerging Pathogens Institute, University of Florida, Gainesville, the United States of America Paul COOK, Microbiological Food Safety Branch, Food Standards Agency, London, the United Kingdom of Great Britain and Northern Ireland Jean-Louis CORDIER, NQSC Group Expert, Food Safety Microbiology, Nestec S.A.Vevey, Switzerland Michelle DANYLUK, Department of Food Science and Human Nutrition, Institute of Food and Agricultural Sciences, University of Florida, Lake Alfred, the United States of America Jeff FARBER, Bureau of Microbial Hazards, Food Directorate, Health Canada, Ottawa, Canada Linda HARRIS, University of California, College of Agricultural and Environmental Sciences, Food Science and Technology Department, Davis, California, the United States of America Edyta MARGAS, School of Biosciences, the University of Nottingham, Sutton Bonington Campus, Loughborough, the United Kingdom of Great Britain and Northern Ireland Gilberto MONTIBELLER, Department of Management, London School of Economics, London, the United Kingdom of Great Britain and Northern Ireland Shizunobu IGIMI, Division of Biomedical Food Research, National Institute of Health Science, Tokyo, Japan Lisa WADDELL, Laboratory for Foodborne Zoonoses, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, Canada Ian YOUNG, Laboratory for Foodborne Zoonoses, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, Canada xiii RESOURCE PERSONS Verna CAROLISSEN-MACKAY, Joint FAO/WHO Food Standards Programme, Rome, Italy Patricia DESMARCHELIER, Principal Food Safety Consultant, Pullenvale Queensland, Australia Laura DYSART, Guelph, Canada Andrijana RAJIĆ, Office of Food Safety, Food and Agriculture Organization of the United Nations, Rome, Italy Secretariat Sarah CAHILL, Food and Agriculture Organization of the United Nations, Italy Haruka IGARASHI, World Health Organization, Switzerland Mina KOJIMA, World Health Organization, Switzerland Jeffrey LEJEUNE, Food and Agriculture Organization of the United Nations, Italy Kang ZHOU, Food and Agriculture Organization of the United Nations, Italy xiv Delaration of interests All participants completed a Declaration of Interests form in advance of the meeting. They were not considered by FAO and WHO to present any conflict in light of the objectives of the meeting. All the declarations, together with any updates, were made known and available to all the participants at the beginning of the meeting. All the experts participated in their individual capacities and not as representatives of their countries, governments or organizations. xv Abbreviations and acronyms aw Water activity CAC Codex Alimentarius Commission CCFH Codex Committee on Food Hygiene CFU Colony forming unit DALY Disability-adjusted life year FAO Food and Agriculture Organization of the United Nations GAP Good Agricultural Practices GHP Good Hygienic Practices GMP Good Manufacturing Practices HACCP Hazard Analysis and Critical Control Point JEMRA Joint FAO/WHO expert meetings on microbiological risk assessment LMF Low-moisture food(s) MCDA Multi-Criteria Decision Analysis WHO World Health Organization xvi Executive summary Low-moisture foods (LMF) are foods that are naturally low in moisture or are produced from higher moisture foods through drying or dehydration processes. For the purposes of this work, LMF were considered to include foods with a water activity (aw) of 0.85 or below. These foods typically have a long shelf life and have been perceived for many years to not represent microbiological food safety risk hazards. However, in recent years, a number of outbreaks of foodborne illnesses linked to LMF has illustrated that despite the fact that microorganisms cannot grow in these products, bacteria do have the possibility to persist for long periods of time in these matrices. Even very low numbers of a microorganism in these types of products can result in illness (e.g. Salmonella in chocolate), or subsequent temperature abuse of a previously low-moisture commodity may allow the micro- organism to proliferate to and cause illness (e.g. Bacillus cereus in rice). As a result, there has been global recognition of the need to more rigorously consider and manage the microbiological hazards associated with LMFs, and in this context the Codex Alimentarius Commission agreed that a Codex Code of Hygienic Practice for Low-Moisture Foods be developed. Responding to a request from the Codex Committee on Food Hygiene (CCFH), the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) implemented a series of activities aimed at collating and analysing the available information on microbiological hazards related to LMF and ranking the foods of greatest concern from a microbiological food safety perspective. Given the broad range of LMF that exist, a categorization of these products was made to facilitate the data collection and ranking exercises. A number of products were considered but ultimately excluded from the ranking exercise including the following: powdered formulae, dry, cured and fermented meats (e.g. sausages, salami and jerky), honey and preserves, and special nutritional foods for malnourished populations. The seven categories of LMF which were ultimately included in the ranking process were (1) cereals and grains, (2) confections and snacks, (3) dried fruits and vegetables, (4) dried protein products, (5) nuts and nut products, (6) seeds for consumption, and (7) spices and dried aromatic herbs (including teas). This work includes an extensive structured review of publicly available data on the illnesses linked to LMF and data on contamination of these products with a range of microbial hazards. Meta-analyses of the contamination data were also xvii undertaken. This work fed into a multi-criteria decision analysis to rank LMF. In addition, the review summarized research on interventions targeted towards mitigating microbiological hazards in LMF, but it was found that the applicability of this evidence to commercial (real-life) conditions was limited. The multi-criteria model for the LMF categories was built up in a consultative manner with experts in the subject matter and in decision and risk analysis. Each of the food categories was evaluated against four criteria: burden of illness, production, consumption and international trade. This required the collection of extensive data to ensure that, to the greatest extent possible, the scoring against each of the above-mentioned criteria was based on the best available evidence. Where evidence was not readily available, expert opinion was relied upon. The output of the risk ranking, in descending order, was as follows: • cereals and grains; • dried protein products; • spices and dried herbs; • nuts and nut products; • confections and snacks; • dried fruits and vegetables; and • seeds for consumption. As the multi-criteria model can be used as a learning tool, i.e. not to prescribe a solution but, instead, to explore the robustness of the findings and the consequences that uncertainties might cause on the ranking, a robustness analysis was undertaken, varying input parameters to test the sensitivity of results to their changes. In addition, a more detailed robustness analysis, concerning difference of priorities among the expert group (criteria weights) and uncertainties about the evidence available (impacts), was undertaken. Cereals and grains scored highly across all the criteria, especially for international trade and food consumption criteria. This is not surprising given the importance of the commodities and products in this category as staples in the global food supply. Dried protein products, which were ranked second, stood out in terms of burden of disease linked to these products. This was influenced by a couple of very large outbreaks associated with dried dairy products, which led to a high burden of disease calculation for this category. The analyses of sensitivity on weights show that the ranking is quite robust with either cereals and grains or dried protein products always being in the top position.

1The burden of foodborne illness and the number of food recalls associated with microbial contamination of low-moisture foods (LMF) has risen in recent years (Beuchat et al., 2013; Dey et al., 2013; Finn et al., 2013; Podolak et al., 2010; Scott et al., 2009; Van Doren et al., 2013a; Vij, et al., 2006). LMF are naturally low in moisture or are produced from higher moisture foods through drying or dehydration processes. The low water activity (aw) of these foods contributes to a long shelf life (Finn et al., 2013). Examples of LMF products include cereals, grains, confections (e.g. chocolate), powdered-protein products (e.g. dairy and egg powders), dried fruits and vegetables, honey, spices, seeds, nuts and nut-based products (e.g. peanut butter), among others (Beuchat et al., 2013; Finn et al., 2013; Podolak et al., 2010). LMF are generally perceived as safe by consumers, and many LMF are consumed as ready-to-eat products with no consumer-level pathogen reduction step such as cooking (Beuchat et al., 2011; Beuchat et al., 2013). LMF are susceptible to contamination from a wide range of microbial hazards. Although most microbial hazards cannot grow in LMF due to the low aw, many pathogens can survive and remain viable for months to years in these foods, posing potential risks to consumers (Beuchat et al., 2013; Finn et al., 2013; Podolak et al., 2010). It is difficult to reduce microbial hazard contamination of LMF by significant margins (e.g. >5 logs) and to non-detectable levels using traditional processing interventions such as heat treatments that are effectively applied to high-moisture foods (Beuchat et al., 2013; Finn et al., 2013). The combination of low aw with the high sugar and/or fat content of many LMF is believed to contribute to the 1 1. Background RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 2 enhanced survival and heat resistance of microbial hazards in these foods (Beuchat et al., 2013; Finn et al., 2013). Many LMF products undergo specific pathogen reduction treatments during processing to reduce potential hazards for consumers. For example, spices and seasonings are often treated with ethylene oxide, propylene oxide, steam treatment, or irradiation to reduce the risk of microbial contamination (Van Doren et al., 2013b). The most important control measures for LMF involve preventing contamination during harvest, post-harvest and processing through implementation of good agricultural practices (GAPs), good manufacturing practices (GMPs), good hygienic practices (GHPs) and hazard analysis critical control point (HACCP) programs (Beuchat et al., 2013; Finn et al., 2013; Podolak et al., 2010). Process-based verification (e.g. audits) and microbial sampling of LMF products and food-processing environments are also important strategies for industry to monitor food safety. However, surveillance of microbial hazards in LMF is not cost effective due to the heterogeneous distribution of pathogens in LMF, diagnostic test limitations, and the variable level of contamination with microbial hazards in LMF (Beuchat et al., 2013; Sperber, 2007). In recognition of the increased global consumption of LMF and the growing risk to human health from these products, several regulatory authorities around the world have developed recommendations and guidelines for industry on how to prevent and manage potential risks of LMF product contamination from microbial hazards (Beuchat et al., 2011; European Food Safety Authority [EFSA], 2013; Grocery Manufacturers Association, 2009; Scott et al., 2009; USFDA, 2013). Due to this increased momentum and a need for standardized and comprehensive international guidance in this area, the Codex Alimentarius Commission has approved the development of a Code of Practice for LMF (FAO and WHO, 2013a). The Codex Committee on Food Hygiene (CCFH) has initiated work on the development of this Code of Practice and in doing so also agreed on the need to request scientific advice on the following (FAO and WHO, 2012): • Which LMF and associated microbiological hazards should be considered as the highest priority for the Committee to address? The ranking process should include, but not be limited to, dried fruits and dehydrated fruits and vegetables, peanut butter, cereals, dry protein products (e.g. dried dairy products), confections (e.g. cocoa and chocolate), snacks (e.g. spiced chips), tree nuts, desiccated coconut, seeds for consumption, spices and dried aromatic plants. • Which information is relevant to the risk management of the microbiological hazards associated with the identified range of LMF, with particular attention CHAPTER 1 - BACKGROUND 3 to agricultural and handling/manufacturing practices in the introduction and control of hazards and the identification of the critical control points for mitigation of the risks associated with LMF? The 45th session of the CCFH reconfirmed its request to FAO/WHO and extended the request to include teas. Following a preliminary report provided by FAO and WHO, the Committee also asked for some clarification in terms of the source of dried protein products that had been associated with foodborne outbreaks. In addition, the Committee agreed that FAO/WHO could consider the following criteria in the ranking of LMF (FAO and WHO, 2013b): • prevalence of contamination of the pathogen in the specified food; • dose-response relationship as estimated by expert knowledge of the behaviour and physiology of the specific pathogen; • frequency and severity of disease; • size and scope of production; • diversity and complexity of the production chain and industry; • potential for amplification of foodborne pathogens through the food chain; • potential for control; and • extent of international trade and economic impact. This report was written based on the JEMRA expert meeting in 2014, which described the approach that was taken to address this request and presents the results of that work. For purposes of transparency, as well as further development or future application of the approach, it also includes an overview of the extensive amount of data that was considered in undertaking this work. The data collection was done in 2014 and was analyzed till 2016. 42 2. Objectives and approach Based on the request of the CCFH, the objectives of this work were as follows: • to undertake a scoping and systematic review and analysis of the available knowledge on foodborne illness linked to LMF, microbial contamination of LMF and interventions available for the control of LMF; • to develop and apply a multi-criteria decision analysis approach to rank LMF of greatest concern from a global microbiological food safety perspective; and • to provide a comprehensive report on the available information and ranking results for use by Codex and member countries. Given the breadth of the work, there were multiple steps involved. These are outlined in the subsequent sections. In addition, a flow chart of the process is provided in Figure 2.1. 2.1 IDENTIFICATION OF CATEGORIES OF LMF For the purpose of this work, LMF were defined as any food item that has an aw level of less than 0.85. The request from CCFH outlined a range of LMF that should be considered in the ranking exercise. In order to facilitate data collection and analysis, it was decided to group LMF into a number of categories (Table 2.1). The initial categorization was developed by the FAO/WHO Secretariat and revised based on input from the leads of the Codex working group on LMF and selected experts. These categories were used as the basis for the scoping-systematic review that was subsequently undertaken (Annex1). CHAPTER 2 -OBJECTIVES AND APPROACH 5 FIGURE 2.1 Flow chart of the steps involved in the data collection and ranking exercise TABLE 2.1 Categorization of LMF Category Foods included Cereals and grains • whole and milled grains (wheat, barley maize, oats, rye, millet, sorghum, buckwheat) • rice and rice products • cereals and cereal products (e.g. breakfast cereals) Confections and snacks • cocoa and chocolate products • other confections/confectionery (e.g. marshmallows, candies) • snacks (e.g. chips, crackers, biscuits) • yeast Dried fruits and vegetables • dried fruits (e.g. raisins, prunes, dates, mangos, apricots, desiccated coconut) • dried vegetables (e.g. tomatoes, potatoes, carrots) • dried/dehydrated mushrooms • dried seaweed Dried protein products • dried dairy products (e.g. milk/whey powders) • dried egg products (e.g. egg powders) • dried meat other than sausages/salamis/jerky (e.g. meat powders, gelatine, fish) Honey and preserves • honey, jams, syrups (e.g. corn syrup) Nuts and nut products • tree nuts (e.g. almonds, brazil nuts, cashews, hazelnuts, macadamia nuts, pecans, pine nuts, pistachios, walnuts) • peanuts and peanut products (e.g. peanut butter, peanut spreads) • mixed and unspecified nuts Seeds for consumption • sesame seeds • tahini (sesame seed paste) • halva/helva (confection made from sesame paste/tahini) • other and unspecified seeds (e.g. pumpkin seeds, sunflower seeds, poppy seeds, melon seeds, flax seeds, mixed/unspecified seeds for consumption) (cont.) Categorization of LMF Follow-up meetings by teleconference Weighting of criteria Ranking of LMF Sensitivity analysis and robustness of ranking Physical meeting of expert panel Screening of food categories Identification of fundamental objectives; definition of criteria and their attributes Collection of additional evidence (databases, expert elicitation) and normalization of values Scoping-systematic review of available data Call for data and experts Establishment of expert panel RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 6 Category Foods included Spices and dried herbs • fruit/seed-based (e.g. paprika, black/white/green/long pepper, aniseed, caraway, celery, coriander, dill seed, fennel, chervil, cumin, allspice, nutmeg/mace, cardamom, fenugreek, mustard) • root-based (e.g. garlic, ginger, turmeric, galangal, onion) • herb/leaf-based (e.g. oregano, marjoram, basil, bay leaf, mint, rosemary, parsley, sage, thyme, dill weed/leaves) • bark/flower-based (e.g. cinnamon, cloves, saffron) • mixed/unspecified (e.g. curry powder, garam masala, tandoori, herb mixes, other mixed/unspecified spices) • tea (e.g. herbal, black teas) Specialized nutritional products • lipid-based nutrient supplements (ready to use therapeutic foods [RUTF] and ready to use supplementary foods [RUSF]) • dried/powdered nutrient supplements (blended powders including some of products listed above) In the course of the work, some modifications to the categories were made. Following the request of the 45th session of the CCFH in 2013, teas were added to the category on spices and dried herbs. Powdered formulae for infants and young children were not included in these categories as the hazards and risks associated with these products have recently been reviewed by FAO and WHO, and Codex has already developed a code of hygienic practice for these products (FAO and WHO 2004, 2006, 2008a, 2008b). In addition, the category of dried protein products was refined to exclude cured and fermented meat products, primarily due to the variability of the water activity associated with these products, depending on the recipe and production process. Thus, in terms of meat, only products with a consistently low aw <0.85 (e.g. meat powders) were summarized for this category. It was also clarified that oils intended for use in food were not considered in this exercise. 2.2 COLLECTION AND REVIEW OF KEY DATA An overview of the microbiological hazards of concern in LMF was determined to be an important starting point and a structured knowledge synthesis of the global research evidence was commissioned. Specifically, a scoping review and systematic-review/meta-analysis was conducted to summarize (1) the burden of illness due to microbial contamination of LMF, (2) the prevalence and concentration of selected microbial hazards in LMF, and (3) interventions to reduce microbial contamination of LMF. The review focused on the above-mentioned categories of LMF and a selection of pathogenic microbiological hazards: Bacillus cereus, Clostridium botulinum, Clostridium perfringens, Cronobacter spp., pathogenic Escherichia coli, Salmonella spp., Staphylococcus aureus, and Listeria monocytogenes. CHAPTER 2 -OBJECTIVES AND APPROACH 7 For the purposes of data collection, the following indicator bacteria were also included: Enterobacteriaceae and generic E. coli. The scoping-systematic review was conducted following standardized international principles together with a “rapid review” approach that employed some short cuts to accommodate limited time and resources (Anderson et al., 2008; Arksey and O’Malley, 2005; Ganann, Ciliska, and Thomas, 2010; Higgins and Green, 2011; Rajić and Young, 2013). Electronic bibliographic databases Scopus, Pubmed/ Medline and reference lists of selected key relevant articles were searched using a comprehensive and reproducible search algorithm to identify potentially relevant literature. Searches for “grey literature” (e.g. reports) were also conducted using the Google search engine. The scoping review stage was used to identify and characterize available research for all three objectives. Study characteristics were recorded for all relevant articles to describe the breadth and distribution of the current knowledge and to identify the main gaps in knowledge. Systematic review methods were used to extract more detailed data from relevant articles, including information on their methodological/reporting soundness. Meta-analysis was utilized to generate weighted estimates of the prevalence of selected microbial hazards in LMF categories where possible. A full overview of the methodology used and the outcomes of this review, presented as an evidence “summary card” for each category of LMF, is described in Annex 1. This review was prepared in advance of the expert meeting and served as one of the key pieces of evidence to support the discussions which led to the development of the ranking model. This review was highly appreciated in terms of the comprehensive summaries it provided for each of the categories which could be used directly as information resources to support risk management decisions on specific categories of LMF. Feedback from the experts, both during and after the meeting, was used to finalize the review. Modifications included additional visual presentation of the contamination data for each category in the form of forest plots and additional description in terms of the strengths and the variability of the data sets. The data presented in Annex 1 was based on the available literature up to 13 January 2014. In the subsequent months, a widely reported outbreak and recall linked to chia seeds unfolded in the United States of America and Canada (Harvey et al., 2017). It should also be noted that the scope of the review did not include statistics on LMF recalls. Data on recalls or refused import shipments is difficult to acquire; however, it can be a useful indicator of trends. The most easily accessible data from recalls is available for the United States of America and the European Union. This data indicated that there were recalls across all categories of LMF, and RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 8 while Salmonella spp. is the most common reason cited, it is far from being the only reason for recalls (see summary data in Annex 2). 2.3 SELECTION OF CATEGORIES FOR RANKING PURPOSES During the expert workshop in May 2014, it was agreed that only seven categories would be considered for the purposes of ranking. These were (1) cereals and grains, (2) confections and snacks, (3) dried fruits and vegetables, (4) dried protein products, (5) nuts and nut products, (6) seeds for consumption, and (7) spices and dried herbs (including teas). Several foods were excluded from the ranking for various reasons: • Powdered formulae for infants and young children, due to the extensive amount of work that had already been undertaken to address the microbiological safety of these products and the existence of Codex guidance in this area; • Dry, cured and fermented meats (e.g. sausages, salami and jerky) were excluded due to the variability in water activity around these products, including products in this category with water activity 0.85; • Honey and preserves: The scoping review indicated that the primary hazard of concern in relation to this category was Clostridium botulinum, and the primary population of concern was infants. In addition, the options for risk management are limited, and many countries already provide guidance advising that honey not be consumed by infants; • Special nutritional foods for malnourished populations have recently been identified as potentially being contaminated with Salmonella and Cronobacter spp (FAO and WHO, 2016). Limited available data associated with these foods was identified – the scoping-systematic review did not identify any information on these products in relation to illness and prevalence of microorganisms. The only available data on these foods was from the agencies which supply these foods to malnourished populations (FAO and WHO, 2016). Furthermore, it was considered that there was no information to suggest that these were particularly different from other LMF and therefore did not warrant a separate category based only on the consuming population. Thus, while this category of products was not further considered in the ranking, it was recommended that CCFH refer to these in the Codex Code of Hygienic Practice.1 • The expert group also clarified that those extensively used common ingredients which are low-moisture in nature and are widely used in processed foods (e.g. sugar and salt) were not included in this ranking exercise. 1 Adopted in 2015. Revised in 2016. Amended in 2018 CHAPTER 2 -OBJECTIVES AND APPROACH 9 2.4 DEVELOPMENT OF RANKING APPROACH In the development of a ranking approach for LMF in terms of microbiological food safety, the objective was to rank the LMF categories in a robust, evidence-based and transparent way, utilizing the best expertise on the subject available and a sound methodology for the assessment of impacts and ranking of food categories. There were a number of challenges to overcome in the development of a ranking approach. These included the need for a global perspective in the assessment, the existence of multiple impacts of concern, the limited amount of evidence about some of these impacts, and the need to incorporate the expertise and opinions of the expert panel supporting the ranking process. These challenges led to the use of Multi-Criteria Decision Analysis (MCDA) and, more specifically, Multi-Attribute Value Theory (MAVT) as the conceptual frameworks (Keeney and Raiffa, 1993; von Winterfeldt and Edwards, 1986; Edwards, Miles and von Winterfeldt, 2007) for the ranking model. This methodology is firmly based on decision theory (French, 1989) and measurement theory (Krantz et al., 1971). It is also well-rooted in behavioural decision research, regarding the elicitation of parameters for the evaluation model (von Winterfeldt, 1999). MCDA has been extensively used in health assessments and prioritizations worldwide, at the international and national levels (e.g. the United Kingdom of Great Britain and Northern Ireland Department for Environment, Food & Rural Affairs [Defra], and the British National Health Service [NHS], among others). The ranking model was developed and applied in an interactive manner (Franco and Montibeller, 2011) by experts in decision and risk analysis and those on the microbiological safety of LMFs. The facilitated approach enabled experts to share information and opinions in a structured way and enhanced the joint understanding and the confidence in the results of the analysis. The evaluation model developed here is an example of the emergent field of Policy Analytics (Tsoukias et al., 2013), with a focus on bridging the science to policy gap. The modelling process followed a top-down evaluation. The steps followed, as shown in Figure 2.2, were (i) identification of the fundamental objectives, (ii) definition of evaluation criteria, (iii) definition of attributes, (iv) gathering of evidence for assessing the impacts of each LMF category on each attribute, (v) conversion to normalized impacts of every LMF category on each attribute, (vi) elicitation of priorities for impacts minimisation (criteria weights), (vii) prioritization of the LMF categories, and (viii) development of a robustness analysis. The process itself and the theory behind it are described in more detail in Annex 3. The development and application of the ranking model is presented in Chapter 3. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 10 FIGURE 2.2 Steps in the multi-criteria prioritization of LMF categories STEP 1 Identification of fundamental objectives STEP 2 Definition of criteria STEP 3 Definition of attributes STEP 4 Evidence gathering about impacts STEP 5 Conversion to normalized impacts STEP 6 Elicitation of priorities (criteria weights) STEP 7 Ranking/Prioritization of LMF categories STEP 8 Robustness analysis 11 3 3. Development and application of ranking model This chapter provides the details of the inputs and the specific evidence that were used in the development and implementation of ranking model. The first step in this type of ranking is to identify the key and the fundamental objectives for the evaluation. While as noted earlier, the key objective of this work was to rank LMF in terms of their microbiological food safety concerns in order to support the provision of management guidance by Codex. Breaking this down in terms of what it means for countries was used as a first step, which then fed into the description of the criteria, their characterization (definition of their attributes) and ultimately the determination of their relative importance, in terms of the weight assigned to each criterion. An overview of each of the steps is provided here with particular emphasis on the data that was used to inform the ranking. More technical details of the ranking approach can be found in Annex 3. 3.1 STEP 1: IDENTIFICATION OF FUNDAMENTAL OBJECTIVES The fundamental objectives were defined as international trade, burden of disease, vulnerabilities due to food consumption, and vulnerabilities due to food production. These were defined by use of a means end network (see Annex 3-Step 1 for more details). RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 12 3.2 STEP 2: DEFINITION OF EVALUATION CRITERIA The four fundamental objectives – international trade, burden of disease, vulnerabilities due to food consumption, and vulnerabilities due to food production – were translated into four evaluation criteria, C1 to C4, and organized as a value tree (Belton and Stewart, 2002), as shown in Figure 3.1. Two evaluation criteria were decomposed into three subcriteria. The criterion vulnerabilities from food consumption (C3) were decomposed into average serving (C3.1), proportion of vulnerable consumers (C3.2), and potential for consumer mishandling (C3.3). The criterion vulnerabilities from food production (C4) was decomposed into increased risk of contamination (C4.1), proportion without kill step (C4.2), and prevalence of pathogen (C4.3). These criteria must observe a strict set of properties to enable a quantitative multi-criteria value model to be developed (see Annex 3 - Step 2). FIGURE 3.1 Value tree for the prioritization of LMF categories 3.3 STEP 3: DEFINITION OF ATTRIBUTES For each criterion located at the bottom level of the value tree, an associated attribute was specified (Table 3.1). This attribute is a performance indicator employed to measure the impact of each option being assessed on the fundamental objective being pursued. Overall impact C3.1: Average serving C3.2: Proportion of vulnerable consumers C3.3: Potential for consumer mishandling C4.1: Increased risk of contamination C3.3: Proportion without kill step C3.3: Prevalence of pathogen C1: International trade C2: Burden of disease C3: Vulnerabilities from food consumption C4: Vulnerabilities from food production CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 13 TABLE 3.1 Criteria, subcriteria, and attributes for the evaluation of LMF categories Criteria Subcriteria Attribute Source of information/evidence C1: International trade - Export value in USD billions/year FAOSTAT Trade data (http://faostat3.fao. org/) C2: Burden of disease - Total disability- adjusted life years (DALYs) in reported outbreak cases, 1990–2013 Systematic/scoping review (Annex 1) and published DALY data (Annex 5) C3: Vulnerabilities due to food consumption C3.1: Average serving Average g/day FAO/WHO Chronic Individual Food Consumption Database Summary Statistics (CIFOCOSS) (Annex 6) C3.2: Proportion of vulnerable consumers Proportion (0–100%) consumed by vulnerable groups (toddlers and elderly) FAO/WHO Chronic Individual Food Consumption Database Summary Statistics (CIFOCOSS) (Annex 6) C3.3: Potential for consumer mishandling Proportion (0–100%) of LMF products in a given category with an increased risk as a result of mishandling/poor practices at any time between final retail and consumption (see Annex 7 for details) Expert opinion* C4: Vulnerabilities due to food production C4.1: Increased risk of contamination Proportion (0–100%) of LMF products in a given category with an increased risk of contamination post kill step (see Annex 7 for details) Expert opinion* C4.2: Proportion without kill step Proportion (0–100%) of LMF in a given category without a kill step prior to retail and distribution (see Annex 7 for details) Expert opinion* C4.3: Prevalence of pathogen Probability that a LMF is contaminated at a level with any pathogens with the potential to cause illness in consumers2 Systematic/scoping review (Annex 1) * Expert opinion was based on an expert elicitation process involving the members of the expert group. Further details of the process used can be found in Annex 7. 2 Levels of contamination: Salmonella = presence, B. cereus, C. perfringens and S. aureus, =>3log10 CFU/g, pathogenic E. coli, Listeria and Cronobacter were omitted from calculation due to lack of data. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 14 3.4 STEP 4: EVIDENCE GATHERING ABOUT IMPACTS Following the definition of the criteria and their attributes, an extensive effort was made to collect the available data and evidence that would specifically support evaluation of the criteria against the attributes identified in Table 3.1. The primary sources of data and evidence used to evaluate each of the criteria are also indicated in Table 3.1. Whenever documented evidence was available it was employed, but for some attributes it was necessary to rely on expert judgment. In this case, a clear protocol was developed to elicit such parameters, as described in Annex 7. The sources and the rationale for each attribute are provided below. 3.4.1 International trade (C1) The data on the value of international trade was collated from FAOSTAT, which was found to be the most comprehensive database with regard to LMF since for many categories the data were sufficiently disaggregated to distinguish LMF from other products. The data collated was the most recent available, which was from 2011. There was, however, a number of challenges in terms of using this data, and for most categories there are some key caveats which should be highlighted. In the case of cereal and grains, it was recognized that not all of these commodities that enter the export market were intended for human consumption. Therefore, a correction factor was applied based on the FAO Food Balance sheets (available at http://faostat3.fao.org/browse/FB/*/E), which indicate from a global perspective the proportion of key commodities which are consumed as food. In relation to confections and snacks, it should be noted that there were limited data for snacks due to the difficulty in clearly defining these. Also, with regard to seeds for human consumption, the export figures were also subjected to a correction factor to account for the proportion of seeds which are pressed for oil. An overview of the data and any modifications that had to be made are included in Annex 4. As extraction of the data for the relevant food categories was a resource-intensive process, it was limited to one year rather than a 5- or 10-year average. As this was the most recent data available, it was considered the most pertinent to the current ranking process. Also, a spot check of a few specific products did not indicate huge deviations in the previous five years. The trade values for each LMF category are shown in Table 3.2. CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 15 TABLE 3.2 Values for international trade criteria for each of the seven LMF categories C1: International trade Code Category name Export value (USD billions/year) Cat 1 Cereals and grains 118.594 Cat 2 Confections and snacks 58.124 Cat 3 Dried fruits and vegetables 15.211 Cat 4 Dried protein products 22.800 Cat 5 Nuts and nut products 20.338 Cat 6 Seeds for consumption 1.150 Cat 7 Spices, dried herbs and tea 14.938 3.4.2 Burden of disease (C2) As part of the scoping review, any publicly available literature on the burden of illness was identified and synthesized for each category. This information was almost exclusively from outbreaks and is summarized in detail in Annex 1. Across all LMF categories, outbreaks involving B. cereus, Cl. botulinum, Cl. perfringens, pathogenic E. coli, Salmonella spp. and S. aureus were captured. No outbreaks associated with generic E. coli, Cronobacter spp., L. monocytogenes or Enterobacteriaceae were identified in the scoping review. For this criterion, a decision was made to exclude outbreaks prior to 1990 in the calculation of burden of disease; this was decided for reasons of timeliness and because outbreak reports are sparse before that cut-off. Each case of illness recorded from 1990–2013 was multiplied by a pathogen-specific per-case DALY estimate, which were then summed by LMF category (see Annex 5 for more details). DALY estimates are shown in Table 3.3. TABLE 3.3 Impacts for the burden of disease criterion C2: Burden of disease Code Category name Total DALYs of outbreak cases, 1990–2013 Cat 1 Cereals and grains 72.53 Cat 2 Confections and snacks 60.26 Cat 3 Dried fruits and vegetables 32.78 Cat 4 Dried protein products 136.44 Cat 5 Nuts and nut products 118.51 Cat 6 Seeds for consumption 18.42 Cat 7 Spices, dried herbs and tea 80.71 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 16 3.4.3 Consumption (C3) As mentioned earlier, the criterion related to consumption was decomposed to three subcriteria as it was not possible to find a single means of capturing the aspects determined critical for consideration by the experts. Even when broken down, however, this was not an easy area for which to obtain data, and so a mixture of information from databases and expert elicitation were used in the evaluation of these subcriteria. 3.4.3.1 Average serving (C3.1) For the purpose of the exercise, the FAO/WHO Chronic Individual Food Consumption Database Summary Statistics (CIFOCOSS) was chosen as being the most reliable individual food consumption database available at the global level (see Annex 6). It was noted that it was not possible to provide reliable estimates for the median and therefore for the standard deviation for some LMF categories (i.e. dried fruits and vegetables and dried protein products) due to the low number of consumers reported in the surveys. The mean serving in grams per day for the average population as well as the amount consumed by those considered to be high consumers were therefore used for ranking purposes and are shown in Table 3.4. The detailed tables on consumption can be found in Annex 6. 3.4.3.2 Proportion of vulnerable consumers (C3.2) For the purposes of this work, it was decided to use age as a proxy for vulnerability of consumers, and so in this context vulnerable consumers are defined as infants and young children (0–35 months) and the elderly (>65 years). While this data is available from population statistics, it was not possible to link such data to the LMF categories, and therefore this would not distinguish those categories which may be more frequently consumed by the vulnerable population. Therefore, using the CIFOCOSS data that was presented in 3.1, the proportion of consumers that were infants and young children and the elderly was calculated for each category. The results are shown in Table 3.4 and details of the calculations are provided in Annex 6. The limitations of using such an approach were acknowledged, and the proportion of the vulnerable population may be underestimated as it does not include those who may be ill or immunocompromised and do not fit in the category of young children or the elderly. However, given the data limitations and the global nature of the work, this was considered to be the most feasible approach. 3.4.3.3 Potential for consumer mishandling (C3.3) This variable is defined as the proportion (0–100 percent) of LMF products in a given category with an increased risk as a result of mishandling/poor practices at any time between final retail and consumption. It concerns those LMF products CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 17 which may become contaminated at high enough levels to affect human health if mishandling occurs (e.g. temperature abuse, etc.), or if there is, for example, addition or combining of ingredients after the kill step, which would present an opportunity for contamination of the product. The inputs to the ranking model on this subcriterion were based on expert opinion, where experts were asked to provide the most likely estimate for the variable for each LMF category. The median of these estimates as shown in Table 3.4 was used in the ranking. Further details of the expert elicitation process are provided in Annex 7. TABLE 3.4 Values for each of the subcriteria used to describe the criterion on vulnerabilities due to food consumption C3.1 - Average serving C3.2 - Vulnerable consumers C3.3 - Consumer mishandling Code Category name Mean [g/day] High consumers level (P95) [g/day] Proportion (0–100%) consumed by vulnerable groups: toddlers and elderly Proportion (0–100%) of LMF products in a given category with an increased risk as a result of mishandling/ poor practices at any time between final retail and consumption Cat 1 Cereals and grains 185.0 537.5 14.9 20 Cat 2 Confections and snacks 67.4 513.0 12.7 5 Cat 3 Dried fruits and vegetables 21.1 295.5 16.0 5 Cat 4 Dried protein products 1.1 40.0 33.5 25 Cat 5 Nuts and nut products 2.1 131.7 19.8 5 Cat 6 Seeds for consumption 5.5 179.0 12.7 5 Cat 7 Spices, dried herbs and tea 4.4 49.1 13.9 15 3.4.4 Production (C4) As mentioned earlier, the criterion related to vulnerabilities in production was decomposed into three subcriteria, as it was not possible to find a single means of capturing the issues determined critical for consideration by the experts. The RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 18 evidence for these subcriteria came from the structured scoping review (Annex 1) and expert elicitation (Annex 7). 3.4.4.1 Increased risk of contamination (C4.1) This variable is defined as the proportion (in terms of amount of product produced for human consumption) of LMF products in a given category with an increased risk of contamination post kill step. More specifically, this is defined as those LMF products to which there is addition or combining of ingredients after the kill step, which would present an opportunity for contamination of the product. Inputs on this were based on expert elicitation where experts were asked to provide the Most Likely (ML) estimate for the variable for each LMF category. The median of these estimates is shown in Table 3.5. Further details of the expert elicitation process are provided in Annex 7. 3.4.4.2 Proportion without kill step (C4.2) This variable is defined as the proportion (0–100 percent) of LMF products in a given category without a kill step prior to retail and distribution. For the purposes of characterizing this parameter, a kill step is defined as follows: a process applied to a food or food ingredient with the aim of minimizing public health hazards from pathogenic microorganisms. The process step would likely not inactivate all microorganisms present, but it should reduce the number of harmful ones to a level at which they do not constitute a significant health hazard. Although not originally intended as a kill step, processes such as roasting or extrusion cooking of LMF may also contribute to reducing numbers of harmful microorganisms which might be present. Regardless of the origin of the process step, all the processes which are used as a kill step must be validated to ensure that they are delivering the intended effect. In the absence of validation, such processes should not be considered as a kill step. Examples of a kill step could include validated processes of applying heat or other means of inactivation when the food or ingredient has a high-water activity (e.g. cooking meat, pasteurizing liquids, etc.). Inputs on this were based on expert elicitation where experts were asked to provide the most likely estimate for the variable for each LMF category. The median of these estimates is shown in Table 3.5. Further details of the expert elicitation process are provided in Annex 7. 3.4.4.3 Prevalence of pathogen (C4.3) The pathogen prevalence per category was estimated based on average meta-analysis estimates from the scoping-systematic review. Based on the availability of data for all seven categories, and the degree of confidence in that data, CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 19 it was agreed to use data on the prevalence of B. cereus, C. perfringens, S. aureus and Salmonella spp. to calculate an estimation of prevalence of contamination for each category. However, one concern that had to be overcome in relation to this approach is related to the toxin-producing organisms. They are only of concern when they reach a threshold concentration and toxin production. A threshold of 3 log CFU/g was assumed for this exercise. For each category, the proportion of positive samples in prevalence surveys that are likely to exceed a 3 log CFU/g threshold was estimated based on the available data. Once the corrected values for each of the pathogens were determined, a minimum, maximum and mid-value for the overall prevalence of pathogen contamination were determined for each category. This approach involved several rounds of expert discussion before being finalized in order to confirm that the approach was reasonable and the output was within what one could reasonably expect. Further details are provided in Annex 8, and the results are shown in Table 3.5. TABLE 3.5 Values for each of the subcriteria used to describe the criterion on vulnerabilities due to food production C4.1 - Increased risk of contamination C4.2 - Proportion without kill step C4.3 - Prevalence of pathogens Code Category name Proportion (0–100%) of LMF products in a given category with an increased risk of contamination post kill step Proportion (0–100%) of LMF products in a given category not subject to a kill step (see definition below) prior to retail and distribution Prevalence or probability of contamination (%) Cat 1 Cereals and grains 14.55 85 3.94 Cat 2 Confections and snacks 40 20 2.21 Cat 3 Dried fruits and vegetables 10 70 4.84 Cat 4 Dried protein products 20 10 2.54 Cat 5 Nuts and nut products 10.5 50 0.78 Cat 6 Seeds for consumption 10 75 2.07 Cat 7 Spices, dried herbs and tea 10 75 11.67 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 20 3.5 STEP 5: EVALUATION OF NORMALIZED IMPACTS The scale for measuring the normalized impact of each LMF category on every attribute was normalized between 0 (for the lowest impact) to 100 (for the highest impact). This is therefore a linear function, with the properties associated with multi-attribute value theory (Dyer and Sarin, 1979). Tables 3.6 to 3.8 show the normalized impact for each attribute of the model. TABLE 3.6 Normalized impacts for criterion C1 (international trade) and C2 (burden of disease) C1 - International trade C2 - Burden of disease Code Category name Export value [USD billions/ year] Normalized impact (v1) [Dis-Value] DALYs from outbreak cases (1990– 2013) Normalized impact (v2) [Dis-Value] Cat 1 Cereals and grains 118.594 100.0 72.53 45.9 Cat 2 Confections and snacks 58.124 48.5 60.26 35.4 Cat 3 Dried fruits and vegetables 15.211 12.0 32.78 12.2 Cat 4 Dried protein products 22.800 18.4 136.44 100.0 Cat 5 Nuts and nut products 20.338 16.3 118.51 84.8 Cat 6 Seeds for consumption 1.150 0.0 18.42 0.0 Cat 7 Spices, dried herbs and tea 14.938 11.7 80.71 52.8 CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 21 TA B LE 3 .7 N or m al iz ed im pa ct s fo r th e cr it er io n C 3 (c on su m pt io n) C3 .1 - A ve ra ge s er vi ng C3 .2 - V ul ne ra bl e co ns um er s C3 .3 - C on su m er m is ha nd lin g Co de Ca te go ry na m e A ve ra ge g/ da y N or m al iz ed im pa ct (v 3. 1) [D is -V al ue ] P ro po rt io n (0 –1 0 0 % ) co ns um ed b y vu ln er ab le g ro up s: to dd le rs a nd e ld er ly N or m al iz ed im pa ct (v 3. 2) [D is -V al ue ] P ro po rt io n (0 –1 0 0 % ) o f L M F pr od uc ts in a g iv en c at eg or y w it h an in cr ea se d ri sk a s a re su lt o f m is ha nd lin g/ po or pr ac ti ce s at a ny ti m e be tw ee n fin al re ta il an d co ns um pt io n N or m al iz ed im pa ct (v 3. 3) [D is -V al ue ] Ca t 1 C er ea ls a nd gr ai ns 18 5. 0 10 0 .0 14 .9 10 .6 20 75 .0 Ca t 2 C on fe ct io ns an d sn ac ks 67 .4 36 .1 12 .7 0 .0 5 0 .0 Ca t 3 D ri ed fr ui ts a nd ve ge ta bl es 21 .1 10 .9 16 .0 15 .9 5 0 .0 Ca t 4 D ri ed p ro te in pr od uc ts 1. 1 0 .0 33 .5 10 0 .0 25 10 0 .0 Ca t 5 N ut s an d nu t pr od uc ts 2. 1 0 .5 19 .8 34 .1 5 0 .0 Ca t 6 Se ed s fo r co ns um pt io n 5. 5 2. 4 12 .7 0 .0 5 0 .0 Ca t 7 Sp ic es , d ri ed he rb s an d te a 4 .4 1. 8 13 .9 5. 8 15 50 .0 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 22 TA B LE 3 .8 N or m al iz ed im pa ct s fo r cr it er io n C 4 (p ro du ct io n) C4 .1 - In cr ea se d ri sk o f c on ta m in at io n C4 .2 - P ro po rt io n w it ho ut k ill s te p C4 .3 - P re va le nc e of p at ho ge ns Co de Ca te go ry na m e P ro po rt io n (0 –1 0 0 % ) of L M F pr od uc ts in a gi ve n ca te go ry w it h an in cr ea se d ri sk o f co nt am in at io n po st k ill st ep N or m al iz ed im pa ct (v 4 .1 ) [D is -V al ue ] P ro po rt io n (0 –1 0 0 % ) o f L M F pr od uc ts in a g iv en ca te go ry n ot s ub je ct to a k ill s te p (s ee de fin it io n be lo w ) pr io r to re ta il an d di st ri bu ti on N or m al iz ed im pa ct (v 4 .2 ) [D is -V al ue ] P re se nc e of co nt am in at io n (l og 10 c fu /g ) N or m al iz ed im pa ct (v 4 .3 ) [D is -V al ue ] Ca t 1 C er ea ls a nd gr ai ns 14 .5 5 15 .2 85 10 0 .0 3. 94 29 .0 Ca t 2 C on fe ct io ns an d sn ac ks 4 0 10 0 .0 20 13 .3 2. 21 13 .1 Ca t 3 D ri ed fr ui ts a nd ve ge ta bl es 10 0 .0 70 80 .0 4 .8 4 37 .3 Ca t 4 D ri ed p ro te in pr od uc ts 20 33 .3 10 0 .0 2. 54 16 .2 Ca t 5 N ut s an d nu t pr od uc ts 10 .5 1. 7 50 53 .3 0 .7 8 0 .0 Ca t 6 Se ed s fo r co ns um pt io n 10 0 .0 75 86 .7 2. 0 7 11 .8 Ca t 7 Sp ic es , d ri ed he rb s an d te a 10 0 .0 75 86 .7 11 .6 7 10 0 .0 CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 23 3.6 STEP 6: ELICITATION OF CRITERIA WEIGHTS The aggregation of multiple impacts into an overall impact requires the definition of priorities among the impacts considered. These priorities are represented by criteria weights in a multi-criteria model. It is important that proper elicitation procedures are employed for obtaining these parameters from experts, as they should consider not only the relative importance of the criteria, but also the ranges of each attribute in such prioritization3 (Keeney and Raiffa, 1993; Keeney, 2002). Several valid protocols are available, and in this exercise the weights were elicited from the expert group using an adaption of the swing weighting method (von Winterfeldt and Edwards, 1986), which makes the assessments more concrete. Details of the protocol used are included in Annex 3 (Step 6). The weights elicited for each of the criteria and subcriteria are presented in Table 3.9. The swing weights define the level of relative importance of each criterion in the final ranking and are elicited on a 0 to 100 scale. The experts clearly identified C2 (burden of disease) as having the highest weight in the ranking exercise. There were some differences of opinions among experts on the swing weights for the other three criteria, reflected in the ranges presented in Table 3.9. Ultimately, production was considered to have the second highest weight, followed by consumption and finally, international trade. Normalized weights, which sum to 100 percent, were calculated by dividing each criterion’s consensus swing weight by the sum of swing weights across all four criteria (270). TABLE 3.9 Overview of the swing weights and their ranges assigned to each of the four main criteria through expert elicitation Criteria Consensus swing weight Range of swing weight/swing weight range Normalized weight (%) Normalized weight range (%) C1 - International trade 45 [30, 60] 16.7 [11.8, 21.1] C2 - Burden of disease 100 - 37 C3 - Consumption 50 [40, 65] 18.5 [15.4, 22.8] C4 - Production 75 [70, 80] 27.8 [26.4, 29.1] 3 The notion of direct importance of a criterion should be avoided in defining weights of evaluation criteria, as it can lead to a misleading definition of these parameters (von Nitzsch and Weber, 1993) and misrepresentation of priorities (Keeney, 2002). RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 24 3.7 STEP 7: PRIORITIZATION OF LMF CATEGORIES (RESULTS) As the criteria are preferentially independent, i.e. the impacts of LMF categories can be assessed independently on every attribute (Keeney, 1996; von Winterfeldt and Edwards, 1986), a simple weighted sum could be used to aggregate the different normalized impacts onto a single overall impact. The overall normalized impact (V) of a LMF category a is thus given by the following formula: V(a) = w1 v1(a) + w2 v2(a) + w3 v3(a) + w4 v4(a). [Eq. 1] With: w1 + w2 + w3 + w4 = 1. The normalized aggregated impact (v3) for food consumption is given by: v3(a) = w3.1 v3.1(a) + w3.2 v3.2(a) + w3.3 v3.3(a). [Eq. 2] With: w3.1 + w3.2 + w3.3 = 1. The normalized aggregated impact (v4) for food production is given by: v4(a) = w4.1 v4.1(a) + w4.2 v4.2(a) + w3.3 v4.3(a). [Eq. 3] With: w4.1 + w4.2 + w4.3 = 1. Based on consumption criteria alone, and using equation 2 above and the baseline weights elicited in the previous step of the analysis, cereals and grains and dried protein products have a very similar high score and rank far ahead of the other categories based on this criterion. CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 25 TABLE 3.10 Normalized aggregated impact on food consumption (C3) for each LMF category C3: Food consumption C3.1 - Average serving C3.2 - Vulnerable consumers C3.3 - Consumer mishandling Impact food consumption Code Category name [Dis-Value] [Dis-Value] [Dis-Value] [Dis-Value] Cat 1 Cereals and grains 100.0 10.6 75.0 57.9 Cat 2 Confections and snacks 36.1 0.0 0.0 15.7 Cat 3 Dried fruits and vegetables 10.9 15.9 0.0 11.6 Cat 4 Dried protein products 0.0 100.0 100.0 56.5 Cat 5 Nuts and nut products 0.5 34.1 0.0 15.1 Cat 6 Seeds for consumption 2.4 0.0 0.0 1.0 Cat 7 Spices, dried herbs and teas 1.8 5.8 50.0 9.8 Normalized weights w3.1 = 43.5% w3.2 = 43.5% w3.3 =13.0% Considering the production criterion alone, using equation 3 above and the baseline weights elicited in the previous step of the analysis, spices, dried herbs and teas rank highest, followed by cereals and grains and dried fruits and vegetables (Table 3.11). Against this criterion, dried protein products rank much lower, which may reflect the well-controlled conditions under which the dried protein products considered in this ranking are produced. TABLE 3.11 Normalized impact on food production (C4) for each LMF category C4: Vulnerability food production C4.1 - Risk of contamination C4.2 - Proportion without kill step C4.3 - Prevalence of pathogens Impact food production Code Category name [Dis-Value] [Dis-Value] [Dis-Value] [Dis-Value] Cat 1 Cereals and grains 15.2 100.0 29.0 50.0 Cat 2 Confections and snacks 100.0 13.3 13.1 29.7 Cat 3 Dried fruits and vegetables 0.0 80.0 37.3 44.4 (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 26 C4: Vulnerability food production C4.1 - Risk of contamination C4.2 - Proportion without kill step C4.3 - Prevalence of pathogens Impact food production Cat 4 Dried protein products 33.3 0.0 16.2 14.0 Cat 5 Nuts and nut products 1.7 53.3 0.0 18.1 Cat 6 Seeds for consumption 0.0 86.7 11.8 34.5 Cat 7 Spices, dried herbs and teas 0.0 86.7 100.0 76.5 Normalized weights w4.1 = 19.0% w4.2 = 33.3% w4.3 = 47.6% Based on equation 1 above and the baseline weights elicited in the previous step of the analysis, category 1 (cereals and grains) has the normalized impact (V = 58.3), followed by category 4 (dried protein products, V = 54.5), and then category 7 (spices, dried herbs and tea, V = 44.6)(Table 3.12). Figure 3.2 presents the contribution of each main criterion to the overall normalized impact of every LMF category. Notice that a large part of the overall score of dried protein products (category 4) comes from its impact on the burden of disease criterion (v2 = 37), while the cereals and grains (category 1) has more distributed impacts on the four main criteria. Thus, figure 3.2 not only illustrates the overall ranking but the criterion which really drove the ranking result. Cereals and grains (category 1) had quite high impacts for all criteria, especially for international trade (C1) and food consumption (C3) criteria, compared to most of the other categories. This is not particularly surprising given that this category included the commodities and products which are considered as staple foods in most parts of the world. However, these aspects did not completely overshadow the other criteria. For dried protein products (category 4), burden of disease (C2) was the dominating driver of the high score, primarily due to a couple of very large outbreaks associated with dried dairy products, which equated to a high burden of disease estimate for this food category. For the third ranked category, spices, dried herbs and tea (category 7), the vulnerabilities of the production and the burden of disease were the driving factors. Generally spices and dried herbs are produced under conditions with a high potential for cross-contamination and without any steps to reduce or kill pathogens. In addition, it should be noted that for dried herbs most of the outbreaks involved Salmonella, which has a higher DALY than other common pathogens e.g. B. cereus. For nuts and nut products (category 5), burden CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 27 TA B LE 3 .1 2 O ve ra ll im pa ct fo r ea ch L M F ca te go ry a nd fi na l r an ki ng o f L M F ca te go ri es Co de Ca te go ry n am e C1 – In te rn at io na l tr ad e (v 1) C2 - B ur de n of di se as e (v 2) C3 - F oo d co ns um pt io n (v 3) C4 - F oo d pr od uc ti on (v 4 ) O ve ra ll im pa ct (V ) [d is -v al ue ] R an ki ng or de r Ca t 1 C er ea ls a nd g ra in s 10 0 .0 4 5. 9 57 .9 50 .0 58 .3 1 Ca t 2 C on fe ct io ns a nd s na ck s 4 8. 5 35 .4 15 .7 29 .7 32 .4 5 Ca t 3 D ri ed fr ui ts a nd v eg et ab le s 12 .0 12 .2 11 .6 4 4 .4 21 .0 6 Ca t 4 D ri ed p ro te in p ro du ct s 18 .4 10 0 .0 56 .5 14 .0 54 .5 2 Ca t 5 N ut s an d nu t pr od uc ts 16 .3 84 .8 15 .1 18 .1 4 2. 0 4 Ca t 6 Se ed s fo r co ns um pt io n 0 .0 0 .0 1. 0 34 .5 9. 8 7 Ca t 7 Sp ic es , d ri ed h er bs a nd t ea s 11 .7 52 .8 9. 8 76 .5 4 4 .6 3 N or m al iz ed w ei gh ts W 1 = 16 .7 % W 2 = 3 7. 0 % W 3 = 18 .5 % W 4 = 2 7. 8% 10 0 .0 % RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 28 of disease was also the key driver as with spices dried herbs and teas, because there have been several moderate to large outbreaks of international concern (e.g. roasted peanuts [2001] shipped globally from China). FIGURE 3.2 Overall impact of LMF categories 3.8 STEP 8: ROBUSTNESS ANALYSIS Multi-criteria evaluation models, such as the one developed here, are not designed to be prescriptive, but rather as learning tools that support decision-making. As such, it is important to explore the robustness of the findings and the consequences that uncertainties might cause on the ranking (Roy, 1993; Roy, 2010). An interactive robustness analysis was conducted with the experts during the ranking process by varying input parameters to test the sensitivity of results to their changes. This was done by using a spreadsheet-based decision support system developed during the project. In addition, a detailed backroom robustness analysis was conducted, concerning differences of priorities among the expert group (criteria weights) and uncertainties about the evidence available (impacts). 3.8.1 Sensitivity to criteria weights – main criteria of the model As mentioned previously, the elicitation of weights from experts provided ranges of weights. In this section, the consequences of varying weights on the ranking of LMF categories for the four main criteria of the model are analysed. C1 International trade C2 Burden of disease C3 Food consumption C4 - Food production V al ue 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 14 11 8 3 13 8 12 2 5 2 3 37 10 5 3 31 3 10 2 20 2 21 4 17 17 CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 29 The sensitivity of the overall impact of every LMF category was analyzed as the weight of criterion C1 (international trade) ranged from 0 to 100 percent (Figure 3.3a). The baseline weight of this criterion in the model is w1 = 16.7 percent (see annex 3 – step 6) and is indicated by the black vertical line. With this baseline weight, cereals and grains (category 1) has the highest overall score, followed by dried protein products (category 4), then spices, dried herbs and teas (category 7). If the weight of this criterion was further increased (to the right of the black vertical line) the cereals and grains (category 1) overall normalized impact would further increase – therefore more emphasis on international trade would lead to even higher ranking of cereals and grains (category 1). However, if the weight of this international trade criterion was decreased, there is a point where the cereals and grains (category 1) would intersect with the dried protein products (category 4) (point ➀: w’1 = 12 percent). Any further reduction of weight below this weight (point ➀) would lead to the selection of dried protein products as the highest-ranked food category. The lower ➀ limit of the range provided by the experts (w1 = [11.8 percent, 21.1 percent ], Table 3.9) is similar to the point (point ➀, Fig 3a), below which dried protein products is predicted to have a higher impact than cereals and grains. Notice that the ranking of the categories with the baseline weights is the same for all the criteria analysed here (i.e. grains, dried protein, spices and herbs, etc.) (Figs 3.3a, b, c, d). a O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W1 = 16.7% Normalized weight W1 (international trade) 1 FIGURE 3.3 Sensitivity analysis for the weight of criterion a) C1, international trade; b) C2, burden of disease; c) C3, food consumption; d) C4 food production (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 30 FIGURE 3.3 Sensitivity analysis for the weight of criterion a) C1, international trade; b) C2, burden of disease; c) C3, food consumption; d) C4, food production c O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W3 = 18.5% Normalized weight W3 (food consumption) b O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W2 = 37.0% Normalized weight W2 (burden of disease) 2 d O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W4 = 27.8% Normalized weight W4 (food production) 3 4 CHAPTER 3 - DEVELOPMENT AND APPLICATION OF RANKING MODEL 31 The sensitivity of the overall impact of every LMF category was analysed as the weight of criterion C2 (burden of disease) ranged from 0 to 100 percent (Figure 3.3b). The baseline weight of this criterion in the model is w2 = 37.0 percent (see annex 3 – step 6) and is indicated by the black vertical line. If the weight of this criterion is increased (to the right of the black vertical line) there is a point where cereals and grains (category 1) intersects with dried protein products (category 4) (point ➁: w’2 = 41.4 percent). If the weight of this criterion were further increased beyond point ➁, dried protein products (category 4) would have a higher rank. For every level below point ➁, cereals and grains (category 1) remained the highest. Notice that of the four criteria, burden of disease was considered to have the most serious impact. The sensitivity of the overall impact of every LMF category was analysed as the weight of criterion C3 (food consumption) ranged from 0 to 100 percent (Figure 3.3c). The baseline weight of this criterion in the model is w3 = 18.5 percent (see annex 3 – step 6) and is indicated by the black vertical line in Figure 3.3c. As the graph shows, whatever the priority (weight) placed on this criterion, the highest LMF category is always cereals and grains (category 1). The sensitivity of the overall impact of every LMF category was analysed as the weight of criterion C4 (food production) ranged from 0 to 100 percent (Figure 3.3d). The baseline weight of this criterion in the model is w2 = 27.8 percent (see annex 3 – step 6) (Fig 3.3d). As the weight of this variable decreases, there is a point where the cereals and grains (category 1) would intersect the dried protein products (category 4) (point ➂: w’4 = 20.0 percent). For weights below this level, dried protein products (category 4) ranks the highest. On the other hand, if the weight of this criterion were increased, there would be a another point where cereals and grains (category 1) would intersect with spices, dried herbs and teas (category 7) (point ➃: w’’4 = 52.0 percent). For weights above this level, spices, dried herbs and teas (category 7) should rank the highest. The range of weights provided by the experts for this criterion (w4 = [26.4 percent, 29.1 percent], Table 3.9) is between points ➂ and ➃, where the cereals and grains (category 1) has the highest score. These analyses of sensitivity on weights show that the ranking is quite robust to changes of priorities, with either cereals and grains (category 1) or dried protein products (category 4) always in the top position. There are no intersection points very near the baseline weights and, in all cases except for criterion 1 (international trade) (Figure 3.3a), there was not a range of weights provided by the experts that reached any intersection point. (For criterion 1, the lower bound of the range provided by experts was only slightly below the intersection point ➀). These RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 32 models (Figure 3.3) were used to identify the selection if their priorities increased or decreased from the baseline weights following suggestions by the expert group during the ranking exercise. The sensitivity analysis of the subcriteria for criteria 3 and 4 are presented in Annex 3 (Step 8) with similar results. In addition, an analysis of robustness considering the uncertainties about the evidence available, particularly in those subcriteria that were based on expert opinion, was undertaken as shown in Annex 3. 33 4. Discussion and conclusions 4.1 RANKING RESULTS Cereals and grains were in the highest position in the ranking that was undertaken. Its ranking was heavily influenced by all criteria, especially for the international trade and food consumption criteria, compared to most of the other categories. However, it also ranked among the top categories based on the other two criteria, burden of illness and food production. This is a diverse group of products, which are consumed globally and subject to many different production and preparation practices. It includes staple commodities for much of the world, and thus, measures to control the microbiological hazards associated with this category will potentially have wide reaching impact in terms of consumer health protection. Dried protein category was ranked second overall. Burden of disease was the dominating driver of the high score, primarily due to a couple of very large outbreaks associated with dried dairy products which led the increase of DALYs for this food category. Some experts did however express concern that these outbreaks were having too large an influence on the ranking of this category. While in general, many of the commodities in this category are produced under well-controlled conditions, but if something does go wrong, the potential impact can be extensive because of several factors: 1) the wide distribution of the products in this group (e.g. dried milk powder), 2) their extensive use as ingredients, and 3) the potential for these commodities to be prepared in a way that is favourable for microbial growth prior to consumption. 4 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 34 Spices, dried herbs and teas ranked third overall. Food production and burden of disease criteria were the driving factors. Despite the fact that these commodities are generally consumed in small amounts, there is ample opportunity for contamination during the production and processing stages. While they may be subjected to microbial inactivation treatments, these may not be suitable or permitted for all commodities in this category, or the treatments may not be adequate to reduce the contamination to levels which minimize the risk to consumer health if GAP/ GMP/GHP have not been applied along the production chain. In addition, it should be noted that several large outbreaks of salmonellosis associated with the food category have been observed. Nuts and nut products were ranked fourth, with burden of disease being the primary driver due to several outbreaks of international concern. For confections and snacks, there was a more even distribution of impact across all four criteria. Production conditions had the greatest impact for dried fruits and vegetables as well as for seeds, with limited or no impact from the other criteria. An extensive robustness analysis of the ranking results was conducted, considering both the criteria weights and the parameters where expert judgment was required. These analyses of the sensitivity on weights showed that the ranking was quite robust to changes of priorities, with either cereals and grains (category 1) or dried protein products (category 4) always the highest ranked – the latter would become the top ranked category if the weight of burden of disease were further increased. Due to the large volume of cereals and grains and dried protein products produced and consumed relative to other categories, it is not surprising that these ranked highly, and improvements in these industries are likely to have a larger impact on public health as compared to LMFs consumed in smaller portions and with lower frequency. In the context of this robustness analysis, the model was considered to be robust. The robustness analysis can also help in identifying the changes in the ranking if significant changes in weights, away from the baseline weights established by experts, are considered. 4.2 KNOWLEDGE SYNTHESIS AND DATA COLLECTION TO SUPPORT DECISION-MAKING Synthesis research methodologies such as systematic review offer transparent and replicable methods to identify, critically appraise and synthesize the available research literature on a clearly formulated question (Young et al., 2014; Sargeant et al., 2014; Higgins and Green, 2011). Thus, synthesis research results provide a valuable means of underpinning evidence-informed policy making and supporting CHAPTER 4 - DISCUSSION AND CONCLUSIONS 35 risk analysis in food safety and public health because of the improved transparency and accountability they lend to the process (Rajić, Young and McEwen, 2013). Meta-analysis is a statistical method to combine results from similar studies identified in a systematic review, which measure the same outcome, into an overall average estimate of effect (Young et al., 2014; Sargeant et al., 2014). This ranking process used evidence-informed inputs from a rapid scoping and systematic review that synthesized global evidence and presented meta-analytic summaries of the current knowledge of microbial food safety (prevalence and concentration), burden of illness and effectiveness of interventions against microbial contamination of LMF. Some of the key points in relation to data highlighted by this process include the following: • There is considerable variability in the quantity and quality of data for prevalence and concentration of selected microbial hazards in various LMF products. Some prevalence estimates were underpinned by more than ten studies and represented surveys from around the world, whereas others may have only been underpinned by one or two small studies from disparate regions. Meta-analytic summaries of prevalence data were computed where possible. Data related to important contamination thresholds for toxin-producing bacteria and the proportion of contaminated samples likely to exceed the thresholds were extracted from the literature identified in the scoping review. However, the amount of data available for this additional and informative analysis was limited. • Burden of illness data was almost exclusively related to outbreaks. It was the outbreak data that was used to calculate DALYs for each LMF category as an indicator or relative measure of the potential burden of illness. No primary data was available on sporadic cases of illness related to LMF. • Burden of illness data was considered by the experts to under-represent what is likely occurring in reality as many LMFs are components of mixed dishes and multi-ingredient foods, and the likelihood of them being associated with illness is significantly lower than for other foods, e.g. ground beef or eggs. However, the outbreaks represent a signal that something has gone wrong, and while these may be only a fraction of actual illness caused by LMF, the experts decided that this was the best information we have and that it should be used for the relative ranking between categories. • Intervention studies identified from the literature were largely small challenge trials that used artificially inoculated samples and were conducted under laboratory conditions. These studies suffered from small sample sizes and potentially exaggerated effectiveness due to the challenge. Most interventions were not commercialized or conducted under commercial conditions, and RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 36 therefore the generalizability is limited. However, many interventions are implemented on a commercial scale in some LMF industries (e.g. nuts and spices), and the experimental trials results indicate that many reduce but do not eliminate hazards from LMF. Therefore, prevention of cross-contamination and GHP/GMP/HACCP based controls are important to minimize hazards in LMF. • The LMF categories represented broad categories of products that had highly variable data depending on the array of products the category represented. For those LMF which are consumed in a state close to the primary commodity, e.g. nuts and seeds, there were adequate data to allow characterization of the situation. However, for more complex products such as confections and snacks, or those categories such as cereals and grains where there are a very large number of potential products, a number of assumptions had to be made to enable use of the data. LMF categories covered a diverse number of categories and products. The work that went into this report, summarizing the literature, gathering additional data and obtaining expert opinion very carefully tried to balance the complexity of the industries which produce the LMFs of interest with the desire to summarize by larger categories. This was done to get an appreciation for those categories where guidelines and improved production practices may have the largest impact on the quality of the food and public health. It is anticipated that some categories will need to be organized into subcategories with related production processes to develop good production practices. 4.3 MCDA AS A RANKING APPROACH FOR FOOD SAFETY ISSUES The multi-criterion decision analysis (MCDA) process, when professionally facilitated, offers a clear transparent approach to ranking options. The experts were challenged to step outside of their particular area of expertise and consider LMF diversity on a global scale. The resulting ranking makes sense from this global perspective. While the output of this ranking process was considered to be reasonable, the approach, like others, is still something that is reflective of the time it was undertaken, the specific set of participants and the available data. If this exercise was repeated at a regional or country level, the outcome might be different. Similarly, there may be the possibility to more narrowly define the categories of interest considering consumption patterns within a country or region of interest. CHAPTER 4 - DISCUSSION AND CONCLUSIONS 37 However, the MCDA approach facilitated the combination of quantitative and non-quantitative inputs on a range of criteria, which would otherwise not likely have been possible to synthesize. The MCDA approach used here runs counter to traditional risk assessment modelling, in part because it includes parameters relating to options that do not relate to human health risk, such as trade importance, and in part because it is built upon value judgments about the relative importance of independent criteria rather than an objective assessment of risk. There is a well-understood and codified set of principles that guide risk assessment, risk management, and risk communication, but such guidelines are lacking for the use of decision-analysis approaches in food safety. Additionally, participating in an MCDA exercise can provide a challenge for experts who may not be comfortable providing value judgments and who tend to be more familiar risk assessment models with distinct underlying mathematical structures. This process has not highlighted LMFs where there is evidence and willingness for change within the production industry. This was outside of this project’s scope but would potentially be of interest when evaluating where influence and impact could happen easily and quickly within the industry. 4.4 CHALLENGES AND BENEFITS OF PROCESS The use of synthesis methodology to provide evidence-based summaries of the global knowledge to guide expert discussions, and as inputs (where appropriate) into the MCDA was a valuable addition to the process, especially with the diverse topic of LMF, where no expert necessarily had knowledge across all categories. The synthesis report (Annex 1) provided a basis for discussion and a transparent list of the available evidence including outbreaks. Furthermore, it was recognized by the expert group that the output of the knowledge synthesis alone serves as a valuable resource in itself to inform risk managers on the issues and challenges associated with LMF. The synthesis methodologies and the MCDA approaches require time and expertise to execute, and they were new to most of the experts. As a result, time was required during the consultation process to introduce the concepts and continually reiterate strengths and challenges with these methods. A major strength of the synthesis methodology is transparency and inclusiveness. This was highlighted on several occasions during the consultation process where the content was challenged primarily for possible missing information (outbreaks primarily). However, the RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 38 outbreak or article, or an explanation of why it did not meet the inclusion criteria identified, was on each occasion located in the synthesis documentation. There were a number of challenges to be overcome in the development of a ranking approach. Firstly, there was the need for a global perspective in the assessment. Secondly, multiple impacts of concern existed. Thirdly, there was a limited amount of evidence about some of these impacts. Lastly, there was the need to incorporate the expertise and opinions of the expert panel supporting the ranking process. The evaluation model that was developed had several important features. Firstly, it was grounded on an appropriate decision frame that considered the nature of the impacts to be assessed. Secondly, it considered decision criteria and associated measurements (attributes) that fulfilled the required properties for a rigorous value assessment and for the unambiguous assessment of impacts. Thirdly, it represented criteria weights that were appropriately elicited using psychometrically valid procedures, and which fulfilled the required properties demanded by multi-attribute value theory. Finally, it was based on a robust methodology and was fit-for-purpose, given the evidence available and the defined criteria. The modelling process that was developed had several benefits. It organized the many conflicting criteria under consideration and clarified and adequately measured the impacts of each LMF category on the criteria considered, given the evidence available. It enabled the aggregation of partial impacts into an overall impact given the associated trade-offs, and thus scientifically-based the ranking of LMF categories and ensured a successful deployment of the evaluation model by involving key experts during the decision modelling process. Lastly, it supported the sharing of information, opinions and perspectives among the experts, enabling a better understanding of the evaluation problem and learning about the evidence, impacts, priorities and the final ranking. 4.5 CONCLUSIONS This ranking exercise aimed to capture the situation from a global perspective and was driven by the ranking criteria and how they were weighted, and the expert panel itself which drove the process. The ranking is also a reflection of the available evidence and expert opinion at the time the work was undertaken. If undertaken at a regional or national level, or even at the global level again in the future, the inputs are likely to be different and therefore, the outcome may also be different. The MCDA approach, which is not widely used as yet in the food safety area, facilitates the consideration of factors such as extent of international trade, i.e. factors not CHAPTER 4 - DISCUSSION AND CONCLUSIONS 39 directly related to risk to human health. However, it is also recognized that for many regulatory authorities risk to human health is the most important and may be the only criteria which they wish to consider. In this case, for example, the review of available data presented in Annex 1 can serve as an extensive resource to support ranking or decision-making at national level. Another challenge in undertaking this work was the diversity of low-moisture foods it covers, even within the categories. This is a limitation of the global approach and undertaking such an exercise at the national or local level may facilitate a more focused list of categories based on local consumption patterns or a further subdivision of the categories considered in this work. Indeed, in some cases it may be necessary to look within the categories to determine the specific commodity hazard combinations of greatest concern. FAO and WHO have recently undertaken such an approach for the category of spices and dried aromatic herbs and a report on this is forthcoming (FAO and WHO, 2016). The expert group also noted that certain LMF stand out due to the characteristics of the consuming population rather than the product itself. One example is powdered formulae for infants and young children. These were excluded from this ranking as risk management guidance and standards already exist at an international level. However, when undertaking such a ranking at the national level, it may be important to include such products. Another group of products considered were low-moisture lipid-based, ready-to-use which have recently been identified as potentially being contaminated with Salmonella and Cronobacter spp (FAO and WHO, 2016). The expert meeting recommended at this point in time that these products not be included as a separate category for ranking purposes due to the limited data currently associated with these foods. However, in some parts of the world it may be important to give greater prominence to these types of products in any ranking exercise. Thus, while this category of products was not further considered explicitly in this ranking, it was recommended that CCFH make reference to these in the Codex Code of Hygienic Practice for LMF. This can help ensure that there is broad awareness of the wide range of LMF products that are consumed. 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Preventive Veterinary Medicine, 113: 339–355. 44 Attributes: the performances indices that enable the evaluation of the impact of every option on each criterion considered in a multi-criteria evaluation Decision theory: a normative theory, based on mathematical axioms, that prescribes how rational decisions should be made Evaluation criteria: the variables that decision makers/assessors want to consider when assessing options in decisions with conflicting objectives or multi-criteria evaluations Fundamental objectives: the fundamental concerns that decision makers/ assessors want to take into account in decisions with conflicting objectives or multi-criteria evaluations Impacts: the possible consequences that each option may generate on the criteria considered in the multi-criteria evaluation, given the evidence available Means-end network of objectives: a qualitative model that represent the means objectives available to decision/policy makers to achieve their fundamental and ultimate objectives Measurement theory: a theory that defines how measurements should be made to assure the compatibility between stimuli (e.g. judgment) and responses (e.g normalized impacts) 6. Glossary 6 45CHAPTER 6 - GLOSSARY Meta-analysis: a statistical technique to obtain weighted estimates of effect, association or prevalence on data from multiple, similar primary research studies collected in a systematic review Multi-attribute value theory: a multi-criteria methodology to support the assessment of the overall value of options by evaluating their partial value on every criterion for impacts that are deterministic Multi-criteria decision analysis: a group of methodologies to support decision-making when there are conflicting objectives to be achieved when evaluating and choosing options Multi-criteria value model: an evaluation model which represents the evaluation criteria, the criteria weights, and the normalized impacts of the options, and enables the evaluation of the overall impact of each option under consideration Normalized impacts: the rescaled impacts of options being evaluated, on a 0–100 scale (where the option with the lowest impact is set as 0, the one with the highest impact as 100, and the other options scored proportionally to those two bounds of the scale). The unit of normalized impacts is disvalue (the higher the number, the highest is the concern about it). Overall normalized impact: the normalized impact of every option being evaluated, on a 100-0 scale, which is obtained by aggregating all the normalized impacts from the criteria. The unit of overall normalized impacts is disvalue (the higher the number, the higher the concern about it). Preferential independence: a logical property of the criteria that enables the assessor to evaluate the impacts of options on one criterion independently of their impacts on all the other criteria of the model Robustness analysis: an analysis designed to explore the robustness of the ranking provided by a multi-criteria evaluation regarding the input parameters of the model (impacts and weights) Sensitivity analysis: an analysis designed to explore how sensitive to input parameters of the multi-criteria model the option with the highest overall impact is Rapid review: a streamlined scoping or systematic review that uses some shortcuts or restrictions in the standardized review process to synthesize evidence about a given topic or question in short timelines and/or using limited resources to directly inform urgent decision-making RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 46 Scoping review: a structured and transparent knowledge synthesis methodology used to identify, characterize and describe the distribution of evidence on a broad research question or topic area Systematic review: a structured and transparent knowledge synthesis methodology used to identify, appraise, summarize and analyse all the available research literature on a clearly defined question or topic Swing-weighting method: a valid elicitation protocol to elicit criteria weights for multi-criteria value models, by presenting the ranges of attributes associated with the evaluation criteria and asking decision makers to value such ranges 47 Annexes 48 Annex 1 Rapid scoping and systematic review meta – analysis of research knowledge This annex was prepared by Ian Young, Lisa Waddell, Andrijana Rajic, Sarah Cahill, Mina Kojima and Laura Dysart in February 2016. A1.1 INTRODUCTION AND OBJECTIVES This report summarizes the results of a structured and transparent scoping and systematic review – meta-analyses of three key aspects of the microbial food safety of LMF: 1. the burden of illness due to microbial contamination of LMF; 2. the prevalence and concentration of microbial hazards in LMF; and 3. interventions to reduce microbial contamination of LMF. Synthesized research findings for these three focus areas will be used as evidence-informed inputs along with additional supporting criteria in a comprehensive risk ranking process of microbial hazards in LMF. The results of the review and risk ranking process will be used to inform the new Codex Alimentarius guidelines for LMF. A1.2 REVIEW METHODS A1.2.1 Review approach The review followed standardized procedures for scoping and systematic reviews as outlined by internationally recommended guidelines (Anderson et al., 2008; Arksey and O’Malley, 2005; Higgins and Green, 2011; Rajić and Young, 2013). However, given the very broad review scope, large quantity of published research in this area, small review team, and a limited timeline of <4 months for producing results and a final report, some of the review steps were streamlined in accordance with the principles of structured “rapid reviews” to inform urgent decision-making (Ganann, Ciliska and Thomas, 2010; Rajić and Young, 2013): • Only two bibliographic databases were searched for peer-reviewed literature. However, we implemented a very comprehensive search verification strategy (described below) and are confident that any literature potentially missed by the searches was captured during verification. ANNEX 1 49 • Only one reviewer conducted data extraction instead of the recommended two independent reviewers. This limitation could have resulted in some errors in the results, but we believe it would not have unduly affected the overall conclusions. The review was built upon a preliminary and unpublished rapid scoping and systematic review of the same research questions conducted in 2013 (Rajić, Dysart and Cahill, unpublished data). The preliminary review was conducted by an external contractor and was used as a basis for development of the review protocol, questions, search and forms as described in this review. A1.2.2 Review protocol and team The review was conducted following a pre-specified protocol outlining each of the review steps as described in this report, including screening and extraction forms. The review team consisted of five professionals with diverse expertise and experience in microbiology, food safety, epidemiology, and knowledge synthesis, transfer and exchange. Two professionals from the Public Health Agency of Canada conducted the review activities with oversight and coordination from three professionals from the FAO and WHO. The team convened via teleconference prior to initiating the review and exchanged correspondence regularly thereafter to discuss the protocol and all screening and extraction forms, to evaluate questions about review scope and eligibility criteria, to review the study progress and preliminary results, and to determine a strategy for summarizing and reporting results. A1.2.3 Review questions The review was conducted to answer the following three research questions: • What is the burden of illness in humans suspected or attributed to LMF contaminated with pathogenic bacteria? • What is the frequency of contamination (prevalence and concentration) of selected microbial hazards in LMF? • What are the potentially effective interventions (from primary production to the end of processing) to mitigate risks associated with contaminated LMF? A1.2.4 Definitions and eligibility criteria The review scope was limited to the following nine selected microbial hazards: Bacillus cereus, Clostridium botulinum, Clostridium perfringens, Cronobacter spp. (formerly Enterobacter sakazakii), Escherichia coli (including generic E. coli and pathogenic strains), Salmonella spp., Staphylococcus aureus, Listeria monocytogenes and Enterobacteriaceae. Other bacterial pathogens, indicator organisms, viruses, RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 50 parasites and fungi were excluded from the scope of this review. Note that unless otherwise specified, the term E. coli is used in this report to refer to both generic and pathogenic strains; in the summary cards, evidence on E. coli is divided into generic E. coli and specific pathogen strains (e.g. E. coli O157). LMF were defined as any food product with a water activity (aw) level of less than 0.85. Categories and subcategories of LMF products were developed to facilitate data organization, summarization and reporting. Eight major LMF product categories were used to structure this report: • cereals and grains; • confections and snacks; • dried fruits and vegetables; • dried protein products; • honey and preserves; • nuts and nut products; • seeds for consumption; and • spices, dried herbs and tea. Results for the burden of illness, prevalence, and intervention information are reported in category-specific summary cards for each LMF product category. A full list of the subcategories and example LMF products for each of these categories is shown in Appendix A, with additional details reported in the summary cards. Composite LMF products with multiple ingredients were assigned to only one of the above categories, either according to where the product best fit (e.g. mixed cereal/grain products were classified under “cereals”) or according to the primary ingredient of concern for contamination (e.g. halva/helva was classified under seeds for consumption as the contaminated ingredient of concern is sesame seed paste). Powdered infant formula was specifically excluded from the scope of this review because international Codex Alimentarius Commission guidelines for these products were recently updated based on a prior risk assessment (FAO and WHO, 2004, 2008). Articles describing the validation of diagnostic tests for the detection of microbial hazards in LMF and those examining interventions at the consumer level (e.g. cooking) were also excluded. For burden of illness information reported in this review, we defined an outbreak as two or more individuals with a similar illness resulting from consuming a common food product and with either an epidemiological or laboratory confirmation (Greig ANNEX 1 51 and Ravel, 2009). We also included case studies where only one reported case of illness occurred due to a confirmed or suspected contaminated LMF product (e.g. infant botulism cases due to honey consumption). Only primary research on burden of illness information was included; foodborne illness attribution studies using outbreak data and/or expert elicitation to attribute foodborne illness to specific food groups or commodities (usually not specific LMF products) were excluded (Havelaar et al., 2008; Batz et al., 2012; Painter et al., 2013). Information on LMF recalls were not summarized in this scoping review. While the scoping review may have captured some of this information if published in peer-reviewed journals and indexed in the bibliographic databases included in the search, most would be contained only in food recall databases which were not searched in this review. A1.2.5 Search strategy The preliminary scoping and systematic review conducted in 2013 was used as a basis for development of a comprehensive search algorithm (Rajić, Dysart and Cahill, unpublished data). This prior review extracted keyword terms from 11–14 known relevant articles from each of the three research questions (burden of illness, prevalence, and intervention information), combined them into a search algorithm and pre-tested the algorithm in PubMed to achieve a highly specific search. In this review, we updated and refined this search algorithm through additional pre-testing in PubMed to improve the sensitivity of the search. The final algorithm contained c-mbinations of keywords in three broad categories: LMF product terms, microbial hazards terms and outcome terms (Appendix B). The search was implemented in two bibliographic databases (Scopus and PubMed/Medline) on 13 January 2014. There were no language or publication date restrictions on the search. Scopus coverage included 1823–2014 and PubMed coverage included 1946–2014 (coverage included “in press” articles). The search was verified through multiple steps. Firstly, we reviewed the final reference list of 464 relevant articles identified in the preliminary scoping and systematic review (Rajić, Dysart and Cahill, unpublished data). The preliminary review included a web search in Google using the terms “low-moisture food,” “low-water activity food” and “dry food pathogens”; it included a search of the reference lists of eight review articles and reports relevant to the review questions (Beuchat et al., 2011; Beuchat et al., 2013; Grocery Manufacturers Association, 2009a, 2009b; Pan et al., 2012; Podolak et al., 2010; Scott et al., 2009; Zweifel and Stephan, 2012), and it included a hand search of the reference lists of all included, relevant articles in the review (Rajić, Dysart and Cahill, unpublished data). In this RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 52 review, we conducted additional verification by reviewing the reference lists of eight additional articles relevant to the review questions (Dey et al., 2013; Friedemann, 2007; Holck et al., 2011; Lehner and Stephan, 2004; Sperber, 2007; Van Doren et al., 2013a, 2013b) and through hand-searching the reference lists of relevant articles. To identify additional grey literature sources of burden of illness (i.e. outbreak) information for LMF products, we searched a comprehensive database of international foodborne disease outbreak reports including the Public Health Agency of Canada (Greig and Ravel, 2009). The database comprises >7 900 outbreak reports from multiple sources: journal articles, newspapers, listservs, press releases, country line lists, and government and laboratory websites by using the same approach as Greig and Ravel (2009). To search the database, all outbreaks implicating LMF products and the selected microbial hazards were queried and used to obtain all recorded information about the outbreak. A1.2.6 Relevance screening Screening of the titles and abstracts of all unique citations identified in the search was conducted using an a priori developed screening form (Appendix C). The form contained one yes/no question to determine the relevance of citations for the project as described above. If the title and abstract did not provide sufficient detail to determine the article’s relevance (e.g. “confectionary items,” “sweets,” and “snacks” may not be referred to as LMF), the article was automatically included at this stage for further evaluation. A1.2.7 Relevance confirmation and article characterization Full texts of all relevant citations were obtained, and articles were reviewed using a relevance confirmation and article characterization form (Appendix D). This contained four questions: confirmation of relevance and research question of focus (burden of illness, prevalence and/or interventions); article language; LMF product categories; and microbial hazards investigated. Only articles in English, French and Spanish were included at this stage unless there was sufficient extractable data from an English abstract. Results from this initial characterization were used to prioritize more detailed data extraction. In addition, after charting these characterization results, the review team decided to exclude dried and/or fermented sausages, salamis and jerkies from further extraction and summarization. This category of products was considered beyond the scope of this review given the large volume of research identified in this area and because we were not able to confirm the aw of many of these products ANNEX 1 53 due to reporting limitations in the literature. In addition, at this stage we decided to exclude all articles that investigated the prevalence or concentration of microbial hazards in LMF published prior to 1990, as these were not considered relevant or reflective of the current state of evidence to inform the risk ranking process or Codex Alimentarius standards. A1.2.8 Data extraction Data were extracted from each article confirmed as relevant using one of three specific data extraction forms developed for each research question of focus (burden of illness, prevalence and interventions) (Appendix E). The burden of illness form contained 17 questions about the source of the outbreak report; year; region/country; outbreak confirmation method (epidemiological or laboratory); specific LMF and microbial hazards implicated; the number of exposed persons, cases, hospitalizations, deaths, attack rate; and other outbreak details (e.g. microbial hazard concentration in the implicated LMF). The prevalence form contained 21 total questions, including ten general questions about the article details (e.g. publication year), study location, study design and sampling methods. Prevalence and concentration data were confirmed to be sampled independent of an outbreak investigation. The 11 other questions were extracted for each LMF product and microbial hazard combination investigated: LMF category and product, microbial hazard, country of product origin, outcome (prevalence and/or concentration data), whether outcome data were sufficiently reported, laboratory methods, and quantitative prevalence and concentration data (e.g. sample size, number positive, mean values and measures of variability). Similarly, the intervention form contained 20 total questions, with nine general questions about the article details (e.g. publication year), study location, study design, and whether the intervention was conducted under commercial conditions. The other 11 questions were extracted for each LMF product and microbial hazard combination: LMF category and product, microbial hazard, intervention type and details, whether the intervention found a statistically significant reduction in the concentration or prevalence of microbial hazards, outcome type, laboratory methods, whether outcome data were sufficiently reported, and the sample size. A1.2.9 Data analysis Data for all three questions of interest (burden of illness, prevalence and interventions) were summarized descriptively and reported in a tabular and narrative format. In addition, overall and LMF category-specific evidence charts RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 54 were created to highlight cross-tabulations between combinations of the following variables: research question of focus, LMF categories investigated, and microbial hazards investigated. The evidence charts were created using bubble figure plots in Microsoft Excel, where each cross-tabulation value is represented by bubbles that are proportional in size to the total number of articles. For prevalence data, we conducted meta-analysis on data subsets to obtain weighted average estimates of the prevalence of microbial hazards in LMF. Random-effects meta-analysis models were calculated for each LMF subcategory and microbial hazard combination with prevalence data from ≥2 articles when at least one of the articles reported non-zero prevalence. The models were calculated using the DerSimonian and Laird method for random-effects (DerSimonian and Laird, 1986). In addition, we used a double arcsine transformation to stabilize the variance of the input data (Barendregt et al., 2013; Freeman and Tukey, 1950). This transformation was necessary because the data subsets often contained low prevalence levels and a high proportion of zero values, and these situations can add undue weight to outlying prevalence values when using a standard log transformation (Barendregt et al., 2013; Fazel et al., 2008). The unit of analysis was prevalence within trials, and in some cases, there was more than one trial reported within an article. We did not account for the extra level of variation due to trials being clustered within articles as this was unlikely to have much consequence on the overall estimates. Heterogeneity in the meta-analysis estimates was assessed using I2, which measures the proportion of variation between trials that is due to heterogeneity rather than random error (Higgins et al., 2003). The following values of I2 were used to categorize the level of heterogeneity: ≤30 percent was considered low; 31–60 percent medium; and >60 high (Higgins and Green, 2011). Average estimates of effect were calculated and reported only if heterogeneity was low or moderate. When heterogeneity was high (i.e. >60 percent), we instead reported the median and range of the prevalence values within the data subset, as reporting meta analytic average estimates may be misleading with so much variation (Higgins and Thompson, 2002). A1.2.10 Review management All citations identified in the search were entered into RefWorks (Thomson ResearchSoft, Philadelphia, PA), and duplicates were removed using the automatic function and manually. Unique citations were imported into the web-based, systematic review software program DistillerSR (Evidence Partners, Ottawa, ON) for relevance screening and article characterization. Data extraction and descriptive analysis were conducted using Microsoft Excel 2010 (Microsoft Corporation, ANNEX 1 55 Redmond, WA). Meta-analysis was conducted using the Excel add-in MetaXL (EpiGear International Pty Ltd., Wilston, Australia). The forms used for relevance screening and article characterization were pre-tested on a selection of 30 abstracts and six articles, respectively. Reviewing proceeded only when consistent inclusion and exclusion agreement was achieved between pre-test reviewers (kappa>0.8). Relevance screening was conducted by two independent reviewers, and discrepancies or conflicts between reviewers were resolved by consensus. Article characterization and extraction were conducted by one reviewer. A1.2.11 Summary cards Results of this review are reported in eight “summary cards” representing the major categories of LMF products (Ruzante et al., 2010). The summary cards were developed to display the results of the review in a more useful and practical format to better meet the stakeholders’ needs. More specifically, the purpose of the summary cards is to highlight the key findings for each of the research questions of interest (burden of illness, prevalence, and intervention information) to better support future risk ranking, risk management and decision-making on the microbial food safety of LMF products. Each summary card contains the following six sections: • LMF category description • Overall evidence summary • Burden of illness summary • Prevalence summary • Interventions summary • References The LMF category description section briefly provides key definitions related to the LMF products, describes LMF product subcategories used to summarize the information, and provides examples of specific LMF products. The evidence summary section briefly highlights the amount of evidence included in the summary and describes an evidence chart showing the distribution of available research by research question focus and microbial hazards investigated. The burden of illness, prevalence, and intervention sections each provide a short (<1 page) narrative summary of the available evidence and key descriptive characteristics and results. In addition, they also provide accompanying tables and figures that describe the evidence and results in more detail. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 56 The burden of illness table lists all identified outbreaks stratified by LMF product (or subcategory) and causative microbial hazard. Quantitative data on the number of outbreaks reported and total cases, hospitalizations, and deaths are reported for each food product and microbial hazard combination. Also reported are the outbreak countries and years, reference publications, and any additional details (e.g. whether susceptible populations were affected, the attack rate and the concentration of the microbial hazard in the LMF product). The prevalence table shows the average or median prevalence estimates for each LMF subcategory and microbial hazard combination. For each cell in the table, three lines of data are shown. The first shows the total number of observations (i.e. food product samples), the total number of individual trials (i.e. food product and microbial hazard combinations), and the total number of articles for each combination. In brackets beside these numbers is the percentage of all trials that did not identify any positive samples (i.e. the prevalence was 0 percent). This measure is provided as an indicator of how often trials identified any positive samples in that LMF subcategory/microbial hazard combination. The second line of prevalence data shows either of the following: • an average estimate of the prevalence from a random-effects meta-analysis for that combination (with 95 percent confidence intervals in brackets), or • the median prevalence value and the range (minimum and maximum values in brackets). The third line in the prevalence table reports two indicators of the representativeness of the prevalence information: • level of consistency in the prevalence data obtained from the heterogeneity measure I2 during meta-analysis (classified as low, medium, or high), and • risk of selection bias due to a non-representative sample (also classified as low, medium, or high). Heterogeneity refers to the variability among studies summarized in a meta-analysis. In the context of this review, the variability in prevalence estimates between studies could be due to differences in study design, sampling and laboratory methodology, geographic location, and/or specific food products investigated, among many other factors. The extent of this variability was measured using the I2 statistic, which indicates (on a scale from 0–100 percent) how different the studies are from each other than would be expected by chance (random error) alone. Heterogeneity ANNEX 1 57 rating definitions were as follows: low = I2 0–30 percent; medium = 31–60 percent; high = >60 percent. For meta-analysis estimates with high heterogeneity (i.e. I2 >60 percent), it can be misleading to present and interpret average prevalence estimates because there is so much unexplained variation between studies. The main meta-analysis assumption is that studies are reasonably comparable and measure the same effect estimate. High heterogeneity may indicate this assumption has been violated, and studies should not be pooled. Therefore, only the median and range are provided for prevalence data if there was significant heterogeneity (i.e. I2 was >60 percent) in the meta-analysis estimates. A superscript of M indicates that the prevalence values represent average estimates from meta-analysis, and a superscript of R indicates that the values represent the median and range. Studies that conducted random or systematic sampling of LMF products were considered to be representative. Selection bias ratings were defined as follows: low = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. When heterogeneity is low and the risk of selection bias is low (i.e. the proportion of studies with a representative sample is high), we have confidence that the reported meta-analysis prevalence estimate is likely reflective of the true average prevalence value across a group of studies that were generalizable to their target commodity. When the opposite is true, heterogeneity is high and there is high risk of selection bias (i.e. few studies had a representative sample), we have little confidence in the meta-analysis overall prevalence estimate as it may be based on unrepresentative data and the variability in results is not explainable. This could mean that the outcome is truly highly variable, or that there are unmeasured context-specific influences affecting the reported prevalence (e.g. geography, time of sampling, study design and methods, etc.). Note that to obtain a normal account of the prevalence and concentration of microbial hazards in LMF, we excluded any surveys conducted during an outbreak or associated with an outbreak investigation. A forest plot figure describing the information captured in the prevalence table is shown following each prevalence table to graphically illustrate the meta-analysis RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 58 results across all microbial hazard and LMF subcategories. Note that microbial hazards were excluded from these figures if no positive samples were identified in the LMF category/summary card. Enterobacteriaceae prevalence results were also excluded from these figures. The forest plot figures are meant to facilitate the interpretation of meta-analysis results within each LMF category and summary card. In these figures, the results of high heterogeneity meta-analyses are presented along with the median and range from the previous table. It was decided that this was the most informative way to convey the results for risk ranking and decision-making; however, we caution our readers that due to high unexplained heterogeneity, the overall estimates of prevalence in the forest plot figures should be interpreted with caution. The intervention table shows all investigated interventions stratified by LMF subcategory and intervention type. For each LMF subcategory/intervention type combination, the table shows the specific interventions applied (including dose and duration, when available), the source publications for each specific intervention, the microbial hazards investigated, the study type, the total number of trials and articles, the percentage of trials with extractable data, and the percentage of trials that found a statistically significant reduction in the concentration or prevalence of microbial hazards due to the intervention. In addition, for any LMF subcategory/intervention type combination with ≥2 articles, a sign test was calculated to determine if the number of trials finding a positive intervention effect was greater than what would be expected by chance alone. If the sign test was significant (P <0.05), this was indicated by an asterisk (*) and bold text in the final column of the table. 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International Journal of Food Microbiology, 116(1): 1–10. Ganann, R., Ciliska, D. & Thomas, H. 2010. Expediting systematic reviews: Methods and implications of rapid reviews. Implementation Science, 5(1): 56. Greig, J.D. & Ravel, A. 2009. Analysis of foodborne outbreak data reported internationally for source attribution. International Journal of Food Microbiology, 130(2): 77–87. Grocery Manufacturers Association. 2009a. Annex to control of Salmonella in low-moisture foods. Arlington, VA, USA. (also available at https:// forms.consumerbrandsassociation.org//forms/store/ProductFormPublic/ SalmonellaControlGuidance-Annex). Grocery Manufacturers Association. 2009b. Control of Salmonella in low-moisture foods. Arlington, VA, USA. (also available at https://forms.consumerbrandsassociation. org/forms/store/ProductFormPublic/SalmonellaControlGuidance). Havelaar, A.H., Galindo, A. V., Kurowicka, D. & Cooke, R. M. 2008. Attribution of foodborne pathogens using structured expert elicitation. Foodborne Pathogens and Disease, 5(5): 649–659. Higgins, J.P.T. & Green, S., eds. 2011. Cochrane handbook for systematic reviews of interventions: Version 5.1. London, the United Kingdom. The Cochrane Collaboration. Higgins, J.P.T., Thompson, S.G., Deeks, J.J. & Altman, D.G. 2003. Measuring inconsistency in meta-analyses. BMJ (Clinical Research Ed.), 327(7414): 557–560. Higgins, J.P.T. & Thompson, S.G. 2002. Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21(11): 1539–1558. Holck, A.L., Axelsson, L., Rode, T.M., Høy, M., Måge, I., Alvseike, O., L’Abée-Lund, T.M., Omer, M.K., Granum, P.E. & Heir, E. 2011. Reduction of verotoxigenic Escherichia coli in production of fermented sausages. Meat Science, 89(3): 286–295. Lehner, A. & Stephan, R. 2004. Microbiological, epidemiological, and food safety aspects of Enterobacter sakazakii. Journal of Food Protection, 67(12): 2850–2857. Painter, J.A., Hoekstra, R. M., Ayers, T., Tauxe, R. V., Braden, C.R., Angulo, F. 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Ruzante, J.M., Davidson, V.J., Caswell, J., Fazil, A., Cranfield, J.A.L., Henson, S.J., Anders, S.M., Schmidt, C. & Farber, J.M. 2010. A multifactorial risk prioritization framework for foodborne pathogens. Risk Analysis, 30(5): 724–742. Scott, V.N., Chen, Y.U.H., Freier, T.A., Kuehm, J., Moorman, M., Meyer, J., Morille- Hinds, J., Post, L., Smoot, L., Hood, S., Shebuski, J. & Banks, J. 2009. Control of Salmonella in low-moisture foods I: Minimizing entry of Salmonella into a processing facility. Food Protection Trends, 29(6): 342–353. Sperber, W. H. & North American Millers’ Association Microbiology Working Group. 2007. Role of microbiological guidelines in the production and commercial use of milled cereal grains: A practical approach for the 21st century. Journal of Food Protection, 70(4): 1041–1053. United States Food and Drug Administration (USDA). 2013. Draft risk profile: Pathogens and filth in spices. Washington, DC. (also available at http://www.fda. gov/downloads/Food/FoodScienceResearch/RiskSafetyAssessment/UCM367337. pdf). Van Doren, J.M., Kleinmeier, D., Hammack, T.S. & Westerman, A. 2013a. Prevalence, serotype diversity, and antimicrobial resistance of Salmonella in imported shipments of spice offered for entry to the United States, FY2007-FY2009. Food Microbiology, 34(2): 239–251. Van Doren, J.M., Neil, K.P., Parish, M., Gieraltowski, L., Gould, L.H. & Gombas, K. L. 2013b. Foodborne illness outbreaks from microbial contaminants in spices, 1973- 2010. Food Microbiology, 36(2): 456–464. Zweifel, C. & Stephan, R. 2012. Spices and herbs as source of Salmonella-related foodborne diseases. Food Research International, 45: 765–769. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 62 FIGURE A1.1 Review flow chart A1.4 REVIEW EVIDENCE SUMMARY A flow chart of the review process and findings is shown in Figure A1.1. Overall, 6 765 citations were screened for relevance, 848 full articles were procured and characterized, and 428 were confirmed as relevant to the review scope. In addition, 135 outbreak from the database involving LMF were also identified and summarized. Excluded (not relevant): 417 Investigated/fermented sausages, salamis or jerky’s: 135 Not a LMF of interest: 68 Other language: 60 Water activity > 0.85: 38 Irrelevant study design or type: 36 Prevalence pre-1990: 36 Review article/not primary research: 19 Not a MH of interest: 18 Duplicate data: 4 Article not retrievable: 3 Se ar ch R el ev an ce sc re en in g R el ev an ce c on fir m at io n Ev id en ce M ap pi ng Excluded (duplicates): 2 290 Excluded (not relevant): 5 917 Burden of illness: 239 outbreak reports* From review: 104 (reporting on 80 unique outbreaks and observational studies) Unpublished: 135 Interventions: 126 articles* Prevalence: 204 articles* *Note: some articles (n=8) contained data in more than one of the above categories. In addition, individual outbreak reports were sometimes reported in more than on article, so the total number of unique articles and outbreak reports was 537. Search total: 9 055 Data search: 8 876 Outbreak database: 21 Preliminary review verification: 93 Additional verification: 65 Citations screened: 6 765 Additional unpublished outbreaks: 135 Articles characterized: 848 Relevant articles: 428 English, Spanish and French language articles: 413 Other languages with extractable data from English abstract: 15 ANNEX 1 63 Among all unique articles and outbreak reports (n=537), the most investigated LMF product categories were the following (Figure A1.2): • Cereals and grains (n=142) • Spices, dried herbs and tea (n=129) • Nuts and nut products (n=95) The most frequently investigated LMF products for prevalence, intervention, and burden of illness information were the following (Figure A1.2): • Prevalence = Spices, dried herbs and tea (n=77) • Interventions = Nuts and nut products (n=51) • Burden of illness = Cereals and grains (n=72) FIGURE A1.2 Evidence chart: LMF products investigated by research focus Across all unique articles and outbreak reports (n=537), the most investigated microbial hazards were the following (Figure A1.3): • Salmonella spp. (n=278) • B. cereus (n=148) • E. coli (n=109) The most frequently investigated microbial hazard for prevalence, intervention, and burden of illness information was Salmonella spp. (n=97, 90 and 97, respectively). Burden of illness Interventions Prevalence C er ea ls a nd g ra in s C on fe ct io ns a nd sn ac ks D ri ed fr ui ts a nd ve ge ta bl es D ri ed p ro te in pr od uc ts H on ey a nd pr es er ve s N ut s an d nu t pr od uc ts Se ed s fo r co ns um pt io n Sp ic es , d ri ed h er bs an d te a 3 13 23 72 15 55 44 15 29 13 14 39 28 1 29 20 51 24 8 4 18 31 21 77 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 64 FIGURE A1.3 Evidence chart: microbial hazards investigated by research focus Burden of illness data was mainly informed by global outbreaks that have occurred since the 1950s to the present. Table A1.1 below shows the overall proportion of burden of illness information captured in the review stratified by the microbial hazards of focus. Salmonella spp. was the most frequent microbial hazard implicated in outbreaks and had the potential to cause large, widespread outbreaks. B. cereus outbreaks were mainly related to smaller outbreaks from rice and other cereal products. S. aureus caused some very large outbreaks due to contaminated powdered milk, thus overall, a disproportionate number of cases is attributed to S. aureus. Figure A1.4 below shows the number and relative size of outbreaks in each category by implicated microbial hazard. There were no illnesses due to L. monocytogenes or Cronobacter spp. captured in this scoping review. B . c er eu s C . b ot ul in um C . P er fr in g en s C ro n oc ac te r sp p. E . C ol i S al m on el la s pp s. L. m on oc yt og en es S ta p h. a ur eu s E nt er ob ac te ri ac ea e Burden of illness Interventions Prevalence 56 15 80 33 1 25 10 3 6 22 32 7 97 9033 9771 16 73 7 21 2539 ANNEX 1 65 TABLE A1.1 Summary of the burden of illness related to LMF outbreaks attributed to select microbial hazards % (count) Outbreaks Cases Hospitalizations Deaths Salmonella spp. 44.9% (96) 43.8% (12 415) 88.6% (895) 73.7% (14) E. coli 2.3% (5) 1.2% (354) 3.3% (33) 5.3% (1) B. cereus 25.7% (55) 3.7% (1057) 1.4% (14) 0% (0) C. botulinum 15.0% (32) 0.3% (84) 6.0% (61) 21.1% (4) C. perfringens 4.7% (10) 1.5% (432) 0% (0) 0% (0) S. aureus 7.5% (16) 49.4% (14 006) 0.7% (7) 0% (0) L. monocytogenes 0% (0) 0% (0) 0% (0) 0% (0) Cronobacter spp. 0% (0) 0% (0) 0% (0) 0% (0) Enterobacteriaceae 0% (0) 0% (0) 0% (0) 0% (0) FIGURE A1.4 The number of LMF outbreaks in each category, grouped by size of the outbreak (number of cases: 0–4, 5–49, 50–500, >500) and microbial hazard 0 -4 5- 4 9 5- -5 0 0 >5 0 0 45 40 35 30 25 20 15 10 5 0 0 -4 5- 4 9 5- -5 0 0 >5 0 0 0 -4 5- 4 9 5- -5 0 0 >5 0 0 0 -4 5- 4 9 5- -5 0 0 >5 0 0 0 -4 5- 4 9 5- -5 0 0 >5 0 0 0 -4 5- 4 9 5- -5 0 0 >5 0 0 0 -4 5- 4 9 5- -5 0 0 >5 0 0 0 -4 5- 4 9 5- -5 0 0 >5 0 0 Cereals and grains Confections and snacks Dried fruit and vegetables Dried protein products Outbreaks grouped by number of cases: 0,4, 5-49, 50-500, >500 Bacillus cereus C. botulinum C. perfringens E. coli S. aureus Salmonella Honey and preserves Nuts and nut products Seeds Spices, dried herbs and tea RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 66 Prevalence data captured in this review provides an understanding of the frequency and level of contamination detected in different LMF products. Most categories had survey information for a range of microbial hazards and products. While the data may not be globally representative and does not demonstrate any changes over time, it does provide a baseline for the likely frequency of contamination. Salmonella spp. was implicated in the greatest number of outbreaks and accounted for 44 percent of disease across LMF categories. Similarly, Salmonella contamination was relatively consistent across all LMF categories with an overall average prevalence of 1.6 percent (95 percent CI: 1.4–1.9), as shown in Table A1.2 below. Other microbial hazards (e.g. B. cereus) were detected at more variable levels in LMF. Intervention data captured in this review was mostly conducted under laboratory and non-commercial conditions, limiting its direct relevance and potential application to real-life conditions. Nevertheless, common themes from these studies across all LMF categories include the importance of preventing LMF contamination during harvest, post-harvest and processing through implementation of both good agricultural and manufacturing practices and hazard analysis critical control point (HACCP) food safety management systems. This is because many LMF products are eaten without a consumer-level kill step (e.g. cooking), and even under experimental and laboratory conditions, many of the investigated processing interventions could not achieve a reduction in pathogenic microorganisms to a level at which they did not constitute a significant health hazard at practical doses and durations. ANNEX 1 67 TABLE A1.2 Average prevalence of Salmonella spp. across all LMF product categories LMF category/ subcategory Average prevalence Low 95% CI High 95% CI Heterogeneity Median (range) Cereals and grains Milled grains 0.7 0.2 1.5 High 0 (0–46.2) Other cereals 0.0 0.0 0.0 Low - Rice products 0.0 0.0 0.0 Low - Whole grains 1.3 0.0 4.1 Low - Overall 0.7 0.3 1.4 High 0 (0–46.2) Confections and snacks Cocoa/chocolate 1.7 0.0 5.0 Med. - Other confections 0.0 0.0 0.0 Low - Snacks 0.0 0.0 0.0 Low - Overall 0.5 0.0 1.9 High 0 (0–4.6) Dried fruits and vegetables Overall 2.0 0.2 5.2 High 0 (0–33.3) Dried protein products Dried dairy 0.0 0.0 0.0 Low - Dried fish 5.6 0.0 38.5 High 10 (0–20) Dried meat 0.0 0.0 0.0 Low - Overall 0.0 0.0 0.1 Low 0 (0–20) Honey and preserves Overall 0.0 0.0 0.0 Low - Nuts and nut products Almonds 0.9 0.5 1.5 High 0.4 (0–2.7) Other tree nuts 0.8 0.3 1.6 High 0 (0–66.7) Peanuts 0.5 0.0 1.2 High 0 (0–2.3) Mixed nuts 0.2 0.0 0.5 Low - Overall 0.6 0.4 0.9 High 0 (0–66.7) Seeds for consumption Sesame 6.2 0.0 18.2 High 6.5 (0–12.5) Halve/helva 6.0 0.0 15.6 Med. - Other/unspecified 0.5 0.1 1.1 Med. - Overall 1.9 0.8 3.3 High 0.1 (0–16.7) Spices, dried herbs and tea Bark/flower 2.3 1.0 3.9 Low - Fruits/seed 4.3 3.6 5.0 Low - Herb 0.0 0.0 0.0 Low - Mixed/unspecified 2.6 1.9 3.4 High 0 (0–14) Root 4.4 2.5 6.7 Low - Overall 3.0 2.6 3.4 Low - Overall 1.6 1.4 1.9 High 0 (0–66.7) Note: The overall estimate for dried fruits and vegetables was based on data only from the dried fruits subcategory, and the overall estimate from honey and preserves was based on data only from the honey subcategory. LMF subcategories LMF category estimates Overall average Average prevalence (95% Cl) 0% 10% 20% 30% 40% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 68 A1.5 SUMMARY CARD: CEREALS AND GRAINS A1.5.1 Low-moisture food category description Cereals and grains refer to gramineous crops harvested for dry grains and their food products (FAO, 1994). This includes wheat, barley, maize/corn, oats, rye, millet, sorghum, buckwheat, and rice, as well as their milled products (e.g. flours and starches) and use in further processed foods (e.g. dry baking mixes, breakfast cereals, pasta and noodles) (FAO, 1994). For the purposes of summarizing prevalence information and conducting meta-analysis in this summary, cereals and grains were classified into the following categories: (1) dried whole grains other than rice; (2) raw rice and rice products (e.g. rice flour and rice noodles); (3) milled grains other than rice, including flours and starches; and (4) other dry cereals and cereal products, including breakfast cereals, cereal and baking mixes and unspecified/mixed cereals. For the interventions summary, the milled grain category was combined with the other dry cereals and cereal products due to limited data availability. A1.5.2 Evidence summary In total, 142 articles4 and outbreak reports5 were identified that investigated the burden of illness related to cereals and grains, the prevalence or concentration of selected microbial hazards in cereals and grains, and/or interventions to reduce contamination of microbial hazards in cereals and grains. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in Appendix F: Summary Card Evidence Charts. B. cereus was the most frequently investigated microbial hazard in cereals and grains for burden of illness (n=44 outbreak reports), prevalence (n=34 articles), and intervention (n=8 articles) information. A1.5.3 Burden of illness Burden of illness evidence related to cereal and grain products includes 72 outbreaks that affected 1 835 individuals, including 98 hospitalizations and 0 deaths between 1975 and 2013. B. cereus was the cause of 44/72 outbreaks (31 due to rice) > S. aureus (11) > Salmonella (10) > C. perfringens (5) > pathogenic 4 Articles refer to peer-reviewed journal publications as well as government and research agency reports. 5 For burden of illness information, multiple articles often reported complementary and/or overlapping information on the same outbreak. In addition, outbreak data were supplemented from other literature sources, including line lists from various countries, news reports, or annual summaries of country outbreaks. Thus, to avoid counting the same outbreak more than once, the term “outbreak report” is used instead of “article” to count the total number of unique outbreaks. ANNEX 1 69 E. coli (2). Outbreaks occurred in the United States of America (26), Australia (6), New Zealand (1), Japan (1), and Europe (34): France (8), Belgium (5), Germany (4), Netherlands (4), Denmark (4), Austria (2), Finland (2), the United Kingdom of Great Britain and Northern Ireland (2), Poland, Italy, Switzerland, Sweden and Norway. Where stated, the products in this category (but not necessarily the ingredients) originated from the same country as the outbreak. Almost 58.5 percent of illnesses captured in this category are attributed to cooked rice and pasta dishes (53 outbreaks), and with the exception of one large rice cake outbreak (15 percent of illnesses), most outbreaks were small and isolated to an event or a batch of food at a restaurant. Only five of these 53 outbreaks were captured in peer-reviewed publications; the remainder were from country line lists and reports with minimal information. Thirty-seven cooked rice outbreaks account for 28 percent of illnesses and were from several countries. Of these, 31 were caused by B. cereus which had a median (range) 7 (2–103) of illnesses per outbreak followed by three S. aureus outbreaks 7 (2–50), a C. perfringens outbreak (23 cases) and a Salmonella outbreak (2 cases). Similarly, 16 outbreaks (3–5 per microbial hazard) involving pasta accounted for 31 percent of illnesses and had a median (range) for B. cereus 15 (2–50), S. aureus 5 (10–32), C. perfringens 40 (16–250) and Salmonella 10 (2–26). Most of these outbreaks were attributed to food handler or consumer mishandling of the product, mainly temperature abuse or slow cooling. Due to a lack of information, it was not always clear that the rice or pasta was the confirmed contaminated ingredient. Considering the quantity of milled product that is consumed, there were very few reported outbreaks associated with flour at the time the analysis was conducted; of the three captured here, the median (range) of cases were 52 (35–67). This is likely because most of these products are cooked prior to consumption. Two out of three outbreaks associated with “flour” resulted in a product recall. There were some larger and/or more widespread outbreaks that involved ready-to-eat products such as infant cereal (2), breakfast cereal (2) and commercially prepared rice cakes (1), which had a median (range) of 33 (2–278) cases. Contamination of these products occurred during manufacturing, and there were recalls and implications for industry associated with these outbreaks. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 70 TA B LE A 1. 3 Su m m ar y of g lo ba lly re po rt ed o ut br ea ks re la te d to c er ea ls a nd g ra in s Ce re al o r G ra in P ro du ct (r ef er en ce ) M ic ro bi al h az ar d( s) O ut br ea ks / ca se sa / ho sp it al iz ed / de at hs Co un tr y (y ea r) b Co m m en ts : s us ce pt ib le p op ul at io ns /a tt ac k ra te / co nc en tr at io n of m ic ro bi al h az ar d in th e pr od uc t To as te d O at C er ea l (A no n. , 1 99 8) S al m on el la A go na 1/ 20 9/ 4 7/ 0 U ni te d St at es o f A m er ic a (1 99 8) 4 7% c as es w er e <1 0 y ea rs a nd 2 1% w er e >7 0 y ea rs . P uff ed R ic e C er ea l (R us so e t al ., 20 13 ) Sa lm on el la A go na 1/ 33 /1 2/ 0 U ni te d St at es o f A m er ic a (2 0 0 8) P ro du ct o ri gi n in t hi s ou tb re ak a nd t he t oa st ed o at s ou tb re ak is t he s am e m an uf ac tu ri ng p la nt . In fa nt C er ea l (R us hd y et a l., 19 98 ) B . c er eu s 1/ 2/ 0 /0 U ni te d K in gd om o f G re at B ri ta in a nd N or th er n Ir el an d (2 0 0 5) C on ce nt ra ti on in p ro du ct w as 10 3 sp or es /g (I nf an t th re sh ol d of e m et ic s yn dr om e is 10 5/ g. ) I nf an ts < 12 m on th s In fa nt C er ea l (D uc le e t al ., 20 0 5) S al m on el la Se nft en be rg 1/ 5/ 0 /0 TU ni te d K in gd om o f G re at B ri ta in a nd N or th er n Ir el an d (1 99 5) A ff ec te d in fa nt s <1 2 m on th s C er ea l p ro du ct s in cl ud in g ri ce a nd s ee ds /p ul se s (n ut s, al m on ds ) (E FS A , 2 0 13 ); (E FS A , 2 0 12 c) ; (E FS A , 2 0 12 e) B . c er eu s 5/ 4 6/ 12 /0 Fr an ce (2 0 11 )E , F ra nc e (2 0 12 )E , S w it ze rl an d (2 0 12 ) E C er ea l p ro du ct s, in cl ud in g ri ce a nd s ee ds /p ul se s (n ut s, al m on ds ), is a E ur op ea n U ni on re po rt in g ca te go ry . S pe ci fic pr od uc ts c ou ld n ot b e ve ri fie d. C er ea l p ro du ct s in cl ud in g ri ce a nd s ee ds /p ul se s (n ut s, al m on ds ) (E FS A , 2 0 0 9a ); (E FS A , 2 0 13 ) S . a ur eu s 2/ 11 /1 /0 Fr an ce (2 0 0 9, 2 0 11 ) B ul gu r (E FS A , 2 0 13 ) B . c er eu s 3/ 21 /0 /0 Fi nl an d (2 0 10 )E , D en m ar k (2 0 11 ) A tt ri bu te d to t em pe ra tu re a bu se a nd s lo w c oo lin g. B uc kw he at (E FS A , 2 0 0 9c ) B . c er eu s 1/ 52 /0 /0 P ol an d (2 0 0 9) Te m po ra ry m as s ga th er in g. Fl ou r (M cC al lu m e t al ., 20 13 ) S al m on el la Ty ph im ur iu m 4 2 1/ 67 /1 2/ 0 N ew Z ea la nd (2 0 0 8) D ue t o co ns um pt io n of a n un co ok ed b ak in g m ix tu re t ha t co nt ai n th e co nt am in at ed fl ou r. P ro du ct fr om im pl ic at ed ba tc h w as re ca lle d. Fl ou r (P ro M ed , 2 0 13 ) E . c ol i O 12 1 1/ 35 /7 /0 U ni te d St at es o f A m er ic a (2 0 13 )E Fl ou r ep id em io lo gi ca lly im pl ic at ed in t he fr oz en fo od re ca ll. U ns pe ci fie d G ra in s (C D C , 2 0 16 ) S al m on el la L ik a 1/ 3/ 0 /0 U ni te d St at es o f A m er ic a (2 0 0 3) R ic e C ak e (N ab ae e t al ., 20 13 ) E . c ol i ( ST E C ) 1/ 14 2C , 1 36 P / 0 /0 Ja pa n (2 0 11 ) C om m er ci al p ro du ct , c on ta m in at ed d ur in g m an uf ac tu ri ng . (c on t. ) ANNEX 1 71 Ce re al o r G ra in P ro du ct (r ef er en ce ) M ic ro bi al h az ar d( s) O ut br ea ks / ca se sa / ho sp it al iz ed / de at hs Co un tr y (y ea r) b Co m m en ts : s us ce pt ib le p op ul at io ns /a tt ac k ra te / co nc en tr at io n of m ic ro bi al h az ar d in th e pr od uc t C oo ke d R ic e R ef c B . c er eu s 31 /3 82 C ,4 4 P / 2/ 0 (C ou nt ry y ea r) c 16 /2 9 ar e la bo ra to ry c on fir m ed o ut br ea ks . 3 o ut br ea ks in vo lv ed c hi ld re n < 6 ye ar s at a d ay c ar e/ sc ho ol . M os t ou tb re ak s w er e is ol at ed t o a ho m e, c at er ed e ve nt o r a si ng le b at ch a t a re st au ra nt . T em pe ra tu re a bu se w as th e m os t ci te d ca us e. T he 19 75 o ut br ea k ha d co ok ed ri ce c on ce nt ra ti on s of 1. 7 x 10 8 o rg an is m s/ g an d ra w r ic e co nc en tr at io n: 10 0 o rg an is m s/ g. C oo ke d R ic e (K er ou an to n et a l., 2 0 0 7) ; (O zf oo dn et , 2 0 0 2) ; ( E FS A , 20 13 ) S . a ur eu s 3/ 52 C ,7 P / 0 /0 Fr an ce (2 0 0 1) , A us tr al ia (2 0 0 2) , P or tu ga l ( 20 11 ) Th e Fr en ch o ut br ea k S. a ur eu s co nc en tr at io n w as 2 .9 ×1 0 4 C FU /g . C oo ke d R ic e (O zf oo dn et , 2 0 0 6) C . p er fr in g en s 1/ 23 P / 0 /0 A us tr al ia (2 0 0 5) E C oo ke d R ic e (O zf oo dn et , 2 0 11 ) S al m on el la Ty ph im ur iu m 4 2. 1/ 2/ 2/ 0 A us tr al ia (2 0 10 )E D ay c ar e ce nt re o ut br ea k C oo ke d P as ta (E FS A , 2 0 0 4 ); (E FS A , 2 0 12 b) ; (C D C , 2 0 16 ) B . c er eu s 3/ 17 C , 5 0 P / 0 /0 B el gi um (2 0 0 4 )E , t he U ni te d St at es (2 0 0 9) , G er m an y (2 0 12 ) Th e G er m an o ut br ea k ha d B . c er eu s co nc en tr at io n of > 3 x 10 7 C FU /g . C oo ke d P as ta (A no n. , 2 0 0 4 ); (C D C , 2 0 16 ) C . p er fr in g en s 4 /3 30 C ,1 6P /0 /0 A us tr al ia (2 0 0 4 E , U ni te d St at es o f A m er ic a (2 0 0 4 , 20 0 9, 2 0 10 ) C oo ke d P as ta (E FS A , 2 0 0 5c ); (C D C , 2 0 16 ) S al m on el la E nt er it id is P T2 1, P T4 , A na tu m 4 /4 4 C , 4 P / 2/ 0 A us tr ia (2 0 0 5E , U ni te d St at es o f A m er ic a (1 99 6E , 2 0 0 4 ) C oo ke d P as ta (E FS A , 2 0 0 9d ); (K er ou an to n et a l., 2 0 0 7) ; ( C D C , 2 0 16 ) S . a ur eu s 5/ 98 /1 /0 Fr an ce (1 98 8) , U ni te d St at es o f A m er ic a (1 99 5E , 19 99 , 2 0 0 8) , B el gi um (2 0 0 9) R ic e N oo dl es (O zf oo dn et , 2 0 10 ) S . a ur eu s 1/ 3/ 0 /0 A us tr al ia (2 0 10 ) S. a ur eu s co nc en tr at io n > 2. 5 x 10 7 o rg an is m s/ g. a S up er sc ri pt C in di ca te s co nfi rm ed c as es , p in di ca te s pr es um pt iv e ca se s. b S up er sc ri pt E in di ca te s th e lin k be tw ee n hu m an c as es a nd im pl ic at ed p ro du ct w as e pi de m io lo gi ca l o nl y, o th er w is e th e lin k w as la bo ra to ry c on fir m ed . c R ef er en ce (C ou nt ry , Y ea r) : R ae vu or i, 19 76 (F in la nd 19 75 ); O zf oo dn et , 2 0 0 2 (A us tr al ia , 2 0 0 2) ; E FS A 2 0 0 5a /E FS A 2 0 10 a/ E FS A , 2 0 12 a (B el gi um 2 0 0 5E , 2 0 10 E , 2 0 12 ); E FS A , 2 0 13 (D en m ar k, 2 0 11 E ); E FS A n 20 13 /E FS A 2 0 12 b (G er m an y 20 11 E , 20 12 ); M ar ti ne lli e t al ., 20 13 (I ta ly , 2 0 12 ); E FS A , 2 0 0 9b (N et he rl an ds , 2 0 0 9E ); E FS A , 2 0 0 5b (N or w ay , 2 0 0 5E ); E FS A , 2 0 12 d (D en m ar k, 2 0 12 E ); T ay , G oh a nd T an , 1 98 2 (S in ga po re , 1 98 1E ); E FS A , 2 0 13 (S w ed en , 2 0 11 E ); K ho dr e t al ., 19 94 /C D C , 20 16 / P ro M ed , 2 0 11 (t he U ni te d St at es o f A m er ic a 19 93 , 1 99 5E , 1 99 9E , 2 0 0 0 E , 2 0 0 9E , 2 0 10 E , 2 0 11 E ). RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 72 A1.5.4 Prevalence A total of 55 studies containing 203 unique trials were identified that investigated the prevalence and/or concentration of one or more selected microbial hazards in cereals and grains. The median publication year was 2009 (range 1992–2014). Seventy-five percent of studies were conducted in Asia, the Middle East (n=24) and Europe (n=17). Most studies (87 percent) sampled products during a specific or defined period, while two conducted sampling over multiple time points, and five reported on the results of systematic surveillance programmes. Over 80 percent of studies sampled products at retail (e.g. markets and grocery stores) and/or from mills. Only 15/55 (27 percent) studies specified the country(s) of product origin. B. cereus was the most investigated microbial hazard across all cereal and grain categories. It was found at highly variable prevalence levels, in some cases detected in all sampled products. Some studies found that a high proportion of B. cereus isolates from positive cereal and grain samples contained enterotoxin-producing genes (Lee et al., 2012; Samapundo et al., 2011). Salmonella spp. were investigated extensively in flours, starches and other milled grains, with most observations coming from two large surveillance studies in the United States of America (Richter et al., 1993; Sperber, 2007). Most trials (77 percent) did not detect Salmonella spp. in any samples, and only one study found a high prevalence (46 percent) in a small and non-representative sample (n=13) in Colombia (Acosta et al., 2013). Generic E. coli was detected at a variable and sometimes very high prevalence in cereals and grains, with a median prevalence of 12.4 percent in milled grains and 8.9 percent in other dry cereals and cereal products. Berghofer et al. (2003) found that incoming whole grains at mills in Australia had a lower prevalence of generic E. coli than milled end-products, suggesting that cross-contamination likely occurred during the milling process. E. coli O157:H7 was identified in only one study, in four out of fifteen samples of sorghum flour from South Africa (Kunene, Hastings and Von Holy, 1999). ANNEX 1 73 C. botulinum, C. perfringens, L. monocytogenes and S. aureus were investigated in only a few studies and were found at low to moderate prevalence levels. A very high prevalence of Enterobacteriaceae was identified in rice samples from Republic of Korea in one study (Jung and Park, 2006). Few studies reported extractable concentration data on levels of selected microbial hazards in cereals and grains (not shown in the table below). In flours, starches and other milled grains, average concentrations of B. cereus ranged from 1.3 to 3.0 x 104 CFU/g and 0.3 to 30 MPN/g, and average concentrations of generic E. coli ranged from 1.9 to 23.5 MPN/g and 0.8 to 5.1 x 104 CFU/g (Aydin, Paulsen and Smulders, 2009; Berghofer et al., 2003; Chitov, Dispan and Kasinrerk, 2008; Eglezos, 2010; Fangio, Roura and Fritz, 2010; Sengun and Karapinar, 2012; Victor et al., 2013). In rice, four studies reported concentrations of B. cereus ranging from 36 to 7 700 CFU/g and 16 to 210 MPN/g (Ankolekar, Rahmati and Labbe, 2009; Chitov, Dispan and Kasinrerk, 2008; Fangio, Roura and Fritz, 2010; Sandra et al., 2012). Average concentrations of B. cereus in other dry cereals and cereal products ranged from 3 to 960 CFU/g and 3 to 200 MPN/g (Chitov, Dispan and Kasinrerk, 2008; Fang, Chu and Shih, 1997; Kim et al., 2009; Lee et al., 2007, 2009, 2012; Rahimi et al., 2013). In samples of a powdered cereal blend in the Republic of Korea, an average concentration of 15 CFU/g was identified for C. perfringens, and a concentration range of 0.7 to 2.24 X 103 MPN/100g was identified for Cronobacter spp. (Lee et al., 2007). In wheat flour samples from Türkiye, an average concentration of 1.3 to 1.6 CFU/g was identified for C. perfringens, with all samples below reported acceptable limit levels (104 CFU/g) for this pathogen (Aydin, Paulsen and Smulders, 2009). RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 74 TABLE A1.4 Prevalence of selected microbial hazards within cereal and grain categories (Each cell includes the number of observations/trials/studies contributing to the average or median prevalence estimate and the proportion of trials that did not find any positive samples and measures of heterogeneity and risk of selection bias. See the table footnotes for detailed explanations on each of these parameters.) Cereals and grains Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Whole grains Flours, starches, and other milled grains Rice and rice products Other dry cereals and cereal products B. cereus 327/11/6 (27%) 26.8 (0–100)R High/High 1037/28/14 (54%) 0 (0–100)R High/High 546/10/9 (38%) 57.3 (17–100)R High/High 908/19/13 (21%) 41.7 (0–100)R High/High C. botulinum N/A 25/1/1 (0%) 16 N/A/High N/A N/A C. perfringens N/A 227/5/5 (80%) 0 (0–9.9)R High/High 8/2/1 (100%) 0 (0–0)R Low/High 44/2/2 (0%) 7.3 (1.2–17.2)M Low/High Cronobacter spp. N/A 22/5/2 (60%) 11.3 (1.2–27.7)M Low/High 43/3/3 (33%) 0 (0–37.5)R High/High 894/12/11 (58%) 0 (0–45)R High/High Generic E. coli 108/2/2 (50%) 1.3 (0–4.1)M Low/Low 4146/12/9 (17%) 12.4 (0–100)R High/Med. N/A 266/5/5 (20%) 8.9 (0–68.2)R High/High E. coli O157:H7 N/A 25/4/2 (25%) 15.9 (4–32.7)M Low/High 8/2/1 (100%) 0 (0–0)R Low/High 100/1/1 (100%) 0 N/A/High Enterobacteriaceae N/A N/A 47/2/1 (0%) 91.7 (83–100)R High/High N/A L. monocytogenes N/A 102/3/3 (33%) 13.3 (0–18.5)R High/High N/A 308/2/2 (50%) 0.7 (0.01–2)M Low/Med. S. aureus N/A 129/4/4 (50%) 3.3 (0–11.5)R High/High 2/1/1 (100%) 0 N/A/High 369/3/3 (33%) 6.3 (0–6.7)R High/Med. Salmonella spp. 108/2/2 (50%) 1.3 (0–4.1)M Low/Low 11040/22/12 (77%) 0 (0–46.2)R High/Med. 8/2/1 (100%) 0 (0–0)R Low/High 287/3/3 (100%) 0 (0–0)R Low/Med. (cont.) ANNEX 1 75 N/A = No data identified for this product-hazard combination. Med. = medium. a Observations/trials/studies: The observations are the total number of samples for all studies included in the summarized category. The number of studies is the number of articles captured. In some cases, articles report data on multiple prevalence trials or sampling frames. While the observations for each trial are independent by time and sample, they are part of a larger study where the methods and investigators are the same. Thus, there is not full independence in these observations, and we note this by acknowledging there are multiple trials within a study. b Superscript M indicates an average prevalence estimate (and 95 percent confidence interval) from a random-effects meta-analysis. Meta-analysis estimates were calculated only if heterogeneity was low or medium (I2 0–60 percent) and if at least one trial found a positive sample. Superscript R indicates a median (and range) of trial prevalence estimates, calculated if heterogeneity was high (I2 >60 percent). Ranges not provided when only one trial was identified. c I2 is a measure of the degree of heterogeneity between trials combined in the meta-analysis. Heterogeneity rating definitions: low = I2 0–30 percent; medium = 31–60 percent; high = >60 percent. Selection bias rating definitions: high = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. Studies that conducted random or systematic sampling were considered representative. The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. Taking into consideration the number of studies in the meta-analysis, high confidence in the meta-analysis results can be inferred when heterogeneity is low, and the risk of selection bias is low, and low confidence can be inferred when both are high; see the methods section for more information. A1.5.5 Interventions A total of 15 experimental studies (consisting of 104 unique trials) were identified evaluating the effects of various interventions to reduce contamination of microbial hazards in cereals and grains. The median publication year was 2003 (range 1973–2013). Most studies (>70 percent) were conducted in the United States of America (n=6), Asia and the Middle East (n=5, four of which were in the Republic of Korea). Twelve of the 15 studies were challenge trials with artificially inoculated samples; one was a lab-based controlled trial; one included challenge and controlled trials, and one was a field-based controlled trial. Most trials were conducted under laboratory and non-commercial conditions, and most (84 percent) contained only three samples per intervention combination investigated. The most common interventions were dry heat treatments, chemical treatments (various acid solutions), irradiation (including ionizing radiation and microwave radiation), and various combinations of these and other treatments. All interventions in rice and other grains were applied against B. cereus, with the exception of one controlled trial that evaluated the effect of irradiation on generic E. coli concentrations (Sarrías, Valero and Salmerón, 2003). In dry cereal mixes and flours, dry heat and microwave irradiation treatments were investigated against Salmonella spp. in several trials; modified storage conditions were investigated against the survival of B. cereus, Cronobacter spp., and E. coli O157:H7 (each in one RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 76 TABLE A1.5 Forest plot of the prevalence of selected microbial hazards within cereal and grain categories Microbial hazard/ LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs./ trials/ studies Heterogeneity Selection bias Median (range) B. cereus Whole grains 42.6 16.1 71.2 327/11/6 High High 26.8 (0–100) Milled grains 26.7 7.4 51.4 1 037/28/14 High High 0 (0–100) Rice/rice products 67.0 40.6 89.2 546/10/9 High High 57.3 (17–100) Other cereals 35.8 20.8 52.3 908/19/13 High High 41.7 (0–100) Overall 38.5 27.3 50.5 High 32.8 (0–100) C. perfringens Milled grains 3.5 0.0 10.4 227/5/5 High High 0 (0–9.9) Rice/rice products 0.0 0.0 0.0 8/2/1 Low High - Other cereals 7.3 1.2 17.2 44/2/2 Low High - Overall 4.5 1.2 9.6 Med. - Cronobacter spp. Milled grains 11.3 1.2 27.7 22/5/2 Low High - Rice/rice products 11.7 0.0 47.7 43/3/3 High High 0 (0–37.5) Other cereals 6.4 1.5 13.9 894/12/11 High High 0 (0–45) Overall 8.0 3.2 14.5 High 0 (0–45) Generic E. coli Whole grains 1.3 0.0 4.1 108/2/2 Low Low - Milled grains 20.2 5.6 40.0 4 146/12/9 High Med. 12.4 (0–100) Other cereals 13.8 0.0 36.4 266/5/5 High High 8.9 (0–68.2) Overall 15.5 6.0 28.1 High 8.9 (0–100) E. coli O157 Milled grains 15.9 4.0 32.7 25/4/2 Low High - Rice/rice products 0.0 0.0 0.0 8/2/1 Low High - Other cereals 0.0 0.0 0.0 100/1/1 N/A High - Overall 6.4 0.0 18.3 High 0 (0–26.7) L. monocytogenes Milled grains 8.7 0.0 28.5 102/3/3 High High 13.3 (0–18.5) Other cereals 0.7 0.0 2.0 308/2/2 Low Med. - Overall 2.2 0.0 6.8 High 0.5 (0–18.5) S. aureus Milled grains 5.7 0.0 16.2 129/4/4 High High 3.3 (0–11.5) Rice/rice products 0.0 0.0 0.0 2/1/1 N/A High - Other cereals 3.7 0.0 10.2 369/3/3 High Med. 6.3 (0–6.7) Overall 4.0 0.9 9.0 High 3.1 (0–11.5) Salmonella spp. Whole grains 1.3 0.0 4.1 108/2/2 Low Low - Milled grains 0.7 0.2 1.5 11 040/22/12 High Med. 0 (0–46.2) Rice/rice products 0.0 0.0 0.0 8/2/1 Low High - Other cereals 0.0 0.0 0.0 287/3/3 Low Med. - Overall 0.7 0.3 1.4 High 0 (0–46.2) CI = confidence interval; Med = medium; No. obs. =number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: C. botulinum evidence not shown in this figure because only one trial/study was identified. LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% ANNEX 1 77 to two studies), and fermentation with lactic acid bacteria was investigated against generic E. coli in one trial. Nearly all trials found that the applied interventions were effective at achieving statistically significant reductions in concentration levels of the investigated microbial hazards. However, for some interventions, the doses and/or duration of treatments required to achieve suitable log reductions in microbial concentration might negatively affect product quality or consumer acceptability (Mtenga et al., 2013; Park et al., 2009). Almost all milled cereals (e.g. flours) are baked, fried or cooked prior to consumption (Sperber, 2007), reducing the risk of illness from microbial hazards such as Salmonella; but certain cereal products are ready-to-eat (e.g. breakfast cereals) and are usually consumed without further processing (Neil et al., 2012). In the case of B. cereus, typical cooking of frequently contaminated cereals and grains, such as rice and pasta, is not sufficient for complete destruction of spores, and mishandling during preparation (e.g. temperature abuse) may lead to foodborne illness in consumers (EFSA, 2005). Control of the selected microbial hazards in cereals and grains should focus on implementation of good agricultural and manufacturing practices and hazard analysis critical control point (HACCP) food safety management systems (EFSA, 2005; Sperber, 2007). Additional interventions and treatments could be considered for higher risk products, such as those that are typically eaten without an additional “kill step” (Sperber, 2007). 0% 20% 40% 60% 80% 100% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 78 TA B LE A 1. 6 Su m m ar y ta bl e of e xp er im en ta l s tu di es e va lu at in g th e eff ec ts o f i nt er ve nt io ns t o re du ce c on ta m in at io n of s el ec te d m ic ro bi al h az ar ds in ce re al s an d gr ai ns Fo od ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or du ra ti on , w he re a va ila bl e) So ur ce (s )a M ic ro bi al ha za rd (s ) St ud y ty pe b N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc D ry c er ea l m ix es a nd flo ur s Fe rm en ta ti on La ct ic a ci d ba ct er ia (7 2 hr ) (K im m on s et a l., 19 99 )a G en er ic E . c ol i C .T . 1/ 1 0 10 0 H ea t tr ea tm en t D ry h ea t (5 7– 75 °C ; 1 0 –1 50 m in ) D ry h ea t (4 3– 60 °C ; 1 –1 3 da ys ) D ry h ea t (4 9° C ; 0 .5 –2 4 h r) (A rc he r et a l., 19 98 ); (B oo kw al te r et a l., 19 80 ); (V an C au w en be rg e, B ot ha st a nd K w ol ek , 19 81 ) S al m on el la sp p. C h. T. 11 /3 0 10 0 * Ir ra di at io n M ic ro w av e (2 4 50 M H z; 5 6. 7– 82 .2 °C ; 3. 9- 10 m in ) (B oo kw al te r, S hu kl a an d K w ol ek , 1 98 2) a S al m on el la sp p. C h. T. 1/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (5 –4 5° C ), in cr ea se d a w (0 .2 7– 0 .7 8) , d ec re as ed p H (5 .6 –6 .7 ; 1 –3 6 w ee ks ) (J aq ue tt e an d B ea uc ha t, 19 98 ) B . c er eu s C h. T. 6/ 1 0 67 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (4 –3 0 °C ), in cr ea se d a w (0 .3 0 –0 .6 9; 1– 12 m on th s) (L in a nd B ea uc ha t, 20 0 7) C ro n ob ac te r sp p. C h. T. 6/ 1 17 83 St or ag e co nd it io ns P ro du ct s to ra ge in v ac uu m fl as ks (7 50 m l) (K im m on s et a l., 19 99 )a G en er ic E . co li C .T . 1/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (5 –4 5° C ), in cr ea se d a w (0 .3 5– 0 .7 3) , d ec re as ed p H (4 .0 –6 .8 ; 1 –2 4 w ee ks ) (D en g, R yu a nd B ea uc ha t, 19 98 ) E . c ol i O 15 7: H 7 C h. T. 3/ 1 0 67 R ic e C he m ic al s Fe rm en te d et ha no l ( 10 –7 0 % ; 5 –6 0 m in ) Su pe rc ri ti ca l c ar bo n di ox id e (3 6– 4 4 °C ; 10 0 –2 0 0 b ar ; 1 0 –3 0 m in ) Fe rm en te d et ha no l + s up er cr it ic al C O 2 So di um h yp oc hl or it e di p (1 0 0 pp m ; 25 –6 0 °C ; 3 –6 h r) C it ri c ac id d ip (1 % ; 2 5– 60 °C ; 3 –6 h r) (K im e t al ., 20 13 ) (K im e t al ., 20 13 ) (K im e t al ., 20 13 ) (P ar k et a l., 2 0 0 9) (P ar k et a l., 2 0 0 9) B . c er eu s C h. T. 15 /2 13 10 0 * (c on t. ) ANNEX 1 79 Fo od ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or du ra ti on , w he re a va ila bl e) So ur ce (s )a M ic ro bi al ha za rd (s ) St ud y ty pe b N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc E le ct ro ly ze d w at er A ci di c el ec tr ol yz ed w at er (3 –6 h r) A lk al in e el ec tr ol yz ed w at er (3 –6 h r) (P ar k et a l., 2 0 0 9) B . c er eu s C h. T. 12 /1 0 10 0 H ea t tr ea tm en t D ry h ea t (1 20 °C ; 1 –3 h rs ) (H ou šk a et a l., 2 0 0 7) B . c er eu s C h. T. 2/ 1 10 0 10 0 Ir ra di at io n E le ct ro n be am (1 .1 –7 .5 k G y) (S ar rí as , V al er o an d Sa lm er ón , 2 0 0 3) a B . c er eu s, G en er ic E . co li C h. T. 2/ 1 10 0 10 0 Ir ra di at io n G am m a (1 .5 –3 0 k G y; 10 k G y/ hr ) E le ct ro n be am (1 .1 –7 .5 k G y) (M te ng a et a l., 2 0 13 ) (S ar rí as V al er o an d Sa lm er ón , 2 0 0 3) a B . c er eu s C h. T. 4 /2 25 75 M ul ti pl e G am m a ir ra di at io n (0 .1 –0 .3 k G y) + so di um h yp oc hl or it e (1 0 –1 0 0 0 p pm ; 2 m in ) + u lt ra so un d (1 8 m in ) C it ri c ac id d ip + a ci di c an d al ka lin e el ec tr ol yz ed w at er (3 –6 h r) (H a, K im a nd H a, 2 0 12 ) (P ar k et a l., 2 0 0 9) B . c er eu s C h. T. 13 /2 7 10 0 * O zo ne G as (0 .1 –0 .4 p pm ; 1 –7 h r) (S ha h et a l., 2 0 11 ) B . c er eu s C .T . 1/ 1 0 10 0 O th er gr ai ns C he m ic al s So di um h yp oc hl or it e di p (1 0 0 pp m ; 25 –6 0 °C ; 3 –6 h r) C it ri c ac id d ip (1 % ; 2 5– 60 °C ; 3 –6 h r) (P ar k et a l., 2 0 0 9) B . c er eu s C h. T. 8/ 1 0 10 0 E le ct ro ly ze d w at er A ci di c el ec tr ol yz ed w at er (3 –6 h r) A lk al in e el ec tr ol yz ed w at er (3 –6 h r) (P ar k et a l., 2 0 0 9) B . c er eu s C h. T. 8/ 1 0 10 0 M ul ti pl e C it ri c ac id d ip + a ci di c an d al ka lin e el ec tr ol yz ed w at er (3 –6 h r) (P ar k et a l., 2 0 0 9) B . c er eu s C h. T. 8/ 1 0 10 0 a I nd ic at es t he se s tu di es w er e co nd uc te d un de r co m m er ci al c on di ti on s. b C h. T. = c ha lle ng e tr ia l; C .T . = c on tr ol le d tr ia l. c I nt er ve nt io n ca te go ri es m ar ke d w it h an a st er is k (* ) in di ca te t ha t m or e tr ia ls f ou nd a s ta ti st ic al ly s ig ni fic an t re du ct io n in m ic ro bi al c on ce nt ra ti on o r pr ev al en ce t ha n w ou ld b e ex pe ct ed b y ch an ce a lo ne ( si gn t es t P v al ue < 0 .0 5) . 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Detection of toxigenic Bacillus cereus and Bacillus thuringiensis spores in U.S. rice. International Journal of Food Microbiology, 128(3): 460–466. REF #: 1280. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 86 Aydin, A., Paulsen, P. & Smulders, J. M. 2009. The physico-chemical and microbiological properties of wheat flour in thrace. Turkish Journal of Agriculture and Forestry, 33: 445–454. Ref #: 6754. Batool, S. A., Rauf, N., Tahir, S. S. & Kalsoom, R. 2012. Microbial and physico-chemical contamination in the wheat flour of the twin cities of Pakistan. Internet Journal of Food Safety, 14: 75–82. Ref #: 6755. Berghofer, L. K., Hocking, A. D., Miskelly, D. & Jansson, E. 2003. Microbiology of wheat and flour milling in Australia. International Journal of Food Microbiology, 85(1–2): 137–149. Ref #: 2267. Biswas, S., Parvez, M. A. K., Shafiquzzaman, M., Nahar, S. & Rahman, M. N. 2010. 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Qualité microbiologique des farines de blé consommées au Maroc. Canadian Journal of Microbiology, 58(2): 145–150. Ref #: 6630. ANNEX 1 87 Fang, S. W., Chu, S. Y. & Shih, D. Y. C. 1997. Occurrence of Bacillus cereus in instant cereal products and their hygienic properties. Journal of Food & Drug Analysis, 5(2): 139–144. Ref #: 6640. Fang, T. J., Chen, C. & Kuo, W. 1999. Microbiological quality and incidence of Staphylococcus aureus and Bacillus cereus in vegetarian food products. Food Microbiology, 16(4): 385–391. Ref #: 6111. Fangio, M. F., Roura, S. I. & Fritz, R. 2010. Isolation and identification of Bacillus spp. and related genera from different starchy foods. Journal of Food Science, 75(4): M218–221. Ref #: 923. Gičová, A., Oriešková, M., Oslanecová, L., Drahovská, H. & Kaclíková, E. 2014. Identification and characterization of Cronobacter strains isolated from powdered infant foods. Letters in Applied Microbiology, 58(3): 242–247 [online]. 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Isolation of Enterobacter sakazakii and other Enterobacteriaceae from powdered infant formula milk and related products. Food Microbiology, 21(6): 771–777. Ref #: 6660. Jaradat, Z. W., Ababneh, Q. O., Saadoun, I. M., Samara, N. A. & Rashdan, A. M. 2009. Isolation of Cronobacter spp. (formerly Enterobacter sakazakii) from infant food, herbs and environmental samples and the subsequent identification and confirmation of the isolates using biochemical, chromogenic assays, PCR and 16S rRNA sequencing. BMC Microbiology, 9. Ref #: 1075. Jung, M. & Park, J. 2006. Prevalence and thermal stability of Enterobacter sakazakii from unprocessed ready-to-eat agricultural products and powdered infant formulas. Food Science and Biotechnology, 15(1): 152–157. Ref #: 6661. Kandhai, M. C., Heuvelink, A. E., Reij, M. W., Beumer, R. R., Dijk, R., van Tilburg, J. J. H. C. & Gorris, L. G. M. 2010. A study into the occurrence of Cronobacter spp. in the Netherlands between 2001 and 2005. Food Control, 21(8): 1127–1136. Ref #: 6664. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 88 Kim, S. K., Kim, K., Jang, S. S., Shin, E. M., Kim, M., Oh, S. & Ryu, S. 2009. Prevalence and toxigenic profiles of Bacillus cereus isolated from dried red peppers, rice, and sunsik in Korea. Journal of Food Protection, 72(3): 578–582. Ref #: 1214. Kim, S. A., Oh, S. W., Lee, Y. M., Imm, J. Y., Hwang, I. G., Kang, D. H. & Rhee, M. S. 2011. Microbial contamination of food products consumed by infants and babies in Korea. Letters in Applied Microbiology, 53(5): 532–538. Ref #: 619. Kunene, N. F., Hastings, J. W. & Von Holy, A. 1999. Bacterial populations associated with a sorghum-based fermented weaning cereal. International Journal of Food Microbiology, 49(1–2): 75–83. Ref #: 6110. Lee, E., Kim, S., Yoo, S., Oh, S., Hwang, I., Kwon, G. & Park, J. 2007. Microbial contamination by Bacillus cereus, Clostridium perfringens, and Enterobacter sakazakii in sunsik. Food Science and Biotechnology, 16(6): 948–953. Ref #: 5395. Lee, H., Chai, L., Tang, S., Jinap, S., Ghazali, F. M., Nakaguchi, Y. & Son, R. 2009. Application of MPN-PCR in biosafety of Bacillus cereus s.l. for ready-to-eat cereals. Food Control, 20(11): 1068–1071. Ref #: 5062. Lee, N., Sun, J. M., Kwon, K. Y., Kim, H. J., Koo, M. & Chun, H. S. 2012. Genetic diversity, antimicrobial resistance, and toxigenic profiles of Bacillus cereus strains isolated from sunsik. Journal of Food Protection, 75(2): 225–230. Ref #: 497. Lesley, M. B., Velnetti, L., Yousr, A. N., Kasing, A. & Samuel, L. 2013. Presence of Bacillus cereus s.l. from ready-to-eat cereals (RTE) products in Sarawak. International Food Research Journal, 20(2): 1031–1034. Ref #: 6672. Mena, C., Almeida, G., Carneiro, L., Teixeira, P., Hogg, T. & Gibbs, P. A. 2004. Incidence of Listeria monocytogenes in different food products commercialized in Portugal. Food Microbiology, 21(2): 213–216. Ref #: 6759. Molloy, C., Cagney, C., O’Brien, S., Iversen, C., Fanning, S. & Duffy, G. 2009. Surveillance and characterisation by pulsed-field gel electrophoresis of Cronobacter spp. in farming and domestic environments, food production animals and retail foods. International Journal of Food Microbiology, 136(2): 198–203. Ref #: 1113. Mozrova, V., Brenova, N., Mrazek, J., Lukesova, D. & Marounek, M. 2014. Surveillance and characterisation of cronobacter spp. in Czech retail food and environmental samples. Folia Microbiologica, 59(1): 63–68. Ref #: 95. Nunes, M. M., Mota, A. L. A. D. A. & Caldas, E. D. 2013. Investigation of food and water microbiological conditions and foodborne disease outbreaks in the federal district, Brazil. Food Control, 34(1): 235–240. Ref #: 4142. Park, Y. B., Kim, J. B., Shin, S. W., Kim, J. C., Cho, S. H., Lee, B. K. & Oh, D. H. 2009. Prevalence, genetic diversity, and antibiotic susceptibility of Bacillus cereus strains isolated from rice and cereals collected in Korea. Journal of Food Protection, 72(3): 612–617. Ref #: 1213.3. ANNEX 1 89 Rahimi, E., Abdos, F., Momtaz, H., Torki Baghbadorani, Z. & Jalali, M. 2013. Bacillus cereus in infant foods: Prevalence study and distribution of enterotoxigenic virulence factors in Isfahan province, Iran. The Scientific World Journal, 292571. Ref #: 4221. Richter, K. S., Dorneanu, E., Eskridge, K. M. & Rao, C. S. 1993. Microbiological quality of flours. Cereal Foods World, 38: 367–369. Ref #: 6743. Rosenkvist, H. & Hansen, Ã. 1995. Contamination profiles and characterisation of Bacillus species in wheat bread and raw materials for bread production. International Journal of Food Microbiology, 26(3): 353–363. Ref #: 6283. Rusul, G. 1995. Prevalence of Bacillus cereus in selected foods and detection of enterotoxin using TECRA-VIA and BCET-RPLA. International Journal of Food Microbiology, 25(2): 131–139. Ref #: 3029. Samapundo, S., Heyndrickx, M., Xhaferi, R. & Devlieghere, F. 2011. Incidence, diversity and toxin gene characteristics of Bacillus cereus group strains isolated from food products marketed in Belgium. International Journal of Food Microbiology, 150(1): 34–41. Ref #: 4666. Sandra, A., Afsah-Hejri, L., Tunung, R., Tuan Zainazor, T. T. C., Tang, J. Y. H., Ghazali, F. M. & Son, R. 2012. Bacillus cereus and Bacillus thuringiensis in ready- to-eat cooked rice in Malaysia. International Food Research Journal, 19(3): 829–836. Ref #: 4446. Sengun, I. Y. & Karapinar, M. 2012. Microbiological quality of tarhana, Turkish cereal based fermented food. Quality Assurance and Safety of Crops & Foods, 4(1): 17–25. Ref #: 6700. Shaker, R., Osaili, T., Al-Omary, W., Jaradat, Z. & Al-Zuby, M. 2007. Isolation of Enterobacter sakazakii and other Enterobacter sp. from food and food production environments. 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RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 90 Turcovsky, I., Kunikova, K., Drahovska, H. & Kaclikova, E. 2011. Biochemical and molecular characterization of Cronobacter spp. (formerly Enterobacter sakazakii) isolated from foods. Antonie Van Leeuwenhoek, 99(2): 257–269. Ref #: 899. Victor, N., Bekele, M. S., Ntseliseng, M., Makotoko, M., Peter, C. & Asita, A. O. 2013. Microbial and physicochemical characterization of maize and wheat flour from a milling company, Lesotho. Internet Journal of Food Safety, 15: 11–19. Ref #: 6760. Wang, X., Meng, J., Zhang, J., Zhou, T., Zhang, Y., Yang, B. & Xia, X. 2012. Characterization of Staphylococcus aureus isolated from powdered infant formula milk and infant rice cereal in China. International Journal of Food Microbiology, 153(1-2): 142–147. Ref #: 560. Yusuf, I. Z., Umoh, V. J. & Ahmad, A. A. 1992. 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RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 92 A1.6 SUMMARY CARD: CONFECTIONS AND SNACKS A1.6.1 Low-moisture food category description For the purposes of this summary, we refer to confections as sugar and sugar-based sweets such as fondants/creams, marshmallows, caramels/toffees, chewing gum, chocolate and other cocoa-based products (e.g. cocoa, chocolate powders and mixes). We refer to snacks as savoury and ready-to-eat low-moisture foods such as chips and dried biscuits/crackers. We also include yeast in this summary, which can be used as a flavouring or an additive to low-moisture foods. For the purposes of summarizing prevalence and intervention information, confections and snacks were classified into the following categories: (1) cocoa and chocolate products, (2) other and unspecified confections and sweets, (3) snacks, and (4) yeast extract. A1.6.2 Evidence summary In total, 87 articles6 and outbreak reports7 were identified that investigated the burden of illness, the prevalence or concentration of selected microbial hazards, and interventions to reduce contamination of microbial hazards in confections and snacks. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in Appendix F: Summary Card Evidence Charts. Salmonella spp. was the most frequently investigated microbial hazard in confections and snacks for burden of illness (n=41 outbreak reports), prevalence (n=11 articles) and intervention (n=12 articles) information. A1.6.3 Burden of illness Burden of illness evidence related to confections and snacks includes 44 outbreaks that affected 2 547 individuals, including 151 hospitalizations and 0 deaths between 1955 and 2012. The median (range) outbreak size was 14 (3–439) cases, and this varied by product type. For example, the size of chocolate outbreaks (n=9) caused by Salmonella was 119 (14–439) cases and accounted for 60.5 percent of all cases. Salmonella caused 93 percent of outbreaks and 99 percent of cases > E. coli O157:H7 (2.3 percent/0.4 percent), B. cereus (2.3 percent/0.2 percent), 6 Articles refer to peer-reviewed journal publications as well as government and research agency reports. 7 For burden of illness information, multiple articles often reported complementary and/or overlapping information on the same outbreak. In addition, outbreak data were supplemented from other literature sources, including line lists from various countries, news reports, or annual summaries of country outbreaks. Thus, to avoid counting the same outbreak more than once, the term “outbreak report” is used instead of “article” to count the total number of unique outbreaks. ANNEX 1 93 and S. aureus (2.3 percent/0.2 percent). Outbreaks occurred in Poland (23), the United States of America (9), the United Kingdom of Great Britain and Northern Ireland (6), Canada (4), Romania (2), Hungary, Sweden, Israel, Germany and Norway. There were several international outbreaks or outbreaks that implicated an imported product in this category; see the table below. Most of the products in this category are ready-to-eat with the exception of cocoa powder and cake mix, which would usually undergo a further cooking step prior to consumption. Except for the Mexican wheat snack and some or all the “sweet” outbreaks reported from Poland in 2011–2012, all outbreaks were attributed to commercially prepared products. A high proportion (82 percent) of non-Polish outbreaks captured in this section was published in peer-reviewed sources. b Superscript E indicates the link between human cases and implicated product was epidemiological only, otherwise the link was laboratory confirmed. A1.6.4 Prevalence A total of 29 studies containing 108 unique trials were identified that investigated the prevalence and/or concentration of one or more selected microbial hazards in confections and snacks. The median publication year was 2009 (range 1992–2014). Most studies (90 percent) were conducted in Europe (n=15) and Asia/the Middle East (n=11). Most studies (76 percent) sampled products during a specific or defined period, while two conducted sampling over multiple time points, and five reported on the results of systematic surveillance programmes. Nearly 80 percent of studies sampled products at retail (e.g. markets and grocery stores) and/or from manufacturing and processing facilities. Only eight out of twenty-nine studies (28 percent) specified the country(s) of product origin. Salmonella spp., L. monocytogenes, and E. coli were the most investigated microbial hazards in the cocoa and chocolate, other/unspecified confections and snack categories, respectively. A very low average prevalence of Salmonella spp. was identified in cocoa and chocolate (1.7 percent, 95 percent CI: 0.03 to 5.0), while it was not identified in other or unspecified confections and snacks. L. monocytogenes was identified at low prevalence levels in other or unspecified confections and was not found in studies sampling cocoa/chocolate and snacks. A very low prevalence of generic E. coli was found in all categories except cocoa and chocolate, where one study identified fourteen out of twenty-nine positive samples of dried and fermented cocoa beans in Brazil (Nascimento et al., 2010). B. cereus and Cronobacter spp. were found at highly variable prevalence levels RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 94 TA B LE A 1. 7 Su m m ar y of g lo ba lly re po rt ed o ut br ea ks re la te d to c on fe ct io ns a nd m is ce lla ne ou s sn ac ks Co nf ec ti on o r sn ac k (r ef er en ce ) M ic ro bi al h az ar d( s) O ut br ea ks / ca se sa / ho sp it al iz ed / de at hs Co un tr y (y ea r) b Co m m en ts : s us ce pt ib le p op ul at io ns /a tt ac k ra te / co nc en tr at io n of m ic ro bi al h az ar d in th e pr od uc t Co nf ec ti on s C ho co la te (W er be r et a l., 20 0 5) ; ( H ar ke r, 20 13 ); (C ra ve n et al .,1 97 5) ; G ill (1 98 3) ; (A no n. , 1 98 6) ; (K ap pe ru d et a l., 19 90 ); (E FS A , 2 0 0 9) ; (E FS A , 2 0 10 ) S al m on el la O ra ni en bu rg , N im a, M on te vi de o, E as tb ou rn e, N ap ol i, Ty ph im ur iu m , E nt er it id is 9/ 14 0 2c , 14 3P /6 3/ 0 G er m an y, o th er E U s ta te s an d C an ad a (2 0 0 1) , C an ad a (2 0 0 1) , C an ad a an d U ni te d St at es o f A m er ic a (1 97 3, 19 85 ), U ni te d K in gd om o f G re at B ri ta in a nd N or th er n Ir el an d (1 98 2, 2 0 0 6) , N or w ay (1 98 7) , H un ga ry (2 0 0 9) , R om an ia (2 0 10 ) G er m an c ho co la te c on ce nt ra ti on : 1 .1 –2 .8 /g C an ad ia n ch oc ol at e co nc en tr at io n: 2 .5 /g It al ia n ch oc ol at e co nc en tr at io n: 3 /g B el gi um c ho co la te c on ce nt ra ti on : 4 .3 –2 4 /1 0 0 g N or w eg ia n ch oc ol at e co nc en tr at io n: r an ge 0 –6 0 C FU / 10 0 g, 9 0 % s am pl es h ad < 10 C FU /1 0 0 g (E FS A , 2 0 10 ) S . a ur eu s 1/ 5/ 5/ 0 R om an ia (2 0 10 )E Sw ee ts a nd C ho co la te (E FS A , 2 0 11 ); (E FS A , 20 12 ) S al m on el la E nt er it id is 23 /2 32 /7 9/ 0 P ol an d (2 0 11 15 E , 2 0 12 3E ) “S w ee ts a nd C ho co la te ” is a E ur op ea n U ni on re po rt in g ca te go ry . S pe ci fic p ro du ct s co ul d no t be v er ifi ed . I f a ny o f th es e ar e re la te d, t he re h as b ee n no in ve st ig at io n to li nk th em . C ho co la te c ov er ed br az il nu ts (H ar ke r, 2 0 13 ) S al m on el la Sc hw ar ze ng ru nd 1/ 90 /0 /0 U ni te d K in gd om o f G re at B ri ta in a nd N or th er n Ir el an d (2 0 0 6) C oc oa P ow de r (G as tr in e t al ., 19 72 ) S al m on el la D ur ha m 1/ 11 0 /? /0 Sw ed en (1 97 0 ) Tr ac ed t o a co nt am in at ed c oc oa p ow de r sh ip m en t (o ri gi n un kn ow n) H ot C ho co la te M ix (N el m s, L ar so n an d B ar ne s- Jo si ah , 1 99 7) B . c er eu s 1/ 4 /0 /0 U ni te d St at es o f A m er ic a (1 99 4 ) C on ce nt ra ti on in h ot c ho co la te w as 17 0 0 0 0 /g . C ak e M ix (Z ha ng e t al ., 20 0 7) S al m on el la Ty ph im ur iu m 1/ 26 /0 /0 U ni te d St at es o f A m er ic a (2 0 0 9) C ak e m ix w as im pl ic at ed in t hi s ic e cr ea m o ut br ea k. (N o co ok in g st ep ) (c on t. ) ANNEX 1 95 Co nf ec ti on o r sn ac k (r ef er en ce ) M ic ro bi al h az ar d( s) O ut br ea ks / ca se sa / ho sp it al iz ed / de at hs Co un tr y (y ea r) b Co m m en ts : s us ce pt ib le p op ul at io ns /a tt ac k ra te / co nc en tr at io n of m ic ro bi al h az ar d in th e pr od uc t Co nf ec ti on s M ar sh m al lo w (L ew is e t al ., 19 96 ) S al m on el la E nt er it id is P T 4 1/ 36 /0 /0 U ni te d K in gd om o f G re at B ri ta in a nd N or th er n Ir el an d (1 99 5) C on ce nt ra ti on : 2 .7 x 10 4 /g o f m ar sh m al lo w H yp ot he si ze d to b e du e to u si ng s he lle d eg gs . I so la te d to on e ba ke ry . Ye as t (J os ep h et a l., 19 91 ); (K un z an d O uc ht er lo ny , 1 95 5) ; (M cC al l e t al ., 19 66 ) S al m on el la . O ra ni en bu rg , Se nft en be rg , M on te vi de o, M an ch es te r, Sc hw ar ze ng ru nd 3/ 19 1c , 13 0 P/ 5/ 0 U ni te d St at es o f A m er ic a (1 95 5, 19 64 ), U ni te d K in gd om of G re at B ri ta in a nd N or th er n Ir el an d (1 98 9) 19 89 o ut br ea k w as a s na ck fl av ou ri ng fr om w hi ch 6 6% o f th e ca se s w er e <5 y ea rs o ld . Th e 19 55 a nd 19 64 o ut br ea ks o cc ur re d in m ed ic al s et ti ng s an d w er e du e to c on ta m in at ed s up pl em en ta l f oo d. T he at ta ck r at e in t he se o ut br ea ks a cr os s se ve ra l i ns ti tu ti on s w as 2 3– 94 .4 % . Sn ac ks P ea nu t fla vo ur ed K os he r Sn ac k (K ill al ea e t al ., 19 96 ) S al m on el la A go na 1/ 16 0 /0 /0 U ni te d K in gd om o f G re at B ri ta in a nd N or th er n Ir el an d, Is ra el a nd U ni te d St at es o f A m er ic a (1 99 4 ) P ro du ct o f I sr ae l. M ai nl y co ns um ed b y ch ild re n 3– 5 ye ar s ol d. C on ce nt ra ti on in p ro du ct 2 –4 5 or ga ni sm s/ 25 g se rv in g. M ex ic an w he at s na ck (C D C , 2 0 16 ) E . c ol i O 15 7: H 7 1/ 11 /4 /0 U ni te d St at es o f A m er ic a (2 0 10 ) P re pa re d at h om e. To rt ill a ch ip s (C D C , 2 0 16 ) S al m on el la E nt er it id is 1/ 7/ 0 /0 U ni te d St at es o f A m er ic a (2 0 10 ) Se rv ed in a re st au ra nt a S up er sc ri pt C in di ca te s co nfi rm ed c as es ; p in di ca te s pr es um pt iv e ca se s. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 96 in confections and snacks. S. aureus was identified in only one small study (3/4) of Turkish delight samples (Akan and Sürücüoğlu, 2012). C. botulinum and Enterobacteriaceae were both investigated in one study each; a low to moderate prevalence of C. botulinum was found in sugar samples from Japan (Nakano et al., 1992), and Enterobacteriaceae was found in five out of twenty-five samples of cocoa powder in the Netherlands (Lima et al., 2011). C. perfringens and E. coli O157:H7 were not identified in any study. Only one study investigated yeast (not shown in the table below); the authors did not isolate B. cereus from four samples in Denmark (Rosenkvist and Hansen, 1995). Few studies reported extractable concentration data on levels of selected microbial hazards in confections and snacks (not shown in the table below). Average (standard deviation) log CFU/g concentrations of B. cereus in chocolate (n=100 samples), chewing gum (100), taffy (50), other candies (300), and mixed snacks (150) in the Republic of Korea were identified as 0.17 (0.58), 0.06 (0.41), 0.02 (0.60), 0.07 (0.42), and 0.32 (0.82), respectively (Kim et al., 2013). The concentration of most of the B. cereus positive samples in this study was much lower than those typically associated with foodborne illness from this pathogen (EFSA, 2005; Kim et al., 2013). Higher average (standard deviation) CFU/g concentrations of B. cereus, at 1.25 x 103 (1.97 x 103), were identified in a study that sampled corn snacks (n=20) in Egypt (Zeid, 2009). In other studies, a median concentration of 155 MPN/g was identified for 8/8 B. cereus positive samples in cereal bar snacks (Lee et al., 2009), a mean (standard deviation) of 33.7 (15.2) CFU/g was identified for S. aureus in 3/4 Turkish delight samples (Akan and Sürücüoğlu, 2012), and a concentration range of 0.9 to >3.0 log MPN/g was identified for generic E. coli in 14/29 dried and fermented cocoa bean ANNEX 1 97 samples (Nascimento et al., 2010). TABLE A1.8 Prevalence of selected microbial hazards within confection and snack categories (Each cell includes the number of observations/trials/studies contributing to the average or median prevalence estimate, the proportion of trials that did not find any positive samples, measures of heterogeneity and risk of selection bias. See the table footnotes for detailed explanations on each of these parameters.) Confections and snacks Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Cocoa and chocolate Other and unspecified confections Snacks B. cereus 106/2/2 (0%) 21.2 (9.0–33.3)R High/Med. 450/3/1 (0%) 3.1 (1.7–4.9)M Low/Low 192/5/5 (20%) 40 (0–70)R High/High C. botulinum N/A 103/5/1 (20%) 7.6 (1.1–18.1)M Med./High N/A C. perfringens 100/1/1 (100%) 0 N/A/Low 450/3/1 (100%) 0 (0–0)R Low/Low 150/1/1 (100%) 0 N/A/Low Cronobacter spp. 47/3/2 (67%) 0 (0–29.7)R High/Med. 123/5/4 (60%) 5.8 (0.7–14.3)M Med./High 33/3/3 (33%) 4.6 (0–100)R High/High Generic E. coli 129/2/2 (50%) 24.1 (0–48.3)R High/Med. 454/4/2 (75%) 0.7 (0.1–1.8)M Low/Low 377/3/3 (67%) 0 (0–4.4)R High/Low E. coli O157:H7 100/1/1 (100%) 0 N/A/Low 450/3/1 (100%) 0 (0–0)R Low/Low 202/4/3 (100%) 0 (0–0)R Low/High Enterobacteriaceae 25/1/1 (0%) 20 Low/High N/A N/A L. monocytogenes 102/2/2 (100%) 0 (0–0)R Low/Med. 1685/11/4 (55%) 0 (0–16.7)R High/Low 164/3/3 (100%) 0 (0–0)R Low/Med. S. aureus 100/1/1 (100%) 0 N/A/Low 454/4/2 (75%) 0 (0–75)R High/Low 160/2/2 (100%) 0 (0–0)R Low/Med. Salmonella spp. 254/5/4 (40%) 1.7 (0.03–5.0)M Med./High 450/3/1 (100%) 0 (0–0)R Low/Low 166/4/4 (100%) 0 (0–0)R Low/Med. N/A = No data identified for this product-hazard combination. Med. = medium. a Observations/trials/studies: The observations are the total number of samples for all studies included in the summarized category. The number of studies is the number of articles captured. In some cases, articles report data on multiple prevalence trials or sampling frames. While the observations for each trial are independent by time and sample, they are part of a larger study where the methods and investigators are the same. Thus, there is not full independence in these observations, and we note this by acknowledging there are multiple trials within a study. b Superscript M indicates an average prevalence estimate (and 95 percent confidence interval) from a random-effects meta-analysis. Meta-analysis estimates were calculated only if heterogeneity was low or medium (I2 0–60 percent) and if at least one trial found a positive sample. Superscript R indicates a median (and range) of trial prevalence estimates, calculated if heterogeneity was high (I2 >60 percent). Ranges not provided when only one trial was identified. c I2 is a measure of the degree of heterogeneity between trials combined in the meta-analysis. Heterogeneity rating definitions: low = I2 0–30 percent; medium = 31–60 percent; high = >60 percent. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 98 TABLE A1.9 Forest plot of the prevalence of selected microbial hazards within confection and snack categories Microbial hazard/LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs. /trials/ studies Heterogeneity Selection bias Median (range) B. cereus Cocoa and chocolate 16.6 0.0 43.1 106/2/2 High Med. 21.2 (9.0–33.3) Other confections 3.1 1.7 4.9 450/3/1 Low Low - Snacks 44.9 6.2 87.1 192/5/5 High High 40 (0–70) Overall 19.0 8.6 32.2 High 9 (0–100) C. botulinum Overall 7.6 1.1 18.1 103/5/1 Med. High - Cronobacter spp. Cocoa and chocolate 14.9 0.0 41.0 47/3/2 High Med. 0 (0–29.7) Other confections 5.8 0.7 14.3 123/5/4 Med. High - Snacks 11.2 0.0 38.7 33/3/3 High High 4.6 (0–100) Overall 8.5 2.6 17.1 High 0 (0–100) Generic E. coli Cocoa and chocolate 15.5 0.0 100.0 129/2/2 High Med. 24.1 (0–48.3) Other confections 0.7 0.1 1.8 454/4/2 Low Low - Snacks 2.0 0.0 7.8 377/3/3 High Low 0 (0–4.4) Overall 2.5 0.1 7.2 High 0 (0–42.3) L. monocytogenes Cocoa and chocolate 0.0 0.0 0.0 102/2/2 Low Med. - Other confections 1.0 0.2 2.2 1 685/11/4 High Low 0 (0–16.7) Snacks 0.0 0.0 0.0 164/3/3 Low Med. - Overall 0.8 0.3 1.7 Med. - S. aureus Cocoa and chocolate 0.0 0.0 0.0 100/1/1 N/A Low - Other confections 1.4 0.0 5.9 454/4/2 High Low 0 (0–75) Snacks 0.0 0.0 0.0 160/2/2 Low Med. - Overall 0.5 0.0 1.9 High 0 (0–75) Salmonella spp. Cocoa and chocolate 1.7 0.0 5.0 254/5/4 Med. High - Other confections 0.0 0.0 0.0 450/3/1 Low Low - Snacks 0.0 0.0 0.0 166/4/4 Low Med. - Overall 0.6 0.1 1.4 Low - CI = confidence interval; Med = medium; No. obs. =number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: C. perfringens and E. coli O157 evidence not shown in this figure because no positive samples were identified in these categories. C. botulinum evidence is based on data from only the other confections subcategory. LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% ANNEX 1 99 Selection bias rating definitions: high = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. Studies that conducted random or systematic sampling were considered representative. The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. Taking into consideration the number of studies in the meta-analysis, high confidence in the meta-analysis results can be inferred when heterogeneity is low and the risk of selection bias is low, and low confidence can be inferred when both are high; see the methods section for more information. A1.6.5 Interventions A total of 15 experimental studies (consisting of 41 unique trials) were identified evaluating the effects of various interventions to reduce contamination of microbial hazards in confections and snacks. The median publication year was 2000 (range 1968 to 2013). Studies were conducted in the United States of America (n=7), Brazil (2), Switzerland (2), Canada, Egypt, Spain and the United Kingdom of Great Britain and Northern Ireland. Thirteen of the 15 studies were challenge trials with artificially inoculated samples, and two were lab-based controlled trials. None of the studies were conducted under commercial conditions, and most included only a small number of samples (e.g. two to four replicates per intervention combination) or did not report their sample size. The most investigated interventions were various heat treatments to reduce contamination of Salmonella spp. in cocoa and chocolate. All investigated trials found that heat treatment is effective (statistically significant reduction in the concentration or prevalence of microbial hazards) against Salmonella spp. in these products (more than would be expected by chance alone). However, high doses and/or durations were often required for complete elimination of this pathogen (Lee, Kermasha and Baker, 1989; Nascimento et al., 2012). Two studies investigating the efficacy of conching (the last heat treatment step in chocolate making) found that it reduces Salmonella contamination but not necessarily to a level at which it does not constitute a significant health risk when initial levels of Salmonella are high (Krapf and Gantenbein-Demarchi, 2010; Nascimento et al., 2012). These findings emphasize the importance of ensuring that good agricultural and manufacturing practices and hazard analysis critical control point (HACCP) food safety management systems are implemented during cocoa harvesting and pre-processing (Krapf and Gantenbein-Demarchi, 2010; Nascimento et al., 2013). The National Confectioners Association Chocolate Council recommends that chocolate manufacturers design their roasting process to achieve a validated four to five log reduction of Salmonella spp. (NCACC, 2011). RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 100 A li m ite d nu m be r o f s tu di es in ve sti ga te d in te rv en tio ns ag ai ns t o th er p at ho ge ns an d in o th er co nf ec tio ns /s w ee ts, sn ac ks an d ye as t. TA B LE A 1. 10 S um m ar y ta bl e of e xp er im en ta l s tu di es e va lu at in g th e eff ec ts o f i nt er ve nt io ns t o re du ce c on ta m in at io n of s el ec te d m ic ro bi al h az ar ds in co nf ec ti on s an d sn ac ks Fo od c at eg or y In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) So ur ce (s ) M ic ro bi al h az ar d( s) St ud y ty pe a N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nb C oc oa / ch oc ol at e D ry in g 25 –3 5° C ; 6 0 –8 0 % R H ; 6 –7 da ys (N as ci m en to , 2 0 13 ) S al m on el la s pp . C h. T. 1/ 1 10 0 0 Fe rm en ta ti on 25 –3 5° C ; 6 0 –8 0 % R H ; 7 d ay s (N as ci m en to , 2 0 13 ) S al m on el la s pp . C h. T. 1/ 1 0 0 H ea t tr ea tm en t D ry h ea t (5 7– 90 °C ; 1 –1 0 50 m in ) D ry h ea t (5 4 –1 0 0 °C ; 1 –6 0 0 m in ) D ry h ea t (7 1° C ; 0 .5 –2 0 h r) D ry h ea t (7 1° C ; 2 –2 4 h r) C on ch in g (5 0 -9 0 °C ; 0 .5 –2 3 hr ) H ot o il di p (1 0 0 °C ; 1 5 m in ) R oa st in g (1 10 –1 4 0 °C ; 1 0 -5 0 m in ) C on ch in g (5 0 –7 0 °C ; 18 0 –1 4 4 0 m in ) (G oe pf er t an d B ig gi e, 19 68 ); (B ar ri le , 1 97 0 a) ; (B ar ri le , 1 97 0 b) ; ( Le e, K er m as ha a nd B ak er , 1 98 9) ; (K ra pf a nd G an te nb ei n- D em ar ch i, 20 10 ); (I zu ri et a an d K om it op ou lo u, 2 0 12 ); (N as ci m en to , 2 0 12 ); (N as ci m en to , 2 0 12 ) S al m on el la s pp . C h. T. 20 /7 50 10 0 * Ir ra di at io n G am m a (5 –1 0 k G y) (B on ve hí a nd Is al , 2 0 0 0 ) E nt er ob ac te ri ac ea e C .T . 1/ 1 10 0 10 0 Ir ra di at io n U lt ra vi ol et (1 9 x 10 3 e rg cm 2 / s; 0 .5 –1 0 m in ) (L ee , K er m as ha a nd B ak er , 19 89 ) S al m on el la s pp . C h. T. 1/ 1 0 10 0 (c on t. ) ANNEX 1 101 Fo od c at eg or y In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) So ur ce (s ) M ic ro bi al h az ar d( s) St ud y ty pe a N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nb St or ag e co nd it io ns In cr ea se d te m pe ra tu re (1 0 –3 8° C ; 1 -3 66 d ay s) (B ay lis e t al ., 20 0 4 ) P at ho ge ni c E . c ol i st ra in s C h. T. 1/ 1 10 0 10 0 St or ag e co nd it io ns In cr ea se d a w (0 .4 3– 0 .7 5; 2 da ys t o 14 w ee ks ) (J uv en , C ox a nd B ai le y, 19 84 ) S al m on el la s pp . C h. T. 2/ 1 0 10 0 U lt ra so un d 16 0 k H z; 4 2° C ; 1 0 –3 0 m in (L ee , K er m as ha a nd B ak er , 19 89 ) S al m on el la s pp . C h. T. 1/ 1 0 10 0 O th er co nf ec ti on s H ea t tr ea tm en t H ot w at er d ip (6 5– 70 °C ; 2 0 m in ) (N um m er , S hr es th a an d Sm it h, 2 0 12 ) S al m on el la s pp . C h. T. 1/ 1 0 10 0 M od ifi ed pa ck ag in g A ir (o xy ge n 0 .5 –2 0 % ) v s. va cu um (1 –2 7 w ee ks ) (C hr is ti an a nd S te w ar t, 19 73 ) S al m on el la s pp ., S . au re us C h. T. 4 /1 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (1 0 –3 8° C ; 4 h r to 3 67 d ay s) (B ay lis e t al ., 20 0 4 ) P at ho ge ni c E . c ol i st ra in s C h. T. 2/ 1 10 0 10 0 St or ag e co nd it io ns In cr ea se d a w (0 .1 1– 0 .5 3; 1– 27 w ee ks ) (C hr is ti an a nd S te w ar t, 19 73 ) S al m on el la s pp ., S . au re us C h. T. 4 /1 0 10 0 Sn ac ks Ir ra di at io n G am m a (1 –1 0 k G y; 5 .6 k G y/ hr ) (Z ei d, 2 0 0 9) B . c er eu s C .T . 1/ 1 10 0 10 0 Ye as t Sp ra y dr yi ng 22 5° C (M ill er , G oe pf er t an d A m un ds on , 1 97 2) S al m on el la s pp . C h. T. 1/ 1 0 10 0 a C h. T. = c ha lle ng e tr ia l; C .T . = c on tr ol le d tr ia l. b In te rv en ti on c at eg or ie s m ar ke d w it h an a st er is k (* ) in di ca te t ha t m or e tr ia ls f ou nd a s ta ti st ic al ly s ig ni fic an t re du ct io n in m ic ro bi al c on ce nt ra ti on o r pr ev al en ce t ha n w ou ld b e ex pe ct ed b y ch an ce a lo ne ( si gn t es t P v al ue <0 .0 5) . S ig ni fic an ce o nl y ca lc ul at ed if m or e th an o ne s tu dy w as c on du ct ed p er in te rv en ti on /m ic ro bi al h az ar d/ st ud y ty pe c om bi na ti on . RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 102 A1.6.6 References in A1.6 References used in summary narrative: Akan, L. S. & Sürücüoğlu, M. S. 2012. Production and characteristics of a traditional food: Turkish delight (lokoom). Journal of Food, Agriculture and Environment, 10(1): 71–73. EFSA. 2005. Opinion of the Scientific Panel on Biological Hazards on Bacillus cereus and other Bacillus spp in foodstuffs. EFSA Journal, 175: 1–48. Kim, M. J., Kim, S. A., Kang, Y. S., Hwang, I. G. & Rhee, M. S. 2013. Microbial diversity and prevalence of foodborne pathogens in cheap and junk foods consumed by primary schoolchildren. Letters in Applied Microbiology, 57(1): 47–53. Krapf, T. & Gantenbein-Demarchi, C. 2010. Thermal inactivation of Salmonella spp. during conching. Food Science and Technology, 43(4): 720–723. Lee, B. H., Kermasha, S. & Baker, B. E. 1989. Thermal, ultrasonic and ultraviolet inactivation of Salmonella in thin films of aqueous media and chocolate. Food Microbiology, 6(3): 143–152. Lee, H. -., Chai, L. -., Tang, S. -., Jinap, S., Ghazali, F. M., Nakaguchi, Y. & Son, R. 2009. Application of MPN-PCR in biosafety of Bacillus cereus s.l. for ready-to-eat cereals. Food Control, 20(11): 1068–1071. Lima, L. J., Kamphuis, H. J., Nout, M. J. & Zwietering, M. H. 2011. Microbiota of cocoa powder with particular reference to aerobic thermoresistant spore-formers. Food Microbiology, 28(3): 573–582. Nakano, H., Yoshikuni, Y., Hashimoto, H. & Sakaguchi, G. 1992. Detection of Clostridium botulinum in natural sweetening. International Journal of Food Microbiology, 16(2): 117–121. Nascimento, M. D. S. D., da Silva, N., da Silva, I. F., da Silva, J. d. C., Marques, E. R. & Barbosa Santos, A. R. 2010. Enteropathogens in cocoa pre-processing. Food Control, 21(4): 408–411. Nascimento, M. D. S. D., Brum, D. M., Pena, P. O., Berto, M. I. & Efraim, P. 2012. Inactivation of Salmonella during cocoa roasting and chocolate conching. International Journal of Food Microbiology, 159(3): 225–229. Nascimento, M. D. S. D., Pena, P. O., Brum, D. M., Imazaki, F. T., Tucci, M. L. S. & Efraim, P. 2013. Behavior of Salmonella during fermentation, drying and storage of cocoa beans. International Journal of Food Microbiology, 167(3): 363–368. National Confectioners Association Chocolate Council (NCACC). 2011. Raw chocolate: risks and recommendations. The Manufacturing Confectioner, 57–59. Rosenkvist, H. & Hansen, Ã. 1995. Contamination profiles and characterisation of Bacillus species in wheat bread and raw materials for bread production. International Journal of Food Microbiology, 26(3): 353–363. ANNEX 1 103 Citation list of burden of illness studies (n=19 unique citations): (Distiller ID = Ref #, Outbreak # =OB # where a Distiller ID is not available – for unpublished outbreaks) Anonymous. 1986. Salmonella Nima in British Columbia. CMAJ, 135(11): 1286. Ref #: 3552. CDC. 2016. CDC line list of foodborne outbreaks. In: Center for Disease Control and Prevention [online]. Atlanta, Georgia, USA. [Cited 20 July 2021]. https://www.cdc. gov/foodsafety/outbreaks/index.html OB#s:141, 145. Craven, P. C., Mackel, D. C., Baine, W. B., Barker, W. H. & Gangarosa, E. J. 1975. International outbreak of Salmonella Eastbourne infection traced to contaminated chocolate. Lancet, 1(7910): 788–792. Ref #: 3960. EFSA. 2009. Trends and Sources of Zoonoses and Zoonotic Agents in Humans, Foodstuffs, Animals and Feedingstuffs, Hungary 2009. Parma, Italy. (also available at https:// www.efsa.europa.eu/en/data-report/biological-hazards-reports). OB#s:o125. EFSA. 2010. Trends and Sources of Zoonoses and Zoonotic Agents in Humans, Foodstuffs, Animals and Feedingstuffs, Romania 2010. Parma, Italy. (also available at https:// www.efsa.europa.eu/en/data-report/biological-hazards-reports). OB#s:o150, s300. EFSA. 2011. Trends and Sources of Zoonoses and Zoonotic Agents in Humans, Foodstuffs, Animals and Feedingstuffs, Poland 2011. Parma, Italy. (also available at https://www. efsa.europa.eu/en/data-report/biological-hazards-reports). OB#s:o178–o194, s298–299. EFSA. 2012. Trends and Sources of Zoonoses and Zoonotic Agents in Humans, Foodstuffs, Animals and Feedingstuffs, Poland 2012. Parma, Italy. (also available at https://www. efsa.europa.eu/en/data-report/biological-hazards-reports). OB#s:o294–296. Gastrin, B., Kampe, A., Nystrom, K. G., Oden-Johanson, B., Wessel, G. & Zetterberg, B. 1972. Salmonella Durham epidemic caused by contaminated cocoa. Lakartidningen, 69(46): 5335–5338. Ref #: 4005. Gill, O. N., Sockett, P. N., Bartlett, C. L., Vaile, M. S., Rowe, B., Gilbert, R. J., Dulake, C., Murrell, H. C. & Salmaso, S. 1983. Outbreak of Salmonella Napoli infection caused by contaminated chocolate bars. Lancet, 1(8324): 574–577. Ref #: 3721. Harker, K. S., Lane, C., Gormley, F. J. & Adak, G. K. 2013. National outbreaks of Salmonella infection in the UK, 2000-2011. Epidemiology and Infection, 1–7. Ref #: 122. Joseph, C. A., Mitchell, E. M., Cowden, J. M., Bruce, J. C., Threlfall, E. J., Hine, C. E., Wallis, R. & Hall, M. L. 1991. A national outbreak of salmonellosis from yeast flavoured products. CDR (London England Review), 1(2): R16–9. Ref #: 3322. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 104 Kapperud, G., Gustavsen, S., Hellesnes, I., Hansen, A. H., Lassen, J., Hirn, J., Jahkola, M., Montenegro, M. A. & Helmuth, R. 1990. Outbreak of Salmonella Typhimurium infection traced to contaminated chocolate and caused by a strain lacking the 60-megadalton virulence plasmid. Journal of Clinical Microbiology, 28(12): 2597–2601. Ref #: 3337. Killalea, D., Ward, L. R., Roberts, D., de Louvois, J., Sufi, F., Stuart, J. M., Wall, P. G., Susman, M., Schwieger, M., Sanderson, P. J., Fisher, I. S., Mead, P. S., Gill, O. N., Bartlett, C. L. & Rowe, B. 1996. International epidemiological and microbiological study of outbreak of Salmonella Agona infection from a ready to eat savoury snack: England and Wales and the United States. British Medical Journal, 313(7065): 1105–1107. Ref #: 2916. Kunz L. & Ouchterlony. O. 1955. Salmonellosis Originating in a Hospital – A Newly Recognised Source of Infection. New England Journal of Medicine, 253: 761–763. Ref #: OB# s283. Lewis, D. A., Paramathasan, R., White, D. G., Neil, L. S., Tanner, A. C., Hill, S. D., Bruce, J. C., Stuart, J. M., Ridley, A. M. & Threlfall, E. J. 1996. Marshmallows cause an outbreak of infection with Salmonella Enteritidis phage type 4. Communicable Diseases Report, 6(13): R183–186. Ref #: 2910. McCall C. E., Collins R. N., Jones D B., Kaufmann A. F. & Brachman P. S. 1966. An Interstate Outbreak of Salmonellosis Traced to a Contaminated Food Supplement. American Journal of Epidemiology, 84(1): 32–39. Ref #: OB#: s284. Nelms, P. K., Larson, O. & Barnes-Josiah, D. 1997. Time to B. cereus about hot chocolate. Public Health Report, 112(3): 240–244. Ref #: 2878. Werber, D., Dreesman, J., Feil, F., van Treeck, U., Fell, G., Ethelberg, S., Hauri, A. M., Roggentin, P., Prager, R., Fisher, I. S., Behnke, S. C., Bartelt, E., Weise, E., Ellis, A., Siitonen, A., Andersson, Y., Tschape, H., Kramer, M. H. & Ammon, A. 2005. International outbreak of Salmonella Oranienburg due to German chocolate. BMC Infectious Diseases, 5: 7. Ref #: 2031. Zhang G., L. Ma, N. Patel, B. Swaminathan, S. Wedel & M. P. Doyle. 2007. Isolation of Salmonella Typhimurium from outbreak-associated cake mix. Journal of Food Protection, 70: 997–1001. Ref #: 6715. Citation list of prevalence studies (N=29): (Distiller ID = Ref #) Akan, L. S. & Sürücüoğlu, M. S. 2012. Production and characteristics of a traditional food: Turkish delight (lokoom). Journal of Food, Agriculture and Environment, 10(1): 71–73. Ref #: 4565. ANNEX 1 105 Alwakee, S. S. & Nasser, L. A. 2011. Microbial contamination and mycotoxins from nuts in Riyadh, Saudi Arabia. American Journal of Food Technology, 6(8): 613–630. Ref #: 4757. Baumgartner, A., Grand, M., Liniger, M. & Iversen, C. 2009. Detection and frequency of Cronobacter spp. (Enterobacter sakazakii) in different categories of ready-to-eat foods other than infant formula. International Journal of Food Microbiology, 136(2): 189–192. Ref #: 1191. EFSA & ECDC. 2010. The community summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in the European Union in 2008. EFSA Journal, 8: 1496. Ref #: 6637. EFSA & ECDC. 2012. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2010. EFSA Journal, 10(3): 2597. Ref #: 6757. Gelbíčová, T. & Karpíšková, R. 2009. Occurrence and characteristics of Listeria monocytogenes in ready-to-eat food from retail market in the Czech Republic. Czech Journal of Food Sciences, 27: S23–S27. Ref #: 5033. Hochel, I., Ruzickova, H., Krasny, L. & Demnerova, K. 2012. Occurrence of Cronobacter spp. in retail foods. Journal of Applied Microbiology, 112(6): 1257–1265. Ref #: 463. Kandhai, M. C., Heuvelink, A. E., Reij, M. W., Beumer, R. R., Dijk, R., van Tilburg, J. J. H. C. & Gorris, L. G. M. 2010. A study into the occurrence of Cronobacter spp. in the Netherlands between 2001 and 2005. Food Control, 21(8): 1127–1136. Ref #: 6664. Kim, S. A., Oh, S. W., Lee, Y. M., Imm, J. Y., Hwang, I. G., Kang, D. H. & Rhee, M. S. 2011. Microbial contamination of food products consumed by infants and babies in Korea. Letters in Applied Microbiology, 53(5): 532–538. Ref #: 619. Kim, M. J., Kim, S. A., Kang, Y. S., Hwang, I. G. & Rhee, M. S. 2013. Microbial diversity and prevalence of foodborne pathogens in cheap and junk foods consumed by primary schoolchildren. Letters in Applied Microbiology, 57(1): 47–53. Ref #: 168. Kiss, R., Papp, N. E., Vamos, G. & Rodler, M. 1996. Listeria monocytogenes isolation from food in Hungary. Acta Alimentaria, 25(1): 83–91. Ref #: 6265. Kolevska, I. S. & Kocic, B. 2009. Food contamination with Salmonella species in the Republic of Macedonia. Foodborne Pathogens and Disease, 6(5): 627–630. Ref #: 1155. Lee, H. -., Chai, L. -., Tang, S. -., Jinap, S., Ghazali, F. M., Nakaguchi, Y. & Son, R. 2009. Application of MPN-PCR in biosafety of Bacillus cereus s.l. for ready-to-eat cereals. Food Control, 20(11): 1068–1071. Ref #: 5062. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 106 Lima, L. J., Kamphuis, H. J., Nout, M. J., & Zwietering, M. H. 2011. Microbiota of cocoa powder with particular reference to aerobic thermoresistant spore-formers. Food Microbiology, 28(3): 573–582. Ref #: 749. Lima, L. J., van der Velpen, V., Wolkers-Rooijackers, J., Kamphuis, H. J., Zwietering, M. H. & Nout, M. J. 2012. Microbiota dynamics and diversity at different stages of industrial processing of cocoa beans into cocoa powder. Applied and Environmental Microbiology, 78(8): 2904–2913. Ref #: 489. Little, C. L., Jemmott, W., Surman-Lee, S., Hucklesby, L. & De Pinna, E. 2009. Assessment of the microbiological safety of edible roasted nut kernels on retail sale in England, with a focus on Salmonella. Journal of Food Protection, 72 (4): 853–855. Ref #: 1187. Mozrova, V., Brenova, N., Mrazek, J., Lukesova, D. & Marounek, M. 2014. Surveillance and characterisation of Cronobacter spp. in Czech retail food and environmental samples. Folia Microbiologica, 59(1): 63–68. Ref #: 95. Nakano, H., Yoshikuni, Y., Hashimoto, H. & Sakaguchi, G. 1992. Detection of Clostridium botulinum in natural sweetening. International Journal of Food Microbiology, 16(2): 117–121. Ref #: 3234. Nascimento, M. D. S. D., da Silva, N., da Silva, I. F., da Silva, J. d. C., Marques, E. R. & Barbosa Santos, A. R. 2010. Enteropathogens in cocoa pre-processing. Food Control, 21(4): 408–411. Ref #: 4955. Rani, U., Ayesha, M. F., Viswanath, P. & Sandhu, J. S. 2005. Studies on detection, enumeration and survival of E. coli “ready to eat” processed cereal food product. Asian Journal of Microbiology, Biotechnology and Environmental Sciences, 7(3): 395–400. Ref #: 5663. Rosenkvist, H. & Hansen, Ã. 1995. Contamination profiles and characterisation of Bacillus species in wheat bread and raw materials for bread production. International Journal of Food Microbiology, 26(3): 353–363. Ref #: 6283. Shaker, R., Osaili, T., Al-Omary, W., Jaradat, Z. & Al-Zuby, M. 2007. Isolation of Enterobacter sakazakii and other Enterobacter sp. from food and food production environments. Food Control, 18(10): 1241–1245. Ref #: 5421. Sheth, M., Patel, J., Sharma, S. & Seshadri, S. 2000. Hazard analysis and critical control points of weaning foods. Indian Journal of Pediatrics, 67(6): 405–410. Ref #: 2598. Te Giffel, M. C., Beumer, R. R., Leijendekkers, S. & Rombouts, F. M. 1996. Incidence of Bacillus cereus and Bacillus subtilis in foods in the Netherlands. Food Microbiology, 13(1): 53-58. Ref #: 6272. Torres-Vitela, M., Escartin, E. F. & Alejandro, C. 1995. Risk of salmonellosis associated with consumption of chocolate in Mexico. Journal of Food Protection, 58(5): 478– 481. Ref #: 6287. ANNEX 1 107 Turcovsky, I., Kunikova, K., Drahovska, H. & Kaclikova, E. 2011. Biochemical and molecular characterization of Cronobacter spp. (formerly Enterobacter sakazakii) isolated from foods. Antonie Van Leeuwenhoek, 99(2): 257–269. Ref #: 899. Vural, A. & Erkan, M. E. 2008. The research of microbiological quality in some edible nut kinds. Journal of Food Technology, 6(1): 25–28. Ref #: 6750. Zeid, A. A. M. A. 2009. Incidence of Bacillus cereus in corn snacks and its control using gamma radiation. Australian Journal of Basic and Applied Sciences, 3(2): 552–560. Ref #: 5141. Citation list of interventions studies (N=15): (Distiller ID = Ref #) Barrile, J. C., Cone, J. F., & Keeney, P. G. 1970a. A study of salmonellae survival in milk chocolate. Manufacturing Confectioner, 50(9): 34–39. Ref #: 6611. Barrile, J. C. & Cone, J. F. 1970b. Effect of added moisture on the heat resistance of Salmonella Anatum in milk chocolate. Applied Microbiology, 19(1): 177–178. Ref #: 6612. Baylis, C. L., MacPhee, S., Robinson, A. J., Griffiths, R., Lilley, K. & Betts, R. P. 2004. Survival of Escherichia coli O157:H7, O111:H- and O26:H11 in artificially contaminated chocolate and confectionery products. International Journal of Food Microbiology, 96(1): 35–48. Ref #: 2114. Bonvehí, J. S. & Isal, D. G. 2000. Evaluation of gamma-irradiation in cocoa husk. Journal of Agricultural and Food Chemistry, 48(6): 2489–2494. Ref #: 2608. Christian, J. H. B. & Stewart, B. J. 1973. Survival of Staphylococcus aureus and Salmonella Newport in dried foods, as influenced by water activity and oxygen. In B. C. Hobbs & J. H. B. Christian, eds. The Microbiological Safety of Foods: Proceedings of the Eighth International Symposium on Food Microbiology, pp. 107-119. Reading, England, September 1972. Ref #: 6774. Goepfert, J. M. & Biggie, R. A. 1968. Heat resistance of Salmonella Typhimurium and Salmonella Senftenberg 775W in milk chocolate. Applied Microbiology, 16(12): 1939–1940. Ref #: 4051. Izurieta, W. P. & Komitopoulou, E. 2012. Effect of moisture on Salmonella spp. heat resistance in cocoa and hazelnut shells. Food Research International, 45(2): 1087– 1092. Ref #: 4542. Juven, B. J., Cox, N. A. & Bailey, J. S. 1984. Survival of Salmonella in dry food and feed. Journal of Food Protection, 47(6): 445–448. Ref #: 6775. Krapf, T. & Gantenbein-Demarchi, C. 2010. Thermal inactivation of Salmonella spp. during conching. Food Science and Technology, 43(4): 720–723. Ref #: 4943. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 108 Lee, B. H., Kermasha, S. & Baker, B. E. 1989. Thermal, ultrasonic and ultraviolet inactivation of Salmonella in thin films of aqueous media and chocolate. Food Microbiology, 6(3): 143–152. Ref #: 6671. Miller, D. L., Goepfert, J. M. & Amundson, C. H. 1972. Survival of Salmonellae and Escherichia coli during the spray drying of various food products. Journal of Food Science, 37(6): 828–831. Ref #: 6680. Nascimento, M. D. S. D., Brum, D. M., Pena, P. O., Berto, M. I. & Efraim, P. 2012. Inactivation of Salmonella during cocoa roasting and chocolate conching. International Journal of Food Microbiology, 159(3): 225–229. Ref #: 288. Nascimento, M. D. S. D., Pena, P. O., Brum, D. M., Imazaki, F. T., Tucci, M. L. S. & Efraim, P. 2013. Behavior of Salmonella during fermentation, drying and storage of cocoa beans. International Journal of Food Microbiology, 167(3): 363–368. Ref #: 35. Nummer, B. A., Shrestha, S. & Smith, J. V. 2012. Survival of Salmonella in a high sugar, low water-activity, peanut butter flavored candy fondant. Food Control, 27(1): 184– 187. Ref #: 6684. Zeid, A. A. M. A. 2009. Incidence of Bacillus cereus in corn snacks and its control using gamma radiation. Australian Journal of Basic and Applied Sciences, 3(2): 552–560. Ref #: 5141. ANNEX 1 109 A1.7 SUMMARY CARD: DRIED FRUITS AND VEGETABLES A1.7.1 Low-moisture food category description This summary covers dried and dehydrated fruits and vegetables, as well as dried seaweed and mushrooms. Examples of dried fruits included raisins, prunes, dates, dried mangos, dried apricots, desiccated coconut and fruit powders. Examples of dried vegetables included sun-dried vegetables (e.g. tomatoes and okra), vegetable powders and mixes (e.g. dry soup mixes), dehydrated vegetables (e.g. potato flakes and carrot slices), and vegetable flours (e.g. potato starch and yam flour). We also included dried legumes and legume flours in the dried vegetable category. For the purposes of summarizing prevalence and intervention information, data were collapsed across four categories: (1) dried/dehydrated fruits, (2) dried/dehydrated vegetables, (3) dried/dehydrated mushrooms, and (4) dried seaweed. A1.7.2 Evidence summary In total, 39 articles8 and outbreak reports9 were identified that investigated the burden of illness, the prevalence or concentration of selected microbial hazards, and interventions to reduce contamination of microbial hazards in dried fruits and vegetables. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in A Appendix F: Summary Card Evidence Charts. Salmonella spp. was the most frequently investigated microbial hazard in dried fruits and vegetables for burden of illness (n=3 outbreak reports), prevalence (n=12 articles), and intervention (n=8 articles) information. A1.7.3 Burden of illness Burden of illness evidence related to dried fruits and vegetables includes three reported outbreaks between 1953 and 2004. Salmonella was implicated in all outbreaks affecting 719 individuals (median 50, range 18–651), including 247 hospitalizations and one death. The dried fruit and vegetable outbreaks are shown in the summary table below and were reported from Australia, the United Kingdom of Great Britain and Northern Ireland and Greece. 8 Articles refer to peer-reviewed journal publications as well as government and research agency reports. 9 For burden of illness information, multiple articles often reported complementary and/or overlapping information on the same outbreak. In addition, outbreak data were supplemented from other literature sources, including line lists from various countries, news reports, or annual summaries of country outbreaks. Thus, to avoid counting the same outbreak more than once, the term “outbreak report” is used instead of “article” to count the total number of unique outbreaks. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 110 TABLE A1.11 Summary table of globally reported outbreaks on dried fruits and vegetables Dried fruit or vegetable category/specific source (reference) Microbial hazard(s) Outbreaks/ cases/ hospitalized/ deathsa Country (year)b Comments: susceptible populations/ attack rate/ concentration of microbial hazard in the product Desiccated coconut (Ward, 1999; Wilson, 1953) Salmonella Typhi, Senftenberg Java phage type Dundee 2/68/7/0 Australia (1953), United Kingdom of Great Britain and Northern Ireland (1998) Retail desiccated coconut. Raisins & chickpea powder (Mellou, 2014) Salmonella Enteritidis (9:g, m: - ) 1/651/247/1 Greece (2004) Contaminated kolliva served at 8 funerals. Raisins and chickpea powder=confirmed contaminated ingredient. Attack rate >70% a Superscript C indicates confirmed cases; p indicates presumptive cases. b Superscript E indicates the link between human cases and implicated product was epidemiological only; otherwise, the link was laboratory confirmed. Most of these outbreaks were small and isolated to one batch of a retail product. The Kolliva outbreak from Greece was largely caused by temperature abuse, and the source of the contamination was confirmed to be raisins and chickpea powder. A1.7.4 Prevalence A total of 23 studies containing 64 unique trials were identified that investigated the prevalence and/or concentration of one or more selected microbial hazards in dried fruits and vegetables. The median publication year was 2008 (range 1992–2014). Most studies (70 percent) were conducted in Europe (n=9) and Asia/the Middle East (n=7) > Africa (4) > Brazil (2) > New Zealand (1). Most studies (78 percent) sampled products during a specific or defined period, while two conducted sampling over multiple time points, and three reported on the results of systematic ANNEX 1 111 surveillance programmes. Over 80 percent of studies sampled products at retail (e.g. markets and grocery stores) and/or from imports, and four sampled from processing facilities. Only 9/23 studies (39 percent) specified the country(s) of product origin. Most studies investigated Salmonella spp. and/or generic E. coli in dried fruits, and B. cereus and/or Cronobacter spp. in dried vegetables. Salmonella spp. was detected at a very low prevalence in dried fruits (median 0 percent), apart from one study that found a prevalence of 33 percent (6/20) in raisin samples in India (Sharma et al., 2008). Generic E. coli and S. aureus were not identified in dried fruits, but they were detected in 1/16 and 4/16 samples, respectively, of sun-dried okra from Nigeria (Arise et al., 2012). B. cereus and Cronobacter spp. were identified at highly variable prevalence levels in dried fruits and vegetables, with B. cereus prevalence approaching or at 100 percent in several trials. Enterobacteriaceae were investigated in a small number of total samples (n=37) of dried fruit in two studies, with an average prevalence of 7.8 percent (95 percent CI: 1.1 to 18.6). One study investigated C. botulinum in dried mushrooms (not shown in the table below); the authors did not isolate C. botulinum spores from 48 samples in China (Malakar et al., 2013). No prevalence studies were identified investigating dried seaweed. C. perfringens and L. monocytogenes were not identified in any study. Few studies reported extractable concentration data on levels of selected microbial hazards in dried fruits and vegetables (not shown in the table below). Average (standard deviation) concentrations of Enterobacteriaceae and Salmonella spp. in 2/20 and 6/20 positive samples of raisins in India were 15 (7.1) and 8.5 x 103 (2.0 x 104) CFU/g, respectively (Sharma et al., 2008). Concentrations of Salmonella spp. in raisins (1/3 samples) and prunes (1/3 samples) from South Africa were 10 and 40 CFU/g, respectively (Witthuhn et al., 2005). Concentrations of B. cereus in positive samples (37/50) of dehydrated potato flakes from New Zealand ranged from 10 to 370 CFU/g, with only eight samples >100 CFU/g (Turner et al., 2006). The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. Taking into consideration the number of studies in the meta-analysis, high confidence in the meta-analysis results can be inferred when heterogeneity is low and the risk of selection bias is low, and low confidence can be inferred when both are high; see the methods section for more information. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 112 TABLE A1.12 Prevalence of selected microbial hazards within dried fruit and vegetable categories (Each cell includes the number of observations/trials/studies contributing to the average or median prevalence estimate, the proportion of trials that did not find any positive samples, measures of heterogeneity and risk of selection bias. See the table footnotes for detailed explanations on each of these parameters.) Dried fruits and vegetables Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Dried/dehydrated fruits Dried/dehydrated vegetables B. cereus 556/2/2 (0%) 50.2 (0–100)R High/Med. 230/6/4 (0%) 98 (13–100)R High/High C. perfringens 1/1/1 (100%)0 N/A/High N/A Cronobacter spp. 10/1/1 (0%) 10 N/A/High 114/6/4 (33%) 9.8 (0–60)R High/Med. Generic E. coli 822/8/4 (100%)0 (0–0)R Low/High 16/1/1 (0%) 6.3 N/A/High Enterobacteriaceae 37/6/2 (83%) 7.8 (1.1–18.6)M Low/High N/A L. monocytogenes 555/1/1 (100%) 0 N/A/Low N/A S. aureus 766/3/3 (100%) 0 (0–0)R Low/Low 16/1/1 (0%) 25 N/A/High Salmonella spp. 1150/14/10 (71%) 0 (0–33.3)R High/Med. N/A N/A = No data identified for this product-hazard combination. Med. = medium. a Observations/trials/studies: The observations are the total number of samples for all studies included in the summarized category. The number of studies is the number of articles captured. In some cases, articles report data on multiple prevalence trials or sampling frames. While the observations for each trial are independent by time and sample, they are part of a larger study where the methods and investigators are the same. Thus, there is not full independence in these observations, and we note this by acknowledging there are multiple trials within a study. b Superscript M indicates an average prevalence estimate (and 95 percent confidence interval) from a random-effects meta-analysis. Meta-analysis estimates were calculated only if heterogeneity was low or medium (I2 0–60 percent) and if at least one trial found a positive sample. Superscript R indicates a median (and range) of trial prevalence estimates, calculated if heterogeneity was high (I2 >60 percent). Ranges not provided when only one trial was identified. c I2 is a measure of the degree of heterogeneity between trials combined in the meta-analysis. Heterogeneity rating definitions: low = I2 0–30 percent; medium = 31–60 percent; high = >60 percent. Selection bias rating definitions: high = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. Studies that conducted random or systematic sampling were considered representative. ANNEX 1 113 TABLE A1.13 Forest plot of the prevalence of selected microbial hazards within dried fruit and vegetable categories Microbial hazard/LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs. /trials/ studies Heterogeneity Selection bias Median (range) B. cereus Dried fruits 27.1 0.0 100.0 556/2/2 High Med. 50.2 (0–100) Dried vegetables 88.6 67.0 100.0 230/6/4 High High 98 (13–100) Overall 76.3 19.0 100.0 High 98 (0.4–100) Cronobacter spp. Dried fruits 10.0 - - 10/1/1 N/A High - Dried vegetables 10.8 0.9 27.2 114/6/4 High Med. 9.8 (0–60) Overall 11.1 2.0 25.1 High 0.1 (0–60) Generic E. coli Dried fruits 0.0 0.0 0.0 822/8/4 Low High - Dried vegetables 6.3 - - 16/1/1 N/A High - Overall 0.2 0.0 0.9 Low - S. aureus Dried fruits 0.0 0.0 0.0 766/3/3 Low Low - Dried vegetables 25.0 - - 16/1/1 N/A High - Overall 1.7 0.0 6.1 High 0(0–25) Salmonella spp. Overall 2.0 0.2 5.2 1 150/14/10 High 0 (0–33.3) CI = confidence interval; Med = medium; No. obs. =number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: C. perfringens and L. monocytogenes evidence not shown in this figure because no positive samples were identified in these categories. Salmonella spp. evidence is based on data from only the dried fruits subcategory. LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 114 A1.7.5 Interventions A total of 13 experimental studies (consisting of 44 unique trials) were identified evaluating the effects of various interventions to reduce contamination of microbial hazards in dried fruits and vegetables. The median publication year was 2005 (range 1973 to 2011). Studies were conducted in the United States of America (n=10), Türkiye (1), Thailand (1) and the Republic of Korea (1). All studies were challenge trials with artificially inoculated samples. None of the studies were conducted under commercial conditions, and most included only a small number of samples (two to ten replicates per intervention combination). The most investigated interventions were various chemical dips and heat treatments applied to fruits and vegetables to reduce contamination of Salmonella spp. and E. coli prior to drying with home-type dehydrators. Nearly all pre-drying treatments were found to be more effective at reducing levels of microbial hazard contamination on the final dried product compared to drying without any pre-treatment; however, in some cases these pre-treatments were not superior to dipping products in sterile water (Derrickson-Tharrington, Kendall and Sofos, 2005; Yoon et al., 2004). One study found that irradiation resulted in a statistically significant reduction in concentration of E. coli, S. aureus, and Salmonella spp. on dried seaweed (Jo et al., 2005), and one study found that gaseous ozone can produce a statistically significant reduction of B. cereus and generic E. coli contamination of dried figs (Akbas and Ozdemir, 2008). Other studies investigated modified storage conditions and packaging on Salmonella spp., pathogenic E. coli, and S. aureus survival in various dried fruits and vegetables (Christian and Stewart, 1973; Deng et al., 1998; Park and Beuchat, 2000). ANNEX 1 115 TA B LE A 1. 14 S um m ar y ta bl e of e xp er im en ta l s tu di es e va lu at in g th e eff ec ts o f i nt er ve nt io ns t o re du ce c on ta m in at io n of s el ec te d m ic ro bi al ha za rd s in d ri ed fr ui ts a nd v eg et ab le s Fo od ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or du ra ti on , w he re a va ila bl e) So ur ce (s ) M ic ro bi al ha za rd (s ) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io na D ri ed fr ui ts P re -d ry in g (5 7. 2– 62 .8 °C ; 6 h r) ch em ic al d ip s A sc or bi c ac id (2 .8 –3 .4 % ; 1 0 –1 5 m in ) C it ri c ac id (1 .7 % ; 1 0 m in ) Le m on ju ic e (5 0 % ; 1 0 m in ) Le m on ju ic e w it h pr es er va ti ve s (5 0 % ; 1 0 m in ) (B ur nh am , K en da ll an d So fo s, 2 0 0 1) ; ( D er ri ck so n- Th ar ri ng to n, K en da ll an d So fo s, 2 0 0 5) ; (D er ri ck so n- Th ar ri ng to n, K en da ll an d So fo s, 2 0 0 5) ; (D er ri ck so n- Th ar ri ng to n, K en da ll an d So fo s, 2 0 0 5) ; (D er ri ck so n- Th ar ri ng to n, K en da ll an d So fo s, 2 0 0 5) E . c ol i O 15 7: H 7 5/ 2 83 10 0 P re -d ry in g (6 0 °C ; 6 hr ) c he m ic al di ps A sc or bi ß c ac id d ip (3 .4 % ; 2 5° C ; 10 m in ) C it ri c ac id (0 .2 1% ; 1 0 m in ) So di um m et ab is ul fit e (4 .1 8% ; 1 0 m in ) (D iP er si o et a l., 2 0 0 3) S al m on el la sp p. 3/ 1 10 0 10 0 P re -d ry in g (5 7. 2– 62 .8 °C ; 6 h r) h ea t tr ea tm en t St ea m b la nc hi ng (8 8° C ; 3 m in ) (B ur nh am , K en da ll an d So fo s, 2 0 0 1) E . c ol i O 15 7: H 7 1/ 1 0 0 O zo ne G as (0 .1 –1 p pm ; 7 0 % R H ; 6 0 –3 60 m in ) (A kb as a nd O zd em ir, 20 0 8) B . c er eu s 2/ 1 0 10 0 O zo ne G as (0 .1 –1 p pm ; 7 0 % R H ; 6 0 –3 60 m in ) (A kb as a nd O zd em ir, 20 0 8) G en er ic E . c ol i 1/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (5 –3 7° C ; 1– 19 w ee ks ) (D en g, R yu a nd B eu ch at , 19 98 ) E . c ol i O 15 7: H 7 2/ 1 0 10 0 D ri ed ve ge ta bl es D ry in g H ot a ir (5 0 –7 0 °C ; 0 –1 6 hr ) Lo w -p re ss ur e su pe rh ea te d st ea m an d va cu um (1 0 k P a; 5 0 –7 0 °C ; 0 –1 6 hr ) (P hu ng am ng oe n, C hi ew ch an a nd D ev ah as ti n, 2 0 11 ) S al m on el la sp p. 3/ 1 0 10 0 (c on t. ) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 116 Fo od ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or du ra ti on , w he re a va ila bl e) So ur ce (s ) M ic ro bi al ha za rd (s ) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io na H ea t tr ea tm en t D ry h ea t (8 0 °C ; 1 5 m in ) (D iP er si o, 2 0 0 5a ) S al m on el la sp p. 1/ 1 0 0 P re -d ry in g (6 0 °C ; 6 hr ) c he m ic al di ps A sc or bi c ac id (3 .4 % ; 1 0 m in ) So di um c hl or id e (3 .2 3% ; 2 5° C ; 5 m in ) C it ri c ac id (0 .1 0 5– 0 .2 1% ; 8 8° C ; 4 m in ) (Y oo n et a l., 2 0 0 4 ); (D iP er si o, 2 0 0 5a ); (D iP er si o, 2 0 0 5b , 2 0 0 7) ; (Y oo n e t al ., 20 0 4 ) S al m on el la sp p. 7/ 4 57 10 0 * P re -d ry in g (6 0 °C ; 6 h r) h ea t tr ea tm en t W at er b la nc hi ng (8 8° C ; 3 –4 m in ) St ea m b la nc hi ng (8 8° C ; 3 –1 0 m in ) D iP er si o (2 0 0 5a , b , 20 0 7) ; D iP er si o (2 0 0 5a , b, 2 0 0 7) ; ( Yo on e t al ., 20 0 4 ) S al m on el la sp p. 7/ 4 4 3 86 M od ifi ed pa ck ag in g A ir (o xy ge n 0 .5 –2 0 % ) v s. v ac uu m (1 –2 7 w ee ks ) (C hr is ti an a nd S te w ar t, 19 73 ) S al m on el la sp p. , S . a ur eu s 2/ 1 0 10 0 M ul ti pl e pr e- dr yi ng (6 0 °C ; 6 hr ) t re at m en ts St ea m b la nc hi ng (8 8° C ; 3 m in ) + as co rb ic a ci d di p (3 .4 % ; 1 0 m in ) (Y oo n et a l., 2 0 0 4 ) S al m on el la sp p. 2/ 1 10 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (4 –3 7° C ), in cr ea se d aw (0 .2 6– 0 .7 8) , de cr ea se d pH (4 .1 –6 .7 ; 1 –3 3 w ee ks ) (P ar l a nd B ea uc ha t, 20 0 0 ) E . c ol i O 15 7: H 7 3/ 1 0 67 St or ag e co nd it io ns In cr ea se d aw (0 .1 1– 0 .5 3; 1– 27 w ee ks ) (C hr is ti an a nd S te w ar t, 19 73 ) S al m on el la sp p. , S . a ur eu s 2/ 1 0 10 0 D ri ed se aw ee d Ir ra di at io n G am m a (1 –3 k G y; 10 k G y/ hr ) (J o et a l., 2 0 0 5) G en er ic E . co li, S . a ur eu s, S al m on el la sp p. 3/ 1 10 0 10 0 a I nt er ve nt io n ca te go ri es m ar ke d w it h an a st er is k (* ) i nd ic at e th at m or e tr ia ls fo un d a st at is ti ca lly s ig ni fic an t r ed uc ti on in m ic ro bi al c on ce nt ra ti on o r p re va le nc e th an w ou ld b e ex pe ct ed b y ch an ce a lo ne (s ig n te st P v al ue < 0 .0 5) . Si gn ifi ca nc e on ly c al cu la te d if m or e th an o ne s tu dy w as c on du ct ed p er in te rv en ti on /m ic ro bi al h az ar d/ st ud y ty pe c om bi na ti on . ANNEX 1 117 A1.7.6 References in A1.7 References used in summary narrative: Akbas, M. Y. & Ozdemir, M. 2008. Application of gaseous ozone to control populations of Escherichia coli, Bacillus cereus and Bacillus cereus spores in dried figs. Food Microbiology, 25(2): 386–391. Arise, A. K., Arise, R. O., Akintola, A. A., Idowu, O. A. & Aworh, O. C. 2012. Microbial, nutritional and sensory evaluation of traditional sundried okra (orunla) in selected markets in south-western Nigeria. Pakistan Journal of Nutrition, 11(3): 231–236. Christian, J. H. B. & Stewart, B. J. 1973. Survival of Staphylococcus aureus and Salmonella Newport in dried foods, as influenced by water activity and oxygen. In B. C. Hobbs & J. H. B. Christian, eds. The Microbiological Safety of Foods: Proceedings of the Eighth International Symposium on Food Microbiology, pp. 107–119. Reading, England, September 1972. Derrickson-Tharrington, E., Kendall, P. A. & Sofos, J. N. 2005. Inactivation of Escherichia coli O157:H7 during storage or drying of apple slices pretreated with acidic solutions. International Journal of Food Microbiology, 99(1): 79–89. Deng, Y., Ryu, J. H. & Beuchat, L. R. 1998. Influence of temperature and pH on survival of Escherichia coli O157:H7 in dry foods and growth in reconstituted infant rice cereal. International Journal of Food Microbiology, 45(3): 173–184. Jo, C., Lee, N. Y., Kang, H. J., Hong, S. P., Kim, Y. H., Kim, J. K. & Byun, M. W. 2005. Inactivation of pathogens inoculated into prepared seafood products for manufacturing kimbab, steamed rice rolled in dried seaweed, by gamma irradiation. Journal of Food Protection, 68(2): 396–402. Malakar, P. K., Plowman, J., Aldus, C. F., Xing, Z., Zhao, Y. & Peck, M. W. 2013. Detection limit of Clostridium botulinum spores in dried mushroom samples sourced from China. International Journal of Food Microbiology, 166(1): 72–76. Park, C.-M. & Beuchat, L. R. 2000. Survival of Escherichia coli O157:H7 in potato starch as affected by water activity, pH and temperature. Letters in Applied Microbiology, 31: 364–367. Sharma, S., Chandra, P., Mishra, C. & Kakkar, P. 2008. Microbiological quality and organochlorine pesticide residue in commercially available ready-to-eat raisins. Bulletin of Environmental Contamination and Toxicology, 81(4): 387–392. Turner, N. J., Whyte, R., Hudson, J. A. & Kaltovei, S. L. 2006. Presence and growth of Bacillus cereus in dehydrated potato flakes and hot-held, ready-to-eat potato products purchased in New Zealand. Journal of Food Protection, 69(5): 1173–1177. Witthuhn, R. C., Engelbrecht, S., Joubert, E. & Britz, T. J. 2005. Microbial content of commercial South African high-moisture dried fruits. Journal of Applied Microbiology, 98(3): 722–726. F oo d ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or du ra ti on , w he re a va ila bl e) So ur ce (s ) M ic ro bi al ha za rd (s ) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io na H ea t tr ea tm en t D ry h ea t (8 0 °C ; 1 5 m in ) (D iP er si o, 2 0 0 5a ) S al m on el la sp p. 1/ 1 0 0 P re -d ry in g (6 0 °C ; 6 hr ) c he m ic al di ps A sc or bi c ac id (3 .4 % ; 1 0 m in ) So di um c hl or id e (3 .2 3% ; 2 5° C ; 5 m in ) C it ri c ac id (0 .1 0 5– 0 .2 1% ; 8 8° C ; 4 m in ) (Y oo n et a l., 2 0 0 4 ); (D iP er si o, 2 0 0 5a ); (D iP er si o, 2 0 0 5b , 2 0 0 7) ; (Y oo n e t al ., 20 0 4 ) S al m on el la sp p. 7/ 4 57 10 0 * P re -d ry in g (6 0 °C ; 6 h r) h ea t tr ea tm en t W at er b la nc hi ng (8 8° C ; 3 –4 m in ) St ea m b la nc hi ng (8 8° C ; 3 –1 0 m in ) D iP er si o (2 0 0 5a , b , 20 0 7) ; D iP er si o (2 0 0 5a , b, 2 0 0 7) ; ( Yo on e t al ., 20 0 4 ) S al m on el la sp p. 7/ 4 4 3 86 M od ifi ed pa ck ag in g A ir (o xy ge n 0 .5 –2 0 % ) v s. v ac uu m (1 –2 7 w ee ks ) (C hr is ti an a nd S te w ar t, 19 73 ) S al m on el la sp p. , S . a ur eu s 2/ 1 0 10 0 M ul ti pl e pr e- dr yi ng (6 0 °C ; 6 hr ) t re at m en ts St ea m b la nc hi ng (8 8° C ; 3 m in ) + as co rb ic a ci d di p (3 .4 % ; 1 0 m in ) (Y oo n et a l., 2 0 0 4 ) S al m on el la sp p. 2/ 1 10 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (4 –3 7° C ), in cr ea se d aw (0 .2 6– 0 .7 8) , de cr ea se d pH (4 .1 –6 .7 ; 1 –3 3 w ee ks ) (P ar l a nd B ea uc ha t, 20 0 0 ) E . c ol i O 15 7: H 7 3/ 1 0 67 St or ag e co nd it io ns In cr ea se d aw (0 .1 1– 0 .5 3; 1– 27 w ee ks ) (C hr is ti an a nd S te w ar t, 19 73 ) S al m on el la sp p. , S . a ur eu s 2/ 1 0 10 0 D ri ed se aw ee d Ir ra di at io n G am m a (1 –3 k G y; 10 k G y/ hr ) (J o et a l., 2 0 0 5) G en er ic E . co li, S . a ur eu s, S al m on el la sp p. 3/ 1 10 0 10 0 a I nt er ve nt io n ca te go ri es m ar ke d w it h an a st er is k (* ) i nd ic at e th at m or e tr ia ls fo un d a st at is ti ca lly s ig ni fic an t r ed uc ti on in m ic ro bi al c on ce nt ra ti on o r p re va le nc e th an w ou ld b e ex pe ct ed b y ch an ce a lo ne (s ig n te st P v al ue < 0 .0 5) . Si gn ifi ca nc e on ly c al cu la te d if m or e th an o ne s tu dy w as c on du ct ed p er in te rv en ti on /m ic ro bi al h az ar d/ st ud y ty pe c om bi na ti on . RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 118 Yoon, Y., Stopforth, J. D., Kendall, P. A. & Sofos, J. N. 2004. Inactivation of Salmonella during drying and storage of roma tomatoes exposed to predrying treatments including peeling, blanching, and dipping in organic acid solutions. Journal of Food Protection, 67(7): 1344–1352. Citation list of burden of illness studies (n=3 unique citations): (Distiller ID = Ref #, Outbreak # = OB # where a Distiller ID is not available – for unpublished outbreaks) Mellou K. 2014. “Query regarding a Salmonella outbreak, Greece, 2004.” Personal communication. Head of the Foodborne Disease Section of Greek CDC. 5 February 2014. OB#72. Ward, L., Duckworth, G. & O’Brien, S. 1999. Salmonella java phage type Dundee - rise in cases in England: update. Euro Surveillance, 3(12): 1435. OB#34. Wilson, M. & Mackenzie, E. 1953. “Typhoid fever and salmonellosis due to the consumption of infected desiccated coconut.” Symposium on Food Microbiology and Public Health: Paper VII. Melbourne, Australia. (also available at https:// sfamjournals.onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2672.1955. tb02110.x). Ref #: 6713. Citation list of prevalence studies (N=23): (Distiller ID = Ref #) Al Askari, G., Kahouadji, A., Khedid, K., Charof, R. & Mennane, Z. 2012. Physicochemical and microbiological study of “raisin”, local and imported (Morocco). Middle East Journal of Scientific Research, 11(1): 1–6. Ref #: 4449. Al Jawally, E. A. K. 2010. Microbiological analysis of date palm fruit sold in Abu Dhabi emirate. Acta Horticulturae, 882: 1209–1212. Ref #: 4817. Arise, A. K., Arise, R. O., Akintola, A. A., Idowu, O. A. & Aworh, O. C. 2012. Microbial, nutritional and sensory evaluation of traditional sundried okra (orunla) in selected markets in south-western Nigeria. Pakistan Journal of Nutrition, 11(3): 231–236. Ref #: 4538. Da Silva, C. G. M., De, M. F., Pires, E. F. & Stamford, T. L. M. 2007. Physicochemical and microbiological characterization of mesquite flour (Prosopis juliflora (sw.) DC). Ciencia e Tecnologia De Alimentos, 27(4): 733–36. Ref #: 5424. Dósea, R. R., Marcellini, P. S., Santos, A. A., Ramos, A. L. D. & Lima, A. S. 2010. Microbiological quality in the flour and starch cassava processing in traditional and model unit. Ciencia Rural, 40(2): 441–446. Ref #: 4982. ANNEX 1 119 EFSA & ECDC. 2011. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2009. EFSA Journal, 9(3): 2090. Ref #: 6636. Erol, I., Hildebrandt, G., Goncuoglu, M., Ormanci, F. S. B., Yurtyeri, A., Kleer, J. & Kuplulu, O. 2009. Incidence and serotype distribution of Salmonella in spices retailed in Turkey. Fleischwirtschaft, 6: 50-51. Ref #: 6761. Hara-Kudo, Y., Ohtsuka, K., Onoue, Y., Otomo, Y., Furukawa, I., Yamaji, A., Segawa, Y. & Takatori, K. 2006. Salmonella prevalence and total microbial and spore populations in spices imported to Japan. Journal of Food Protection, 69(10): 2519– 2523. Ref #: 1725. Hochel, I., Ruzickova, H., Krasny, L. & Demnerova, K. 2012. Occurrence of Cronobacter spp. in retail foods. Journal of Applied Microbiology, 112(6): 1257–1265. Ref #: 463. Iversen, C. & Forsythe, S. 2004. Isolation of Enterobacter sakazakii and other Enterobacteriaceae from powdered infant formula milk and related products. Food Microbiology, 21(6): 771–777. Ref #: 6660. Kandhai, M. C., Heuvelink, A. E., Reij, M. W., Beumer, R. R., Dijk, R., van Tilburg, J. J. H. C. & Gorris, L. G. M. 2010. A study into the occurrence of Cronobacter spp. in the Netherlands between 2001 and 2005. Food Control, 21(8): 1127–1136. Ref #: 6664. Kneifel, W. & Berger, E. 1994. Microbiological criteria of random samples of spices and herbs retailed on the Austrian market. Journal of Food Protection, 57(10): 893–901. Ref #: 6668. Malakar, P. K., Plowman, J., Aldus, C. F., Xing, Z., Zhao, Y. & Peck, M. W. 2013. Detection limit of Clostridium botulinum spores in dried mushroom samples sourced from China. International Journal of Food Microbiology, 166(1): 72–76. Ref #: 99. Meldrum, R. J., Smith, R. M., Ellis, P., Garside, J. & Welsh Food Microbiological Forum. 2006. Microbiological quality of randomly selected ready-to-eat foods sampled between 2003 and 2005 in Wales, the United Kingdom. International Journal of Food Microbiology, 108(3): 397–400. Ref #: 1854. Mena, C. & Kakkar, P. 2008. Microbiological quality and organochlorine pesticide residue in commercially available ready-to-eat raisins. Bulletin of Environmental Contamination and Toxicology, 81(4): 387–392. Ref #: 1341. Turcovsky, I., Kunikova, K., Drahovska, H. & Kaclikova, E. 2011. Biochemical and molecular characterization of Cronobacter spp. (formerly Enterobacter sakazakii) isolated from foods. Antonie Van Leeuwenhoek, 99(2): 257–269. Ref #: 899. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 120 Turner, N. J., Whyte, R., Hudson, J. A. & Kaltovei, S. L. 2006. Presence and growth of Bacillus cereus in dehydrated potato flakes and hot-held, ready-to-eat potato products purchased in New Zealand. Journal of Food Protection, 69(5): 1173–1177. Ref #: 1813. Witthuhn, R. C., Engelbrecht, S., Joubert, E. & Britz, T. J. 2005. Microbial content of commercial South African high-moisture dried fruits. Journal of Applied Microbiology, 98(3): 722–726. Ref #: 2026. Yusof, N., Ramli, R. A. A. & Ali, F. 2007. Chemical, sensory and microbiological changes of gamma irradiated coconut cream powder. Radiation Physics and Chemistry, 76(11): 1882–1884. Ref #: 6714. Yusuf, I. Z., Umoh, V. J. & Ahmad, A. A. 1992. Occurrence and survival of enterotoxigenic Bacillus cereus in some Nigerian flour-based foods. Food Control, 3(3): 149–152. Ref #: 6344. Citation list of interventions studies (N=13): (Distiller ID = Ref #) Akbas, M. Y. & Ozdemir, M. 2008. Application of gaseous ozone to control populations of Escherichia coli, Bacillus cereus and Bacillus cereus spores in dried figs. Food Microbiology, 25(2): 386–391. Ref #: 6601. Burnham, J. A., Kendall, P. A. & Sofos, J. N. 2001. Ascorbic acid enhances destruction of Escherichia coli O157:H7 during home-type drying of apple slices. Journal of Food Protection, 64(8): 1244–1248. Ref #: 6615. Christian, J. H. B. & Stewart, B. J. 1973. Survival of Staphylococcus aureus and Salmonella Newport in dried foods, as influenced by water activity and oxygen. In B. C. Hobbs and J. H. B. Christian, eds. The Microbiological Safety of Foods: Proceedings of the Eighth International Symposium on Food Microbiology, pp. 107-119. Reading, England, September 1972. Ref #: 6774. Deng, Y., Ryu, J. H. & Beuchat, L. R. 1998. Influence of temperature and pH on survival of Escherichia coli O157:H7 in dry foods and growth in reconstituted infant rice cereal. International Journal of Food Microbiology, 45(3): 173–184. Ref #: 6628. Derrickson-Tharrington, E., Kendall, P. A. & Sofos, J. N. 2005. Inactivation of Escherichia coli O157:H7 during storage or drying of apple slices pretreated with acidic solutions. International Journal of Food Microbiology, 99(1): 79–89. Ref #: 6752. DiPersio, P. A., Kendall, P. A., Calicioglu, M. & Sofos, J. N. 2003. Inactivation of Salmonella during drying and storage of apple slices treated with acidic or sodium metabisulfite solutions. Journal of Food Protection, 66(12): 2245–2251. Ref #: 6753. ANNEX 1 121 DiPersio, P. A., Kendall, P. A., Yoon, Y. & Sofos, J. N. 2005a. Influence of blanching treatments on Salmonella during home-type dehydration and storage of potato slices. Journal of Food Protection, 68(12): 2587–2593. Ref #: 1881. DiPersio, P. A., Yoon, Y., Sofos, J. N. & Kendall, P. A. 2005b. Inactivation of Salmonella during drying and storage of carrot slices prepared using commonly recommended methods. Journal of Food Science, 70(4): M230–M235. Ref #: 5740. Dipersio, P. A., Kendall, P. A., Yoon, Y. & Sofos, J. N. 2007. Influence of modified blanching treatments on inactivation of Salmonella during drying and storage of carrot slices. Food Microbiology, 24(5): 500–507. Ref #: 1653. Jo, C., Lee, N. Y., Kang, H. J., Hong, S. P., Kim, Y. H., Kim, J. K. & Byun, M. W. 2005. Inactivation of pathogens inoculated into prepared seafood products for manufacturing kimbab, steamed rice rolled in dried seaweed, by gamma irradiation. Journal of Food Protection, 68(2): 396–402. Ref #: 2023. Park, C.-M. & Beuchat, L. R. 2000. Survival of Escherichia coli O157:H7 in potato starch as affected by water activity, pH and temperature. Letters in Applied Microbiology, 31: 364–367. Ref #: 6777. Phungamngoen, C., Chiewchan, N. & Devahastin, S. 2011. Thermal resistance of Salmonella enterica serovar Snatum on cabbage surfaces during drying: Effects of drying methods and conditions. International Journal of Food Microbiology, 147(2): 127–133. Ref #: 6688. Yoon, Y., Stopforth, J. D., Kendall, P. A. & Sofos, J. N. 2004. Inactivation of Salmonella during drying and storage of roma tomatoes exposed to predrying treatments including peeling, blanching, and dipping in organic acid solutions. Journal of Food Protection, 67(7): 1344–1352. Ref #: 2132. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 122 A1.8 SUMMARY CARD: DRIED PROTEIN PRODUCTS A1.8.1 Low-moisture food category description This summary covers dried protein products. For the purposes of summarizing prevalence and intervention information, data were collapsed across four categories: (1) dairy products (e.g. milk, whey, and milk-product powders); (2) egg products (e.g. egg powders); (3) fish/seafood products (e.g. dried fish and fish meal/flour); and (4) meat products other than sausages, salamis and jerkies (e.g. gelatin and meat powders). Although the search included terms for dry protiens of plant origin (e.g. soy powder), no evidence on these products was identified in this scoping review. Specifically excluded from this summary are dried and/or fermented sausages, salamis, and jerkies, which can have a low water activity (i.e. aw <0.85). However, they were excluded due to the vast amount of literature identified in this area and reporting limitations (the water activity of products in most studies could not be confirmed). Also excluded is powdered infant formula, which was considered beyond the scope of this review. A1.8.2 Evidence summary In total, 66 articles10 and outbreak reports11 were identified that investigated the burden of illness, the prevalence or concentration of selected microbial hazards, and interventions to reduce contamination of microbial hazards in dried protein products. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in Appendix F: Summary Card Evidence Charts. Salmonella spp. was the most frequently investigated microbial hazard in dried protein products for burden of illness (n=6 outbreak reports) and intervention (n=10 articles) information, while Cronobacter spp. was the most investigated microbial hazard in prevalence studies (n=20 articles). A1.8.3 Burden of illness Burden of illness evidence related to dried protein products included 13 outbreaks, six attributed to powdered milk and seven attributed to dried fish. There were no outbreaks related to dry vegetable proteins such as soy powders. Outbreaks occurred 10 Articles refer to peer-reviewed journal publications as well as government and research agency reports. 11 For burden of illness information, multiple articles often reported complementary and/or overlapping information on the same outbreak. In addition, outbreak data were supplemented from other literature sources, including line lists from various countries, news reports, or annual summaries of country outbreaks. Thus, to avoid counting the same outbreak more than once, the term “outbreak report” is used instead of “article” to count the total number of unique outbreaks. ANNEX 1 123 in the United States of America (2), Ukraine (2), Japan (2), Trinidad and Tobago, France, Singapore, Canada, Russian Federation and Germany. There was a lot of variation in the size of the outbreaks captured in each category. Hospitalizations and deaths were only reported from dried fish outbreaks involving C. botulinum. The six powdered milk outbreaks 1965–2006 were caused by Salmonella in three outbreaks affecting 3 078 individuals (median 49, range 29–3 000) and S. aureus in the remaining three outbreaks affecting 13 606 individuals (median 150, range 3–13 420). The large outbreak in this category was from Japan, and they were not able to culture S. aureus from the powdered milk; however, staphylococcal enterotoxin A was detectable at high enough concentrations to cause illness. The seven outbreaks attributed to commercial dried fish products included three due to Salmonella that affected 1 540 individuals (median 33, range 2–1 505). The remaining four outbreaks were caused by C. botulinum contamination and affected 16 people, including 14 hospitalizations and one death. The median outbreak size was four (range 3–6). TABLE A1.15 Summary table of globally reported outbreaks on dried protein products Dried protein category/specific source (reference) Microbial hazard(s) Outbreaks/ cases/ hospitalized/ deathsa Country (year)b Comments: susceptible populations/ attack rate/ concentration of microbial hazard in the product Milk Protein Powdered Milk (Collins et al., 1968; Weissman et al., 1977; Asao, 2003) Salmonella Worthington, Newbrunswick, Derby 3/3078/0/0 United States of America (1965), Trinidad and Tobago (1973), France (2005) Children <4 years comprised 89% of cases in the Trinidad outbreak. The outbreak in France was mainly in hospitalized patients. Powdered Milk (InVS 2005; Clark, 2006; Doyle, 2007) S. aureus 3/ 4949C, 8657P/0/0 Japan (2000), China (2004), United States of America (2006)E Most cases were from the large outbreak in Japan; viable S. aureus was not cultured in this outbreak, but the staphylococcal enterotoxin A concentration mean was 7.28 (range 1.4–26.2) ng/g (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 124 Dried protein category/specific source (reference) Microbial hazard(s) Outbreaks/ cases/ hospitalized/ deathsa Country (year)b Comments: susceptible populations/ attack rate/ concentration of microbial hazard in the product Fish/Seafood Protein Dried Anchovy (Ling et al., 2002; Anon., 2005) Salmonella Typhimurium DT104 2/35/0/0 Singapore (2000), Canada (2005) Singapore outbreak mainly involved infants and toddlers. Cuttlefish Chips (Miyakawa et al., 2006) Salmonella Oranienburg and Chester 1/1505/0/0 Japan (1999) Largely affected infants and toddlers. Commercial Dried Fish (Peck, 2003; Eriksen et al., 2004) C. botulinum 4/14C, 2P/14/1 Ukraine (2004E, 2005E), Russian Federation (2004)E, Germany (2003) Commercially produced dried fish snack. a Superscript C indicates confirmed cases; p indicates presumptive cases. b Superscript E indicates the link between human cases and implicated product was epidemiological only; otherwise, the link was laboratory confirmed. A1.8.4 Prevalence A total of 39 studies containing 90 unique trials were identified that investigated the prevalence and/or concentration of one or more selected microbial hazards in dried protein products. The median publication year was 2010 (range 1995– 2014). Most studies (72 percent) were conducted in Europe (n=18) and Asia/the Middle East (n=10) > Africa (6) > Latin/South America (4) > Australia (1). Most studies (74 percent) sampled products during a specific or defined period, while four conducted sampling over multiple time points, and six reported on the results of systematic surveillance programmes. Nearly 80 percent of studies sampled products at retail stores or markets (n=24) and from processing facilities (n=7). Only 13/39 studies (33 percent) specified the country(s) of product origin. Most studies investigated Cronobacter spp. in dried dairy products, which was found at a low average prevalence of 4.5 percent (95 percent CI 3 to 6.2 percent). Enterobacteriaceae were also found at a low median prevalence (3.3 percent) in dried dairy products. In a study of 813 milk powder samples that were presumptive positive for Enterobacteriaceae (not shown in the table below), Cronobacter spp. was found at a higher prevalence of 17 percent (Jacobs, Braun and Hammer, 2011). ANNEX 1 125 B. cereus was found at highly variable prevalence levels (ranging from 0 to 60 percent) in dried dairy products. C. botulinum was found in 3/26 milk powder samples in one study (Carlin et al., 2004), and L. monocytogenes was not identified from 100 milk powder samples in one study (Rodas-Suarez et al., 2013). Salmonella spp. was not isolated from dried dairy products or gelatin in any study. However, 1/61 batch samples of gelatin were found to be non-compliant with Salmonella criteria in European Union Regulation 2073/2005 in the 2008 summary surveillance report (EFSA and ECDC, 2010). In a study of eight samples of gelatin, Cronobacter spp. was isolated from one sample and generic E. coli was not found (de la Rosa, Medina and Vivar, 1995). Dried fish and seafood products were investigated in only two studies (not shown in the table below). In a representative study of 100 dried fish and seafood products in Republic of Korea, B. cereus, generic E. coli, and L. monocytogenes were found in 13, 1, and 1 samples, respectively, while C. perfringens, E. coli O157:H7, S. aureus and Salmonella spp. was not identified (Kim et al., 2013). In another study in Zambia, Salmonella spp. was isolated from 1/5 dried minnow samples (Jermini et al., 1997). No studies were identified that investigated microbial hazards in egg or meat powders. Few studies reported extractable concentration data on levels of selected microbial hazards in dried protein products (not shown in the table below). Average (standard deviation) concentrations of B. cereus in 29/65 and 2/35 positive samples of milk powder in Egypt were 630 (140) and 380 (200) CFU/g in two different brands, respectively (Deeb et al., 2010). Average concentrations of B. cereus in 175/381 positive samples of various milk powder products in Chile ranged from 6.4 to 5.96 x 103 MPN/g (Reyes et al., 2007). In 13/100 positive samples of dried fish and seafood products from the Republic of Korea, average (standard deviation) concentrations of B. cereus were 0.28 (0.74) log CFU/g (Kim et al., 2013). A1.8.5 Interventions A total of 14 experimental studies (consisting of 62 unique trials) were identified evaluating the effects of various interventions to reduce contamination of RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 126 microbial hazards in dried protein products. The median publication year was 1991 (range 1968 to 2013). Studies were conducted in the United States of America (n=9), Türkiye (2), Hungary (1), Jordan (1) and South Africa (1). All studies were challenge trials with artificially inoculated samples. None of the studies were conducted under commercial conditions, and most included only a small number of samples (2–10 replicates per intervention combination) or did not report their sample size. The most investigated interventions applied to dried protein products were various heat and drying treatments, chemical additives, and modified storage conditions. Interventions were applied towards Salmonella spp., pathogenic E. coli, Cronobacter spp., and S. aureus in dried dairy products, Salmonella spp. in dried egg and fish/ seafood products, and pathogenic E. coli in dried meat products. Except for chemical additives, most studies found that the investigated interventions resulted in statistically significant reductions in microbial hazard contamination on the final dried products. However, in some cases, treatments did not always reduce microbial hazards in dried protein products to a level at which they would not pose a risk to human health (LiCari and Potter, 1970a; Torlak and Sert, 2013). TABLE A1.16 Prevalence of selected microbial hazards within dried protein product categories (Each cell includes the number of observations/trials/studies contributing to the average or median prevalence estimate, the proportion of trials that did not find any positive samples and measures of heterogeneity and risk of selection bias. See the table footnotes for detailed explanations on each of these parameters.) Dried protein products Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Dried dairy products Gelatin B. cereus 632/7/7 (14%) 44.4 (0–60)R High/Med. N/A C. botulinum 26/1/1 (0%)11.5 N/A/High N/A Cronobacter spp. 2714/29/17 (45%) 4.5 (3.0–6.2)M Med./High 8/1/1 (0%) 12.5 N/A/High (cont.) ANNEX 1 127 Dried protein products Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Dried dairy products Gelatin Generic E. coli N/A 8/1/1 (0%) 0 N/A/High Enterobacteriaceae 2288/4/2 (50%) 3.3 (0–7.1)R High/Med. N/A L. monocytogenes 100/1/1 (100%) 0 N/A/Low N/A Salmonella spp. 4505/7/6 (100%) 0 (0–0)R Low/Low 565/6/5 (100%) 0 (0–0)R Low/Low N/A = No data identified for this product-hazard combination. Med. = medium. a Observations/trials/studies: The observations are the total number of samples for all studies included in the summarized category. The number of studies is the number of articles captured. In some cases, articles report data on multiple prevalence trials or sampling frames. While the observations for each trial are independent by time and sample, they are part of a larger study where the methods and investigators are the same. Thus, there is not full independence in these observations, and we note this by acknowledging there are multiple trials within a study. b Superscript M indicates an average prevalence estimate (and 95 percent confidence interval) from a random-effects meta-analysis. Meta-analysis estimates were calculated only if heterogeneity was low or medium (I2 0-60 percent) and if at least one trial found a positive sample. Superscript R indicates a median (and range) of trial prevalence estimates, calculated if heterogeneity was high (I2 >60 percent). Ranges not provided when only one trial was identified. c I2 is a measure of the degree of heterogeneity between trials combined in the meta-analysis. Heterogeneity rating definitions: low = I2 0–30 percent; medium = 31–60 percent; high = >60 percent. Selection bias rating definitions: high = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. Studies that conducted random or systematic sampling were considered representative. The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. Taking into consideration the number of studies in the meta-analysis, high confidence in the meta-analysis results can be inferred when heterogeneity is low and the risk of selection bias is low, and low confidence can be inferred when both are high; see the methods section for more information. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 128 TABLE A1.17 Forest plot of the prevalence of selected microbial hazards within dried protein product categories Microbial hazard/LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs. /trials/ studies Heterogeneity Selection bias Median (range) B. cereus Dried dairy products 35.0 14.9 57.9 632/7/7 High Med. 44.4 (0–60) Dried fish products 13.0 - - 100/1/1 N/A Low - Overall 31.5 14.2 51.7 High 38.9 (0–60) Cronobacter spp. Dried dairy products 4.5 3.0 6.2 2 714/29/17 Med. High - Gelatine 12.5 - - 8/1/1 N/A High - Overall 4.6 3.1 6.4 Med. - Generic E. coli Dried dairy products 1.0 - - 100/1/1 N/A Low - Gelatine 0.0 - - 8/1/1 N/A High - Overall 1.5 0.0 4.3 Low - L. monocytogenes Dried dairy products 0.0 - - 100/1/1 N/A Low - Dried fish products 1.0 - - 100/1/1 N/A Low - Overall 0.7 0.0 2.1 Low - Salmonella spp. Dried dairy products 0.0 0.0 0.0 4 505/7/6 Low Low - Dried fish products 5.6 0.0 38.5 105/2/2 High Med. 10 (0–20) Gelatine 0.0 0.0 0.0 565/6/5 Low Low - Overall 0.0 0.0 0.1 Low 0 (0–20) CI = confidence interval; Med = medium; No. obs. = number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: C. botulinum evidence not shown in this figure as only one trial was identified in this category. LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% ANNEX 1 129 TA B LE A 1. 18 S um m ar y ta bl e of e xp er im en ta l s tu di es e va lu at in g th e eff ec ts o f i nt er ve nt io ns t o re du ce c on ta m in at io n of s el ec te d m ic ro bi al h az ar ds in dr ie d pr ot ei n pr od uc ts Fo od ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or du ra ti on , w he re a va ila bl e) So ur ce (s ) M ic ro bi al ha za rd (s ) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io na D ri ed d ai ry C he m ic al a dd it iv es D ie th yl py ro ca rb on at e (0 .1 % ), po ta ss iu m s or ba te (5 0 0 p pm ), s od iu m be nz oa te (0 .2 % ), w he y (1 –1 0 % ; 0 –3 m on th s) (M cD on ou gh a nd H ar gr ov e, 19 68 ) S al m on el la s pp . 4 /1 0 0 H ea t tr ea tm en t H ot w at er (6 0 –1 0 0 °C ; 1 0 m in ) (O sa ili e t al ., 20 0 9) C ro n ob ac te r sp p. 3/ 1 10 0 10 0 H ea t tr ea tm en t D ry h ea t (1 10 °C ; 1 –5 m in ) D ry h ea t (6 0 –1 15 .5 °C ; 1 5 m in t o 10 h r) H ot a ir h ea te d th ou gh o il ba th (8 7. 7– 14 8. 8° C ; 3 –6 m in ) (L iC ar i a nd P ot te r, 19 70 a) ; ( M cD on ou gh an d H ar gr ov e, 19 68 ); (M cD on ou gh a nd H ar gr ov e, 19 68 ) S al m on el la s pp . 6/ 2 0 10 0 * M od ifi ed pa ck ag in g A ir (o xy ge n 0 .5 –2 0 % ) v s. v ac uu m (1 –2 7 w ee ks ) (C hr is ti an a nd St ew ar t, 19 73 ) S al m on el la s pp ., S . a ur eu s 2/ 1 0 10 0 O zo ne G as (2 .8 –5 .3 m g/ L; 3 0 –1 20 m in ) (T or la k an d Se rt , 20 13 ) C ro n ob ac te r sp p. 2/ 1 0 10 0 Sp ra y dr yi ng 16 5– 22 5° C (M ill er , G oe pf er t an d A m un ds on , 1 97 2) P at ho ge ni c E . co li (m ul ti pl e st ra in s) 1/ 1 0 10 0 Sp ra y dr yi ng 32 .2 –2 26 .7 °C ; 5 .3 –8 .8 k g/ cm 2 ; 3 s ec 16 5- 22 5° C (L iC ar i a nd P ot te r, 19 70 a) ; ( M ill er , G oe pf er t an d A m un ds on , 1 97 2) S al m on el la s pp . 8/ 2 0 10 0 * St or ag e co nd it io ns In cr ea se d te m p. (5 –3 7° C ; 1 –1 9 w ee ks ) (D en g, 19 98 ) E . c ol i O 15 7: H 7 3/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m p. (2 5– 55 °C ; 1 –8 w ee ks ) In cr ea se d te m p. (4 .4 –5 0 °C ; 1 –1 5 w ee ks ) In cr ea se d aw (0 .4 3– 0 .7 5; 2 d ay s– 14 w ee ks ) In cr ea se d aw (0 .1 1– 0 .5 3; 1– 27 w ee ks ) (L iC ar i a nd P ot te r, 19 70 b) ; ( M cD on ou gh an d H ar gr ov e, 19 68 ) (J uv en , C ox a nd B ai le y, 19 84 ); (C hr is ti an a nd St ew ar t, 19 73 ) S al m on el la s pp . 6/ 4 0 10 0 * (c on t. ) 0% 20% 40% 60% 80% 100% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 130 Fo od ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or du ra ti on , w he re a va ila bl e) So ur ce (s ) M ic ro bi al ha za rd (s ) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io na St or ag e co nd it io ns In cr ea se d aw (0 .1 1– 0 .5 3; 1– 27 w ee ks ) (C hr is ti an a nd St ew ar t, 19 73 ) S . a ur eu s 1/ 1 0 10 0 D ri ed e gg s H ea t tr ea tm en t D ry h ea t (5 4 –8 2° C ; 1 h r to 7 d ay s) D ry h ea t (5 0 –5 5° C ; 6 -2 4 h r) (J un g an d B ea uc ha t, 19 99 ); (N ém et h et a l., 20 11 ) S al m on el la s pp . 2/ 2 50 10 0 Sp ra y dr yi ng 22 5° C (M ill er , G oe pf er t an d A m un ds on , 1 97 2) S al m on el la s pp . 3/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m p. (1 3 an d 37 °C ) a nd A w (0 .3 0 –0 .3 7 vs . 0 .5 2– 0 .6 1; 1– 8 w ee ks ) (J un g an d B ea uc ha t, 19 99 ) S al m on el la s pp . 2/ 1 0 10 0 D ri ed fi sh C he m ic al a dd it iv es A ce ti c (0 .2 % ), b ut yr ic (0 .5 % ), fo rm ic (0 .5 % ), a nd p ro pi on ic (0 .5 % ) a ci ds (1 3– 82 d ay s) E th ox yq ui n (4 0 0 m g/ kg ; 1 0 –2 12 d ay s) Fi sh o il (8 % ) a nd o xi di ze d fis h oi l ( 10 % ; 10 –2 0 0 d ay s) St ea ri c ac id (1 0 % ; 2 0 –2 20 d ay s) Fr ee u ns at ur at ed fa tt y ac id s (1 0 % ; 10 –1 20 d ay s) (L am pr ec ht e t al ., 19 74 ) S al m on el la s pp . 13 /1 0 54 M od ifi ed pa ck ag in g O xy ge n vs . a ir a tm os ph er e (2 0 –3 0 °C ; 26 –2 0 7 da ys ) (L am pr ec ht e t al ., 19 74 ) S al m on el la s pp . 1/ 1 0 10 0 Sa lt in g an d dr yi ng Sa lt in g (3 0 –8 0 % ) a nd d ry in g (4 °C ; 1 –7 0 da ys ) (M ol e t al ., 20 10 ) S al m on el la s pp . 1/ 1 10 0 10 0 D ri ed m ea t po w de rs C he m ic al a dd it iv es So di um c hl or id e (0 .5 –2 0 % ; 1 –8 w ee ks ) (R yu , D en g an d B ea uc ha t, 19 99 ) E . c ol i O 15 7: H 7 1/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m p. (5 –7 °C ; 1 –1 9 w ee ks ) In cr ea se d te m p. (5 –2 5° C ; 1 –8 w ee ks ) In cr ea se d A w (0 .3 4 –0 .6 8; 1– 8 w ee ks ) (D en g, R yu a nd B ea uc ha t, 19 98 ); (R yu , D en g an d B ea uc ha t, 19 99 ); (R yu , D en g an d B ea uc ha t, 19 99 ) E . c ol i O 15 7: H 7 3/ 2 0 10 0 a I nt er ve nt io n ca te go ri es m ar ke d w it h an a st er is k (* ) in di ca te t ha t m or e tr ia ls f ou nd a s ta ti st ic al ly s ig ni fic an t re du ct io n in m ic ro bi al c on ce nt ra ti on o r pr ev al en ce t ha n w ou ld b e ex pe ct ed b y ch an ce a lo ne ( si gn t es t P v al ue < 0 .0 5) . Si gn ifi ca nc e on ly c al cu la te d if m or e th an o ne s tu dy w as c on du ct ed p er in te rv en ti on /m ic ro bi al h az ar d/ st ud y ty pe c om bi na ti on . ANNEX 1 131 A1.8.6 References in A1.8 References used in summary narrative: Carlin, F., Broussolle, V., Perelle, S., Litman, S. & Fach, P. 2004. Prevalence of Clostridium botulinum in food raw materials used in REPFEDs manufactured in France. International Journal of Food Microbiology, 91(2): 141–145. de la Rosa, M. C., Medina, M. R., & Vivar, C. 1995. Microbiological quality of pharmaceutical raw materials. Pharmaceutica Acta Helvetiae, 70(3): 227–232. Deeb, A. M. M., Al-Hawary, I. I., Aman, I. M. & Shahin, M. H. A. 2010. Bacteriological investigation on milk powder in the Egyptian market with emphasis on its safety. Global Veterinaria, 4(5): 424–433. EFSA & ECDC. 2010. The community summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in the European Union in 2008. EFSA Journal, 8: 1496. Jermini, M., Bryan, F. L., Schmitt, R., Mwandwe, C., Mwenya, J., Zyuulu, M. H. & Michael, M. 1997. Hazards and critical control points of food vending operations in a city in Zambia. Journal of Food Protection, 60(3): 288–299. Jacobs, C., Braun, P. & Hammer, P. 2011. Reservoir and routes of transmission of Enterobacter sakazakii (Cronobacter spp.) in a milk powder-producing plant. Journal of Dairy Science, 94(8): 3801–3810. Kim, M. J., Kim, S. A., Kang, Y. S., Hwang, I. G. & Rhee, M. S. 2013. Microbial diversity and prevalence of foodborne pathogens in cheap and junk foods consumed by primary schoolchildren. Letters in Applied Microbiology, 57(1): 47–53. LiCari, J. J. & Potter, N. N. 1970a. Salmonella survival during spray drying and subsequent handling of skimmilk powder. II. Effects of drying conditions. Journal of Dairy Science, 53(7): 871–876. Reyes, J. E., Bastias, J. M., Gutierrez, M. R. & Rodriguez Mde, L. 2007. Prevalence of Bacillus cereus in dried milk products used by Chilean school feeding program. Food Microbiology, 24(1): 1–6. Rodas-Suarez, O. R., Quinones-Ramirez, E. I., Fernandez, F. J. & Vazquez-Salinas, C. 2013. Listeria monocytogenes strains isolated from dry milk samples in Mexico: Occurrence and antibiotic sensitivity. Journal of Environmental Health, 76(2): 32– 37. Torlak, E. & Sert, D. 2013. Inactivation of Cronobacter by gaseous ozone in milk powders with different fat contents. International Dairy Journal, 32(2): 121–125. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 132 Citation list of burden of illness studies (n=12 unique citations): (Distiller ID = Ref #, Outbreak # =OB # where a Distiller ID is not available – for unpublished outbreaks) Anonymous. 2005. CFIA: Warning-Health Hazard Alert-JHC Brand Cooked Seasoning Anchovies May Contain Salmonella Bacteria. (also available at https://www. salmonellablog.com/salmonella-watch/jhc-brand-anchovies-may-contain- salmonella/) OB#85. Asao, T., Kumeda, Y., Kawai, T., Shibata, T., Oda, H., Haruki, K., Nakazawa, H. & Kozaki, S. 2003. An extensive outbreak of staphylococcal food poisoning due to low-fat milk in Japan: estimation of enterotoxin A in the incriminated milk and powdered skim milk. Epidemiology and Infection, 1(130): 33–40. Ref #: 6731. Collins, R. N., Treger, M. D., Goldsby, J. B., Boring, J. R. 3rd, Coohon, D. B. & Barr, R. N. 1968. Interstate outbreak of Salmonella newbrunswick infection traced to powdered milk. Journal of the American Medical Association, 10 (203): 838–844. Ref #: 4060. Clark, M. 2006. Foodborne Illness Outbreak Database. Ottawa County Jail Powdered Milk 2006. Foodborne Illness Outbreak Database [online]. [Cited 20 July 2021]. http://outbreakdatabase.com/details/ottawa-county-jail-powdered-milk-2006/. OB#=97. Doyle, P. 2007. Are Chinese Products Slowly Killing Us? [online]. [Cited 20 July 2021]. http://www.rense.com/general78/chinsl.htm. OB#75. Eriksen, T., Brantsaeter, A.B., Kiehl, W. & Steffens, I. 2004. Botulism infection after eating fish in Norway and Germany: two outbreak reports. Euro Surveillance, 8(3): 2366. OB#60. InVS, Outbreak Investigation Group. 2005. Outbreak of Salmonella Worthington infections in elderly people due to contaminated milk powder, France, January- July 2005. Euro Surveillance, 10 (29): 2753. Ref #: 5713. Ling, M. L., Goh, K. T., Wang, G. C., Neo, K. S. & Chua, T. 2002. An outbreak of multidrug-resistant Salmonella enterica subsp. enterica serotype Typhimurium, DT104L linked to dried anchovy in Singapore. Epidemiology and Infection, 128(1): 1–5. Ref #: 6726. Miyakawa, S., Takahashi, K., Hattori, M., Itoh, K., Kurazono, T. & Amano, F. 2006. Outbreak of Salmonella Oranienburg infection in Japan. Journal of Environmental Biology, 27(1): 157–158. Ref #: 5983. Peck, M. W. 2006. Clostridium botulinum and the safety of minimally heated, chilled foods: An emerging issue? Journal of Applied Microbiology, 101: 556–570. OB#66, 67,80. ANNEX 1 133 Weissman, J. B., Deen, A. D., Williams, M., Swanston, N. & Ali, S. 1977. An island- wide epidemic of salmonellosis in Trinidad traced to contaminated powdered milk. West Indian Medical Journal, 3(26): 135–143. Ref #: 388. Citation list of prevalence studies (N=39): (Distiller ID = Ref #) Aigbekaen, B. O. & Oshoma, C. E. 2010. Isolation of Enterobacter sakazakii from powdered foods locally consumed in Nigeria. Pakistan Journal of Nutrition, 9(7): 659–663. Ref #: 4816. Aljaloud, S. O., Ibrahim, S. A., Fraser, A. M., Song, T., & Shahbazi, A. 2013. Microbiological quality and safety of dietary supplements sold in Saudi Arabia. Emirates Journal of Food and Agriculture, 25(8): 593–596. Ref #: 4202. Baumgartner, A., Grand, M., Liniger, M. & Iversen, C. 2009. Detection and frequency of Cronobacter spp. (Enterobacter sakazakii) in different categories of ready-to-eat foods other than infant formula. International Journal of Food Microbiology, 136(2): 18–9192. Ref #: 1191. Bedi, S. K., Sharma, C. S., Gill, J. P. S., Aulakh, R. S. & Sharma, J. K. 2005. Incidence of enterotoxigenic Bacillus cereus in milk and milk products. Journal of Food Science and Technology, 42(3): 272–275. Ref #: 5737. Blanco, W., Arias, M. L., Perez, C., Rodriguez, C. & Chaves, C. 2009. Toxigenic Bacillus cereus detection in lactic products with spices and dehydrated milk collected in Costa Rica. Archivos Latinoamericanos De Nutricion, 59(4): 402–406. Ref #: 5016. Carlin, F., Broussolle, V., Perelle, S., Litman, S. & Fach, P. 2004. Prevalence of Clostridium botulinum in food raw materials used in REPFEDs manufactured in France. International Journal of Food Microbiology, 91(2): 141–145. Ref #: 2177. de la Rosa, M. C., Medina, M. R., & Vivar, C. 1995. Microbiological quality of pharmaceutical raw materials. Pharmaceutica Acta Helvetiae, 70(3): 227–232. Ref #: 3005. Deeb, A. M. M., Al-Hawary, I. I., Aman, I. M., & Shahin, M. H. A. 2010. Bacteriological investigation on milk powder in the Egyptian market with emphasis on its safety. Global Veterinaria, 4(5): 424–433. Ref #: 6770. EFSA & ECDC. 2010. The community summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in the European Union in 2008. EFSA Journal, 8: 1496. Ref #: 6637. EFSA & ECDC. 2011. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2009. EFSA Journal, 9(3): 2090. Ref #: 6636. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 134 EFSA & ECDC. 2012. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2010. EFSA Journal, 10(3): 2597. Ref #: 6757. EFSA & ECDC. 2013. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2011. EFSA Journal, 11(4): 3129. Ref #: 6756. Eglezos, S., Huang, B., Dykes, G. A. & Fegan, N. 2010. The prevalence and concentration of Bacillus cereus in retail food products in Brisbane, Australia. Foodborne Pathogens and Disease, 7(7): 867–870. Ref #: 981. El-Gamal, M., El Dairouty, R. K., Okda, A. Y., Salah, S. H. & El-Shamy, S. 2013. Incidence and interrelation of Cronobacter sakazakii and other foodborne bacteria in some milk products and infant formula milks in Cairo and Giza area. World Applied Sciences Journal, 26(9): 1129–1141. Ref #: 4106. El-Sharoud, W. M., El-Din, M. Z., Ziada, D. M., Ahmed, S. F. & Klena, J. D. 2008. Surveillance and genotyping of Enterobacter sakazakii suggest its potential transmission from milk powder into imitation recombined soft cheese. Journal of Applied Microbiology, 105(2): 559–566. Ref #: 1433. El-Sharoud, W. M., O’Brien, S., Negredo, C., Iversen, C., Fanning, S. & Healy, B. 2009. Characterization of Cronobacter recovered from dried milk and related products. BMC Microbiology, 9: 24-2180-9-24. Ref #: 6771. Ferraz, M. A., Cerqueira, M. M. O. P. & Souza, M. R. 2010. Evaluation of Enterobacteriaceae in the powdered milk production chain using both traditional (ISO 21528:2) and rapid (3M™ Petrifilm™) methods. Annals of Microbiology, 60(2): 373–376. Ref #: 4923. Gökmen, M., Tekinşen, K. K. & Gürbüz, Ü. 2010. Presence of Enterobacter sakazakii in milk powder, whey powder and white cheese produced in Konya. Kafkas Universitesi Veteriner Fakultesi Dergisi, 16: S163–S166. Ref #: 4876. Hassan, G. & Nabbut, N. 1996. Prevalence and characterization of Bacillus cereus isolates from clinical and natural sources. Journal of Food Protection, 59(2): 193–196. Ref #: 6273. Hein, I., Gadzov, B., Schoder, D., Foissy, H., Malorny, B. & Wagner, M. 2009. Temporal and spatial distribution of Cronobacter isolates in a milk powder processing plant determined by pulsed-field gel electrophoresis. Foodborne Pathogens and Disease, 6(2): 225–233. Ref #: 1231. Heuvelink, A. E., Ahmed, M., Kodde, F. D., Zwartkruis-Nahuis, J. T. M. & de Boer, E. 2002. Enterobacter sakazakii in melkpoeder. Project number OT 0110. Keuringsdienst Van Waren Oost. Ref #: 6772. ANNEX 1 135 Hochel, I., Ruzickova, H., Krasny, L. & Demnerova, K. 2012. Occurrence of Cronobacter spp. in retail foods. Journal of Applied Microbiology, 112(6): 1257–1265. Ref #: 463. Iversen, C. & Forsythe, S. 2004. Isolation of Enterobacter sakazakii and other Enterobacteriaceae from powdered infant formula milk and related products. Food Microbiology, 21(6): 771–777. Ref #: 6660. Jacobs, C., Braun, P. & Hammer, P. 2011. Reservoir and routes of transmission of Enterobacter sakazakii (Cronobacter spp.) in a milk powder-producing plant. Journal of Dairy Science, 94(8): 3801–3810. Ref #: 639. Jaradat, Z. W., Ababneh, Q. O., Saadoun, I. M., Samara, N. A. & Rashdan, A. M. 2009. Isolation of Cronobacter spp. (formerly Enterobacter sakazakii) from infant food, herbs and environmental samples and the subsequent identification and confirmation of the isolates using biochemical, chromogenic assays, PCR and 16S rRNA sequencing. BMC Microbiology, 9. Ref #: 1075. Jermini, M., Bryan, F. L., Schmitt, R., Mwandwe, C., Mwenya, J., Zyuulu, M. H. & Michael, M. 1997. Hazards and critical control points of food vending operations in a city in Zambia. Journal of Food Protection, 60(3): 288–299. Ref #: 6223. Kaclíková, E. & Turcovský, I. 2011. A method for the detection of Cronobacter strains in powdered milk-based foods using enrichment and real-time PCR. Journal of Food and Nutrition Research, 50(2): 118–124. Ref #: 4731. Kandhai, M. C., Heuvelink, A. E., Reij, M. W., Beumer, R. R., Dijk, R., van Tilburg, J. J. H. C. & Gorris, L. G. M. 2010. A study into the occurrence of Cronobacter spp. in the Netherlands between 2001 and 2005. Food Control, 21(8): 1127–1136. Ref #: 6664. Kim, M. J., Kim, S. A., Kang, Y. S., Hwang, I. G. & Rhee, M. S. 2013. Microbial diversity and prevalence of foodborne pathogens in cheap and junk foods consumed by primary schoolchildren. Letters in Applied Microbiology, 57(1): 47–53. Ref #: 168. Mozrova, V., Brenova, N., Mrazek, J., Lukesova, D. & Marounek, M. 2014. Surveillance and characterisation of Cronobacter spp. in Czech retail food and environmental samples. Folia Microbiologica, 59(1): 63–68. Ref #: 95. Mullane, N., Healy, B., Meade, J., Whyte, P., Wall, P. G. & Fanning, S. 2008. Dissemination of Cronobacter spp. (Enterobacter sakazakii) in a powdered milk protein manufacturing facility. Applied and Environmental Microbiology, 74(19): 5913–5917. Ref #: 1344. Ramalingam, C., Jain, H., Vatsa, K., Akhtar, N., Mitra, B., Vishnudas, D., Yadav, S., Garg, K., Prakash, A., & Rai, A. 2013. Detection and biochemical characterization of microorganisms in milk and cocoa powder samples by FTIR and subsequent production of bacteriocin from lactobacillus. International Journal of Drug Development and Research, 5(1): 310–320. Ref #: 4303. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 136 Reyes, J. E., Bastias, J. M., Gutierrez, M. R. & Rodriguez Mde, L. 2007. Prevalence of Bacillus cereus in dried milk products used by Chilean school feeding program. Food Microbiology, 24(1): 1–6. Ref #: 1751. Rodas-Suarez, O. R., Quinones-Ramirez, E. I., Fernandez, F. J. & Vazquez-Salinas, C. 2013. Listeria monocytogenes strains isolated from dry milk samples in Mexico: Occurrence and antibiotic sensitivity. Journal of Environmental Health, 76(2): 32– 37. Ref #: 48. Shaker, R., Osaili, T., Al-Omary, W., Jaradat, Z. & Al-Zuby, M. 2007. Isolation of Enterobacter sakazakii and other Enterobacter sp. from food and food production environments. Food Control, 18(10): 1241–1245. Ref #: 5421. Te Giffel, M. C., Beumer, R. R., Bonestroo, M. H. & Rombouts, P. M. 1996. Incidence and characterization of Bacillus cereus in two dairy processing plants. Netherlands Milk and Dairy Journal, 50(4): 479–492. Ref #: 6236. Turcovsky, I., Kunikova, K., Drahovska, H. & Kaclikova, E. 2011. Biochemical and molecular characterization of Cronobacter spp. (formerly Enterobacter sakazakii) isolated from foods. Antonie Van Leeuwenhoek, 99(2): 257–269. Ref #: 899. Wang, X., Meng, J., Zhang, J., Zhou, T., Zhang, Y., Yang, B. & Xia, X. 2012. Characterization of Staphylococcus aureus isolated from powdered infant formula milk and infant rice cereal in China. International Journal of Food Microbiology, 153(1–2): 142–147. Ref #: 6773. Yan, H., Neogi, S. B., Mo, Z., Guan, W., Shen, Z., Zhang, S., Li, L., Yamasaki, S., Shi, L. & Zhong, N. 2010. Prevalence and characterization of antimicrobial resistance of foodborne Listeria monocytogenes isolates in Hebei province of northern China, 2005-2007. International Journal of Food Microbiology, 144(2): 310–316. Ref #: 873. Citation list of interventions studies (N=14): (Distiller ID = Ref #) Christian, J. H. B. & Stewart, B. J. 1973. Survival of Staphylococcus aureus and Salmonella Newport in dried foods, as influenced by water activity and oxygen. In B. C. Hobbs and J. H. B. Christian, eds. The Microbiological Safety of Foods: Proceedings of the Eighth International Symposium on Food Microbiology, pp. 107- 119. Reading, England, September 1972. Ref #: 6774. Deng, Y., Ryu, J. H. & Beuchat, L. R. 1998. Influence of temperature and pH on survival of Escherichia coli O157:H7 in dry foods and growth in reconstituted infant rice cereal. International Journal of Food Microbiology, 45(3): 173–184. Ref #: 6628. ANNEX 1 137 Jung, Y. S. & Beuchat, L. R. 1999. Survival of multidrug-resistant Salmonella Typhimurium DT104 in egg powders as affected by water activity and temperature. International Journal of Food Microbiology, 49(1–2): 1–8. Ref #: 6112. Juven, B. J., Cox, N. A. & Bailey, J. S. 1984. Survival of Salmonella in dry food and feed. Journal of Food Protection, 47(6): 445–448. Ref #: 6775. Lamprecht, E. C. & Elliott, M. C. 1974. Death rate of Salmonella Oranienburg in fish meals as influenced by autoxidation treatment. Journal of the Science of Food and Agriculture, 25(10): 1329–1338. Ref #: 3978. LiCari, J. J. & Potter, N. N. 1970a. Salmonella survival during spray drying and subsequent handling of skimmilk powder. II. Effects of drying conditions. Journal of Dairy Science, 53(7): 871–876. Ref #: 6776. LiCari, J. J. & Potter, N. N. 1970b. Salmonella survival during spray drying and subsequent handling of skimmilk powder. III. Effects of storage temperature on salmonella and dried milk properties. Journal of Dairy Science, 53(7): 877–882. Ref #: 6673. McDonough, F. E. & Hargrove, R. E. 1968. Heat resistance of Salmonella in dried milk. Journal of Dairy Science, 51(10): 158–71591. Ref #: 6678. Miller, D. L., Goepfert, J. M. & Amundson, C. H. 1972. Survival of Salmonellae and Escherichia coli during the spray drying of various food products. Journal of Food Science, 37(6): 828–831. Ref #: 6680. Mol, S., Cosansu, S., Ucok Alakavuk, D. & Ozturan, S. 2010. Survival of Salmonella Enteritidis during salting and drying of horse mackerel (trachurus trachurus) fillets. International Journal of Food Microbiology, 139(1–2): 36–40. Ref # 6681. Németh, C., Dalmadi, I., Mráz, B., Friedrich, L., Pásztor-Huszár, K., Suhajda, A., Janzsó, B. & Balla, C. 2011. Study of long term post-treatment of whole egg powder at 50-55°C. Polish Journal of Food and Nutrition Sciences, 61(4): 239–243. Ref #: 4667. Osaili, T. M., Shaker, R. R., Al-Haddaq, M. S., Al-Nabulsi, A. A. & Holley, R. A. 2009. Heat resistance of Cronobacter species (Enterobacter sakazakii) in milk and special feeding formula. Journal of Applied Microbiology, 107(3): 928–935. Ref #: 1218. Ryu, J. H., Deng, Y. & Beuchat, L. R. 1999. Survival of Escherichia coli O157:H7 in dried beef powder as affected by water activity, sodium chloride content and temperature. Food Microbiology, 16(3): 309–316. Ref #: 6694. Torlak, E. & Sert, D. 2013. Inactivation of Cronobacter by gaseous ozone in milk powders with different fat contents. International Dairy Journal, 32(2): 121–125. Ref #: 4162. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 138 A1.9 SUMMARY CARD: HONEY AND PRESERVES A1.9.1 Low-moisture food category description This summary primarily covers honey, a natural sweet produced by honeybees from the nectar of plants (FAO, 2002). It also includes syrups (e.g. corn and table) and preserves (e.g. jam). A1.9.2 Evidence summary In total, 57 articles12 and outbreak reports13 were identified that investigated the burden of illness, the prevalence or concentration of selected microbial hazards, and interventions to reduce contamination of microbial hazards in honey and preserves. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in Appendix F: Summary Card Evidence Charts. C. botulinum was the most frequently investigated microbial hazard in honey and preserves for burden of illness (n=27 outbreak reports and articles), prevalence (n=21 articles), and intervention (n=1 article) information. A1.9.3 Burden of illness Burden of illness evidence includes one outbreak, two case control studies and 25 case reports or case series reported between 1976 and 2013. S. aureus was implicated in one outbreak involving a maple-bacon jam. C. botulinum was associated with honey in all case reports and the two case control studies on infant botulism (Midura, 1979; Spika et al., 1989). Honey was the only food that tested positive for C. botulinum in all but one case report; Saraiva et al. (2012) reported chamomile fed to the infant also tested positive for C. botulinum B toxins. In some studies soil and vacuum cleaner dust from case households also tested positive. Globally, recommendations not to feed honey to infants less than 12 months old have been adopted since the late 1970’s. 12 Articles refer to peer-reviewed journal publications as well as government and research agency reports. 13 For burden of illness information, multiple articles often reported complementary and/or overlapping information on the same outbreak. In addition, outbreak data were supplemented from other literature sources, including line lists from various countries, news reports, or annual summaries of country outbreaks. Thus, to avoid counting the same outbreak more than once, the term “outbreak report” is used instead of “article” to count the total number of unique outbreaks. ANNEX 1 139 TA B LE A 1. 19 S um m ar y ta bl e of g lo ba lly re po rt ed c as e re po rt s an d ou tb re ak s on h on ey a nd p re se rv es P re se rv e or h on ey c at eg or y/ s pe ci fic so ur ce (r ef er en ce ) M ic ro bi al ha za rd (s ) O ut br ea ks / ca se s/ ho sp it al iz ed / de at hs a Co un tr y (y ea r) b Co m m en ts : s us ce pt ib le p op ul at io ns / at ta ck r at e/ co nc en tr at io n of m ic ro bi al h az ar d in th e pr od uc t M ap le -b ac on J am (G io va ni , 2 0 13 ) S . a ur eu s 1/ 79 C , 1 4 4 P/ 5/ 0 C an ad a (2 0 13 ) Te m pe ra tu re a bu se w as s us pe ct ed . Se rv ed b y a fa ir fo od v en do r. H on ey (A bd ul la e t al ., 20 12 ); (A no n. , 20 0 9) ; ( A rr ia ga da , W ilh el m a nd D on os o, 2 0 0 9) ; ( B al sl ev e t al ., 19 97 ); (C en to rb i e t al ., 19 99 ); (F en ic ia e t al ., 19 93 ); (H oa ra u et a l., 2 0 12 ); (J un g an d O tt os so n, 2 0 0 1) ; ( K in g et a l., 20 10 ); (K ot ha re a nd K as sn er , 1 99 5) ; (M ue lle r- B un ke e t al ., 20 0 0 ); (N ab ey a et a l., 19 89 ); (N od a et a l., 19 88 ); (P ui g de C en to rb i e t al ., 19 98 ); (R am ro op et a l., 2 0 12 ); (S ar ai va e t al ., 20 12 ); (S m it h et a l., 2 0 10 ); ( Th om as se e t al ., 20 0 5) ; ( To rr es T or to sa e t al ., 19 86 ); (T oy og uc hi e t al ., 19 91 ); ( va n de r V or st et a l., 2 0 0 6) ; ( W ol te rs , 2 0 0 0 ); (Y an ay et a l., 2 0 0 4 ); (M ar le r, 2 0 14 ) C . b ot ul in um 25 /1 7C ,2 2P /3 9/ 1 Ja pa n (1 98 6, 19 89 ), It al y (1 99 1) , U ni te d St at es o f A m er ic a (1 99 4 E ), A rg en ti na (1 99 5E , 1 99 9) , D en m ar k (1 99 6, 2 0 0 0 ), N or w ay (1 99 8E ), t he N et he rl an ds (2 0 0 0 E 2 0 0 4 E ), A ra bi an G ul f ( 20 0 5) , F ra nc e (2 0 0 9E ), C hi le (2 0 0 8E ), U ni te d K in gd om o f G re at B ri ta in a nd N or th er n Ir el an d (2 0 0 9, 2 0 10 , 2 0 12 , 20 13 E ), Is ra el (2 0 0 4 E ), G er m an y (2 0 0 0 E ), P or tu ga l (2 0 12 ) A ll w er e in fa nt b ot ul is m c as e re po rt s of in fa nt s <1 2 m on th s. 10 0 % w er e ho sp it al iz ed c as es w it h ho sp it al iz at io ns la st in g 3 da ys t o 7. 5 m on th s. A ll ca se s w er e co nfi rm ed t o be C . b ot ul in um t yp e A o r B . a S up er sc ri pt C in di ca te s co nfi rm ed c as es ; p in di ca te s pr es um pt iv e ca se s. b S up er sc ri pt E in di ca te s th e lin k be tw ee n hu m an c as es a nd im pl ic at ed p ro du ct w as e pi de m io lo gi ca l o nl y; o th er w is e, t he li nk w as la bo ra to ry c on fir m ed . RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 140 A1.9.4 Prevalence A total of 29 studies containing 47 unique trials were identified that investigated the prevalence and/or concentration of one or more selected microbial hazards in honey and preserves. The median publication year was 2003 (range 1990–2013). Most studies were conducted in either Brazil or Argentina (38 percent) > Asia/the Middle East (28 percent) > Europe (28 percent) > the United States of America (3.5 percent) and South Africa (3.5 percent). Nearly all studies (97 percent) sampled products during a specific or defined period, while one conducted sampling over multiple time points. Most studies sampled products from apiaries (38 percent) and/or at retail stores and markets (38 percent). Most studies (69 percent) specified the country(s) of product origin. C. botulinum was the most investigated microbial hazard in honey and preserves. In honey, it was found at a low median prevalence of 3.4 percent (95 percent CI 0 to 24 percent). The highest prevalence (24 percent) was found in honey extracted from honeycombs in apiaries in Finland (Nevas et al., 2006). C. botulinum was found at a very low median prevalence of 0.2 percent (95 percent CI 0 to 0.7 percent) in corn and other syrups in two studies; only 1/16 samples of corn syrup from one study in Japan were positive (Nakano et al., 1992). B. cereus was identified in honey at highly variable prevalence levels, ranging from 23 to 78 percent. C. perfringens was identified at a low prevalence in honey in one study: from 7/116 samples in France (Delmas, Vidon and Sebald, 1994). Cronobacter spp., generic E. coli, E. coli O157:H7, L. monocytogenes, S. aureus and Salmonella spp. were not identified in any study. No prevalence studies were identified for preserves (e.g. jams). Few studies reported extractable concentration data on levels of selected microbial hazards in honey (not shown in the table below). Average concentrations of C. botulinum in positive honey samples ranged with 36 to 60 spores/g in two studies (De Centorbi et al., 1997; Nakano and Sakaguchi, 1991) and were 38 spores/kg in a study from Finland (Nevas et al., 2002). In a study that found three positive samples in Argentina, two samples contained <1 000 spores/kg, while one contained 15 000/kg and was associated with a case of infant botulism (Monetto et al., 1999). B. cereus concentrations in honey ranged from 100 to 10 000 spores/kg in two studies (Monetto et al., 1999; Piana et al., 1991). ANNEX 1 141 TABLE A1.20 Prevalence of selected microbial hazards in honey and preserves (Each cell includes the number of observations/trials/studies contributing to the average or median prevalence estimate, the proportion of trials that did not find any positive samples and measures of heterogeneity and risk of selection bias. See the table footnotes for detailed explanations on each of these parameters.) Honey and preserves Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Honey Syrups B. cereus 698/6/6 (0%) 33.2 (22.9–77.8)R High/High N/A C. botulinum 2197/20/19 (20%) 3.4 (0–23.9)R High/Med. 741/4/2 (75%) 0.2 (0–0.7)M Med./Low C. perfringens 166/2/2 (50%) 3.0 (0–6.0)R High/Med. N/A Cronobacter spp. 30/1/1 (100%) 0 N/A/High N/A Generic E. coli 71/2/2 (100%) 0 (0–0)R Low/High N/A E. coli O157:H7 30/1/1 (100%) 0 N/A/High N/A L. monocytogenes 30/1/1 (100%) 0 N/A/High N/A S. aureus 30/1/1 (100%) 0 N/A/High N/A Salmonella spp. 604/9/9 (100%) 0 (0–0)R Low/High N/A N/A = No data identified for this product-hazard combination. Med. = medium. a Observations/trials/studies: The observations are the total number of samples for all studies included in the summarized category. The number of studies is the number of articles captured. In some cases, articles report data on multiple prevalence trials or sampling frames. While the observations for each trial are independent by time and sample, they are part of a larger study where the methods and investigators are the same. Thus, there is not full independence in these observations, and we note this by acknowledging there are multiple trials within a study. b Superscript M indicates an average prevalence estimate (and 95 percent confidence interval) from a random-effects meta-analysis. Meta-analysis estimates were calculated only if heterogeneity was low or medium (I2 0–60 percent) and if at least one trial found a positive sample. Superscript R indicates a median (and range) of trial prevalence estimates, calculated If heterogeneity was high (I2 >60 percent). Ranges not provided when only one trial was identified. c I2 is a measure of the degree of heterogeneity between trials combined in the meta-analysis. Heterogeneity rating definitions: low = I2 0–30 percent; medium = 31–60 percent; high = >60 percent. Selection bias rating definitions: high = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. Studies that conducted random or systematic sampling were considered representative. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 142 The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. Taking into consideration the number of studies in the meta-analysis, high confidence in the meta-analysis results can be inferred when heterogeneity is low and the risk of selection bias is low, and low confidence can be inferred when both are high; see the methods section for more information. TABLE A1.21 Forest plot of the prevalence of selected microbial hazards in honey and preserves Microbial hazard/LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs. /trials/ studies Heterogeneity Selection bias Median (range) B. cereus Overall 38.9 24.1 54.7 689/6/6 High High 33.2 (22.9–77.8) C. botulinum Honey 5.5 3.1 8.4 2 197/20/19 High Med. 3.4 (0–23.9) Syrups 0.2 0.0 0.7 741/4/2 Med. Low - Overall 4.2 2.0 7.1 High 2.9 (0–23.9) C. perfringens Overall 2.9 0.0 10.6 166/2/2 High Med. 3.0 (0–6.0) CI = confidence interval; Med = medium; No. obs. =number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: E. coli, L. monocytogenes, S. aureus and Salmonella spp. evidence not shown in this figure because no positive samples were identified in these categories. B. cereus and C. perfringens evidence is based on data from only the honey subcategory. LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% ANNEX 1 143 A1.9.5 Interventions Only one experimental study (consisting of one unique trial) was identified evaluating the effects of interventions to reduce contamination of microbial hazards in honey. The study investigated the effect of gamma irradiation (6–25 kGy; 125 Gy/min) to reduce contamination of C. botulinum spores in honey (Postmes, van den Bogaard and Hazen, 1995). The authors found that a large dose (25kGy) was needed to effectively sterilize the honey, which could affect the honey’s sensory quality (Postmes, van den Bogaard and Hazen, 1995). The study was conducted in the Netherlands, was a challenge trial with artificially inoculated samples, was conducted under laboratory and non-commercial conditions, did not include extractable data, and included only six samples per intervention combination. A1.9.6 References References used in summary narrative: Delmas, C., Vidon, D. J. & Sebald, M. 1994. Survey of honey for Clostridium botulinum spores in eastern France. Food Microbiology, 11(6): 515–518. Ref #: 6763. De Centorbi, O. P., Satorres, S. E., Alcaraz, L. E., Centorbi, H. J. & Fernandez, R. 1997. Detection of Clostridium botulinum spores in honey. Revista Argentina De Microbiologia, 29(3): 147–151. FAO. 2002. Non-wood forest products from temperate broad-leaved trees. In: Food and Agriculture Organization of the United Nations [online]. Rome. [Cited 20 July 2021]. http://www.fao.org/3/y4351e/y4351e00.htm#Contents Midura, T. F. 1979. Laboratory aspects of infant botulism in California. Reviews of Infectious Diseases, 1(4): 652–655. Monetto, A. M., Francavilla, A., Rondini, A., Manca, L., Siravegna, M. & Fernandez, R. 1999. A study of botulinum spores in honey. Anaerobe, 5(3-4): 185–186. Nakano, H. & Sakagucki, G. 1991. An unusually heavy contamination of honey products by Clostridium botulinum type F and Bacillus alvei. FEMS Microbiology Letters, 79(2–3): 171–177. Nakano, H., Yoshikuni, Y., Hashimoto, H. & Sakaguchi, G. 1992. Detection of Clostridium botulinum in natural sweetening. International Journal of Food Microbiology, 16(2): 117–121. Nevas, M., Hielm, S., Lindstrom, M., Horn, H., Koivulehto, K. & Korkeala, H. 2002. High prevalence of Clostridium botulinum types A and B in honey samples detected by polymerase chain reaction. International Journal of Food Microbiology, 72(1–2): 45–52. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 144 Nevas, M., Lindstrom, M., Horman, A., Keto-Timonen, R. & Korkeala, H. 2006. Contamination routes of Clostridium botulinum in the honey production. Environmental Microbiology, 8(6), 1085-1094. Piana, M. L., Poda, G., Cesaroni, D., Chetti, L., Bucci, M. A. & Gotti, P. 1991. Research on microbial characteristics of honey samples of Udine province. Rivista Della Societa Italiana Di Scienza Dell’Alimentazione, 20(5): 293–301. Postmes, T., van den Bogaard, A. E. & Hazen, M. 1995. The sterilization of honey with cobalt 60 gamma radiation: a study of honey spiked with spores of Clostridium botulinum and Bacillus subtilis. Experientia, 51: 986–989. Saraiva, M., Campos Cunha, I., Costa Bonito, C., Pena, C., Toscano, M. M., Teixeira Lopes, T., Sousa, I. & Calhau, M. A. 2012 First case of infant botulism in Portugal. Food Control 26: 79–80. Spika, J.S., Shaffer, N., Hargrett-Bean, N., Collin, S., MacDonald, N. & Blake, P. 1989. Risk factors for infant botulism in the United States. American Journal of Disease of Children, 143: 828–832. Citation list of burden of illness studies (n=28 unique citations): (Distiller ID = Ref #, Outbreak # =OB # where a Distiller ID is not available – for unpublished outbreaks) Abdulla, C. O., Ayubi, A., Zulfiquer, F., Santhanam, G., Ahmed, M. A. S. & Deeb, J. 2012. Infant botulism following honey ingestion. BMJ Case Reports, 2012(sep05 2): bcr1120115153–bcr1120115153 [online]. [Cited 20 July 2021]. https://casereports. bmj.com/lookup/doi/10.1136/bcr.11.2011.5153 Anonymous. 2009. Two cases of infant botulism associated with consumption of honey. In: Health Protection Agency [online]. London, UK. OB#122. Arriagada, S. D, Wilhelm, B. J. & Donoso, F. A. 2009. Infant botulism: case report and review. Revista Chilena de Infectología, 26(2): 162–167. Ref #: 1131 Balslev, T., Ostergaard, E., Madsen, I. K. & Wandall, D. A. 1997. Infant botulism. The first culture-confirmed Danish case. Neuropediatrics, 28(5): 287–288. Ref #: 2830. Centorbi, H. J., Aliendro, O. E., Demo, N. O., Dutto, R., Fernandez, R. & De Centorbi, O. N. P. 1999. First case of infant botulism associated with honey feeding in Argentina. Anaerobe, 5(3-4): 181–183. Ref #: 6075. Fenicia, L., Ferrini, A. M., Aureli, P, & Pocecco, M. 1993. A case of infant botulism associated with honey feeding in Italy. European Journal of Epidemiology, 9(6): 671–673. Ref #: 3133. ANNEX 1 145 Govani, R. 2013. Update on investigation into CNE food-borne illness. In: Toronto Public Health Alert [online]. Toronto, Canada. Hoarau, G., Pelloux, I., Gayot, A., Wroblewski, I., Popoff, M. R., Mazuet, C., Maurin, M. & Croize, J. 2012. Two cases of type A infant botulism in Grenoble, France: no honey for infants. European Journal of Pediatrics, 171(3): 589–591. Ref #: 546. Jung, A. & Ottosson, J. 2001. Infantile botulism caused by honey. Ugeskr Laeger, 163(2): 169. Ref #: 2516. King, L.A., Popoff, M.R., Mazuet, C., Espié, E., Vaillant, V. & de Valk, H. 2010. Infant botulism in France, 1991–2009 [Le botulisme infantile en France, 1991-2009]. Archives of Pediatrics, 17(9): 1288–1292. Ref #: 4885. Kothare, S. V. & Kassner, E. G. 1995. Infant botulism: a rare cause of colonic ileus. Pediatrics Radiology, 25(1): 24–27. Ref #: 3044. Marler, B. 2014. Honey and botulism – baby risk [online]. [Cited 20 July 2021]. http:// www.botulismblog.com/botulism-watch/honey-and-botulism-baby-risk/#. U6m4y3ZKPSg OB# o303. Mueller-Bunke, H., Höck, A., Schöntube, M., & Noack, R. 2000. Botulism in infants [Sauglingsbotulismu]. Monatsschrift Fur Kinderheilkunde, 148(3): 242–245. Ref #: 6084. Midura, T. F. 1979. Laboratory aspects of infant botulism in California. Review of Infectious Diseases, 1(4): 652–655. Ref #: 3836. Nabeya, T., Yano, R., Saito, T., Inoue, H., Shinohara, N., Yokoyama, T., Nagai, S., Nishibayashi, Y. & Sakaguchi, G. 1989. Infant botulism was confirmed in Ehime Prefecture. Kansenshogaku Zasshi, 63(3): 268–272. Ref #: 3437. Noda, H., Sugita, K., Koike, A., Nasu, T., Takahashi, M., Shimizu, T., Ooi, K., & Sakaguchi, G. 1988. Infant botulism in Asia. American Journal of Diseases of Children, 142(2): 125–126. Ref #: 3500. Puig de Centorbi, O., Centorbi, H. J., Demo, N., Pujales, G. & Fernandez, R. 1998. Infant botulism during a one year period in San Luis, Argentina. Zentralbl fur Bakteriologie, 287(1–2): 61–66. Ref #: 2813. Ramroop, S., Williams, B., Vora, S. & Moshal, K. 2012. Infant botulism and botulism immune globulin in the UK: A case series of four infants. Archives of Diseases of Children, 97(5): 459–460. Ref #: 4515. Saraiva, M., Campos Cunha, I., Costa Bonito, C., Pena, C., Toscano, M. M., Teixeira Lopes, T., Sousa, I. & Calhau, M. A. 2012. First case of infant botulism in Portugal. Food Control 26: 79–80. Ref #: 4476. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 146 Smith, J. K., Burns, S., Cunningham, S., Freeman, J., McLellan, A. & McWilliam, K. 2010. The hazards of honey: infantile botulism. BMJ Case Reports, 2010(sep23 1): bcr0520103038–bcr0520103038 [online]. [Cited 20 July 2021]. https://casereports. bmj.com/content/2010/bcr.05.2010.3038. Ref #: 1036. Spika, J.S., Shaffer, N., Hargrett-Bean, N., Collin, S., MacDonald, N. & Blake, P. 1989. Risk factors for infant botulism in the United States. American Journal of Diseases of Children, 143: 828–832. Ref #: 6748. Thomasse, Y., Arends, J. P., van der Heide, P. A., Smit, L. M., van Weerden, T. W. & Fock, J. M. 2005. Three infants with constipation and muscular weakness: infantile botulism. Nederlands Tijdschrift Voor Geneeskunde, 149(15): 826–831. Ref #: 1998. Tollofsrud, P. A., Kvittingen, E. A., Granum, P. E. & Vollo, A. 1998. Botulism in newborn infants. Tidsskrift For Den Norske Lægeforening, 118(28): 4355–4356. Ref #: 2739. Torres Tortosa, P., Martinez Villalta, E., Rodriguez Caamano, J., Lorca Cano, C., Puche Mira, A. & Borrajo, E. 1986. Botulism in the infant. Presentation of a case. An Esp Pediatr, 24(3): 193–196. Ref #: 3578. Toyoguchi, S., Tsugu, H., Nariai, A., Kaburagi, Y., Asahina, Y., Ambo, K. & Katou, K. 1991. Infant botulism with Down syndrome. Acta Paediatrica Japonica, 33(3): 394–397. Ref #: 3308. van der Vorst, M. M., Jamal, W., Rotimi, V. O. & Moosa, A. 2006. Infant botulism due to consumption of contaminated commercially prepared honey. First report from the Arabian Gulf States. Medical Principles and Practice, 15(6): 456–458. Ref #: 1728. Wolters, B. 2000. First case of infant botulism in the Netherlands. Euro Surveillance, 4(49): 1478. OB#42. Yanay, O., Lerman-Sagie, T., Gilad, E., Nissenkorn, A., Jaferi, J., Watemberg, N. & Houri, S. 2004. Infant botulism in Israel: Knowledge enables prompt diagnosis. Israel Medical Association Journal, 6(4): 249–250. Ref #:5828. Citation list of prevalence studies (N=29): (Distiller ID = Ref #) Cabedo, L., Picart i Barrot, L. & Teixido i Canelles, A. 2008. Prevalence of Listeria monocytogenes and Salmonella in ready-to-eat food in Catalonia, Spain. Journal of Food Protection, 71(4): 855–859. Ref #: 6616. De Centorbi, O. P., Alcaraz, L. E. & Centorbi, H. J. 1994. Bacteriologic analysis and detection of Clostridium botulinum spores in honey. Revista Argentina De Microbiologia, 26(2): 96–100. Ref #: 3097. ANNEX 1 147 De Centorbi, O. P., Satorres, S. E., Alcaraz, L. E., Centorbi, H. J. & Fernandez, R. 1997. Detection of Clostridium botulinum spores in honey. Revista Argentina De Microbiologia, 29(3): 147–151. Ref #: 2857. De Jong L. I. T., Fernández, R. A., Blanco, M. I., Lúquez, C. & Ciccarelli, A. S. 2003. Transmisión del botulismo del lactante. Pren. Med. Argent., 90: 188–194. Ref #: 5874. Delmas, C., Vidon, D. J. & Sebald, M. 1994. Survey of honey for Clostridium botulinum spores in eastern France. Food Microbiology, 11(6): 515–518. Ref #: 6763. Du, S. J., Cheng, C. M., Lai, H. Y. & Chen, L. H. 1991. Combined methods of dialysis, cooked meat medium enrichment and laboratory animal toxicity for screening Clostridium botulinum spores in honey and infant food. Zhonghua Minguo Wei Sheng Wu Ji Mian Yi Xue Za Zhi, 24(2): 240–247. Ref #: 6764. Gallez, L. M. & Fernandez, L. A. 2009. Honeys from the ventania mountain range: Microbiological quality evaluation at different points of the honey-processing plant. [Mieles del sistema serrano de Ventania: evaluacion de la calidad microbiologica dentro del circuito de la planta de extraccion]. Revista Argentina De Microbiologia, 41(3): 163–167. Ref #: 1086. Iurlina, M. O. & Fritz, R. 2005. Characterization of microorganisms in Argentinean honeys from different sources. International Journal of Food Microbiology, 105(3): 297–304. Ref #: 5662. Iurlina, M. O., Saiz, A. I., Fuselli, S. R. & Fritz, R. 2006. Prevalence of Bacillus spp. in different food products collected in Argentina. LWT - Food Science and Technology, 39(2): 105–110. Ref #: 5637. Kim, S. A., Oh, S. W., Lee, Y. M., Imm, J. Y., Hwang, I. G., Kang, D. H. & Rhee, M. S. 2011. Microbial contamination of food products consumed by infants and babies in Korea. Letters in Applied Microbiology, 53(5): 532–538. Ref #: 619. Koluman, A., Melikoğlu Gölcü, B., Derin, O., Özkök, S. & Anniballi, F. 2013. Clostridium botulinum in honey: Prevalence and antibiotic susceptibility of isolated strains. Turkish Journal of Veterinary and Animal Sciences, 37(6): 706–711. Ref #: 4120. Küplülü, Ö., Göncüoğlu, M., Özdemir, H. & Koluman, A. 2006. Incidence of Clostridium botulinum spores in honey in Turkey. Food Control, 17(3): 222–224. Ref #: 6766. Lilly, T. J., Rhodehamel, E. J., Kautter, D. A. & Solmon, H. M. 1991. Clostridium botulinum spores in corn syrup and other syrups. Journal of Food Protection, 54: 585–587. Ref #: 6747. López, A. C. & Alippi, A. M. 2007. Phenotypic and genotypic diversity of Bacillus cereus isolates recovered from honey. International Journal of Food Microbiology, 117(2): 175–184. Ref #: 1625. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 148 Mäde, D., Trümper, K. & Stark, R. 2000. Nachweis von Clostridium botulinum in honig durch polymerase-kettenreaktion. Archiv Fur Lebensmittelhygiene, 51(3): 68–70. Ref #: 6057. Monetto, A. M., Francavilla, A., Rondini, A., Manca, L., Siravegna, M. & Fernandez, R. 1999. A study of botulinum spores in honey. Anaerobe, 5(3–4): 185–186. Ref #: 6076. Nakano, H., Okabe, T., Hashimoto, H. & Sakaguchi, G. 1990. Incidence of Clostridium botulinum in honey of various origins. Japanese Journal of Medical Science & Biology, 43(5): 183–195. Ref #: 3349. Nakano, H. & Sakagucki, G. 1991. An unusually heavy contamination of honey products by Clostridium botulinum type F and Bacillus alvei. FEMS Microbiology Letters, 79(2–3): 171177. Ref #: 3312. Nakano, H., Yoshikuni, Y., Hashimoto, H. & Sakaguchi, G. 1992. Detection of Clostridium botulinum in natural sweetening. International Journal of Food Microbiology, 16(2): 117–121. Ref #: 3234. Nevas, M., Hielm, S., Lindstrom, M., Horn, H., Koivulehto, K. & Korkeala, H. 2002. High prevalence of Clostridium botulinum types A and B in honey samples detected by polymerase chain reaction. International Journal of Food Microbiology, 72(1–2): 45–52. Ref #: 2447. Nevas, M., Lindstrom, M., Hautamaki, K., Puoskari, S. & Korkeala, H. 2005. Prevalence and diversity of Clostridium botulinum types A, B, E and F in honey produced in the Nordic countries. International Journal of Food Microbiology, 105(2): 145–151. Ref #: 1949. Nevas, M., Lindstrom, M., Horman, A., Keto-Timonen, R. & Korkeala, H. 2006. Contamination routes of Clostridium botulinum in the honey production environment. Environmental Microbiology, 8(6): 1085–1094. Ref #: 1820. Piana, M. L., Poda, G., Cesaroni, D., Chetti, L., Bucci, M. A. & Gotti, P. 1991. Research on microbial characteristics of honey samples of Udine province. Rivista Della Societa Italiana Di Scienza Dell’Alimentazione, 20(5): 293–301. Ref #: 6767. Pota, T. & Aruna, K. 2013. Microbiological analysis, biochemical composition and antibacterial activity of crude honey against multiple drug resistant uropathogens. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 4(3): 434– 444. Ref #: 4229. Rall, V. L., Bombo, A. J., Lopes, T. F., Carvalho, L. R. & Silva, M. G. 2003. Honey consumption in the state of Sao Paulo: A risk to human health? Anaerobe, 9(6): 299–303. Ref #: 6768. Różańska, H. 2011. Microbiological quality of Polish honey. Bulletin of the Veterinary Institute in Pulawy, 55(3): 443–445. Ref #: 4596. ANNEX 1 149 Schocken-Iturrino, R., Carneiro, M. C., Kato, E., Sorbara, J. O. B., Rossi, O. D. & Gerbasi, L. E. R. 1999. Study of the presence of the spores of Clostridium botulinum in honey in Brazil. FEMS Immunology and Medical Microbiology, 24(3): 379–382. Ref #: 6116. Tabera, A. E., Libonatti, C. C. & Díaz, M. 2002. Relevamiento de muestras de mieles procedentes de la zona de tandil. Boletín Apícola, 20: 13–17. Ref #: 6769. Tandlich, R., Smogrovicova, D., Frith, K. -., Wilhelmi, B. S. & Limson, J. L. 2011. “Chemical, microbial and antioxidant properties of selected honey varieties from South Africa.” Paper presented at the 6th Baltic Conference on Food Science and Technology, 5–6 May 2011, Jelgava, Latvia. Ref #: 4628. Citation list of interventions studies (N=1): (Distiller ID = Ref #) Postmes, T., van den Bogaard, A. E. & Hazen, M. 1995. The sterilization of honey with cobalt 60 gamma radiation: a study of honey spiked with spores of Clostridium botulinum and Bacillus subtilis. Experientia, 51: 986–989. Ref #: 3001. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 150 A1.10 SUMMARY CARD: NUTS AND NUT PRODUCTS A1.10.1 Low-moisture food category description This summary covers edible nuts and nut products, which are defined as the dried, hard-shelled fruits, kernels or seeds of trees, shrubs or other plants (FAO, 1995). We define two major categories of nuts in this summary: (1) tree nuts and (2) peanuts. Peanuts, or groundnuts (Arachis hypogaea), refer to the edible seeds of a plant in the legume family (FAO, 1995). Tree nuts refer to all other nuts included in this summary, including true nuts in the botanical sense (e.g. hazelnuts/filberts) and other dried, hard-shelled fruits and seeds commonly referred to as culinary nuts (e.g. almonds, Brazil nuts, cashews, pecans, pistachios, pine nuts and walnuts). For the purposes of conducting meta-analysis of prevalence estimates, data were collapsed across four nut categories: (1) almonds; (2) other tree nuts (consisting of Brazil nuts, cashews, hazelnuts, macadamia nuts, pecans, pine nuts, pistachios and walnuts); (3) peanuts; and (4) mixed/unspecified nuts. For the interventions summary, these categories were further collapsed into (1) all tree nuts (including almonds) and (2) peanut butters/spreads. The difference in peanut categories is because no prevalence studies were identified that investigated peanut butters/ spreads, while intervention studies in peanut products only investigated the latter, and none evaluated raw peanuts. A1.10.2 Evidence summary In total, 95 articles and outbreak reports were identified that investigated the burden of illness related to nuts, prevalence or concentration of selected microbial hazards in nuts, and/or interventions to reduce contamination of microbial hazards in nuts. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in Appendix F: Summary Card Evidence Charts. Salmonella spp. was the most frequently investigated microbial hazard in nuts for burden of illness (n=16 articles and outbreak reports), prevalence (n=19), and intervention (n=46 articles) information. A1.10.3 Burden of illness Burden of illness evidence related to nuts and nut products (mainly peanut butter) includes 20 outbreaks that affected 2 241 individuals, including 318 hospitalizations and 13 deaths between 1986 and 2013. Salmonella spp. accounted for 97 percent of illnesses associated with nuts and nut products > E. coli O157:H7 1.3 percent > C. botulinum 0.7 percent. Few countries have reported outbreaks associated with nuts (four involved multiple countries): the United States of America (11) > Canada (6) ANNEX 1 151 > Australia (4) > Sweden (2) > the United Kingdom of Great Britain and Northern Ireland (1). The origin of the product implicated in the outbreaks was local (13), imported (5) from the United States of America, China, Türkiye and India and unknown (2). Six contaminated peanut butter outbreaks were mainly from North America with one exception from Australia. This group accounted for 73 percent of the cases, five outbreaks (1 619 cases) due to Salmonella and one outbreak (five cases) due to C. botulinum. The outbreak size, median (range), from contaminated peanut butter was 75 (5–715). Conversely, there were 14 outbreaks associated with various nuts including: almonds (4), cashews (2), hazelnuts (1), peanuts (4), pine nuts (1), pistachios (2) and walnuts (1) that caused 27 percent of all illness median (range) 23 (1–168) cases per outbreak. Sixteen outbreaks (564 cases) were caused by Salmonella, two (30 cases) by E. coli O157:H7 and one (23 cases) by C. botulinum. A1.10.4 Prevalence A total of 24 studies containing 192 unique trials were identified that investigated the prevalence and/or concentration of selected microbial hazards in nuts and nut products. The median publication year was 2010 (range 1995 to 2014). More than half of the studies (n=13/24) were conducted in Europe, while four were conducted in the United States of America, three in Asia and the Middle East, two in Australia and two in South America. Most studies (58 percent) sampled products during a specific or defined period, while six conducted sampling over multiple years or time points, and four reported on the results of surveillance programmes. Studies primarily sampled products at retail grocery stores and markets (50 percent), and from processing plants (42 percent). Half of the studies (n=12) specified the country(s) of product origin. Overall, most trials did not identify any of the selected microbial hazards in nuts or nut products. When microbial hazards were found, the prevalence was generally low (except for B. cereus and Enterobacteriaceae in tree nuts in a limited number of samples and trials). Salmonella spp. was the most investigated microbial hazard across all nuts categories, followed by generic E. coli and E. coli O157:H7. The prevalence of Salmonella spp. was largely heterogeneous in the almonds, other tree nuts, and peanuts categories, while the average prevalence in mixed/unspecified nuts was 0.2 percent (95 percent CI: 0 to 0.5). In the former categories, Salmonella spp. median prevalence estimates RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 152 TA B LE A 1. 22 S um m ar y of g lo ba lly re po rt ed o ut br ea ks re la te d to n ut s an d nu t pr od uc ts N ut o r N ut P ro du ct (r ef er en ce ) M ic ro bi al h az ar d( s) O ut br ea ks / ca se sa / ho sp it al iz ed / de at hs Co un tr y (y ea r) b Co m m en ts : s us ce pt ib le p op ul at io ns /a tt ac k ra te / co nc en tr at io n of m ic ro bi al h az ar d in th e pr od uc t A lm on ds (I sa ac s et a l., 2 0 0 5) ; ( K ea dy et a l., 2 0 0 4 ); (M ul le r et a l., 20 0 7) ; ( E fo od al er t, 2 0 12 ) S al m on el la (E nt er it id is P T3 0 , P T9 + & N ST 3+ a nd Ty ph im ur iu m ) 4 /2 19 C . 4 7P /1 4 /1 U ni te d St at es o f A m er ic a & C an ad a (2 0 0 1 & 2 0 0 4 E ), Sw ed en (2 0 0 6) E , A us tr al ia (2 0 12 ) R aw a lm on ds im pl ic at ed (3 ) a nd u nk no w n (1 ). T ra ce ba ck t o C al if or ni a (3 ), A us tr al ia (1 ), C al if or ni a st ar te d pa st eu ri za ti on in 2 0 0 7. A lm on ds w er e la bo ra to ry co nfi rm ed o nl y in 2 0 0 1 a nd 2 0 12 . C as he w s (E FS A , 2 0 13 ) S al m on el la P oo na 1/ 16 /0 /0 Sw ed en (2 0 11 )E E pi de m io lo gi ca l e vi de nc e on ly C as he w a nd P ea nu t m ix (O zF oo dN et , 2 0 10 ) S al m on el la Ty ph im ur iu m D T1 70 1/ 19 P / 0 /0 A us tr al ia (2 0 10 )E Th e nu t m ix tu re t es te d po si ti ve fo r S . T yp h im u ri u m . P ea nu ts (K ir k et a l., 2 0 0 4 ); (H ar ri s et al ., 20 14 ) S al m on el la S ta nl ey , N ew po rt a nd Th om ps on 2/ 21 1/ 0 /0 A us tr al ia , C an ad a & U ni te d K in gd om o f G re at B ri ta in an d N or th er n Ir el an d (2 0 0 1) , U ni te d St at es o f A m er ic a (2 0 0 6) Fl av ou re d an d ro as te d in s he ll pe an ut s fr om C hi na (2 0 0 1) . C on ce nt ra ti on < 0 .0 3– 2 or ga ni sm s/ g. B oi le d pe an ut s fr om fa ir v en do r im pl ic at ed in (2 0 0 6) . P ea nu t B ut te r (S ch ei l e t al ., 19 98 ); (S al m on el la L aw ye r, 2 0 0 4 ); (S he th e t al ., 20 11 ); (C av al la ro et a l. 20 11 ); (M ac D on al d et a l., 20 13 ) S al m on el la M ba nd ak a, G ro up B , T en ne ss ee , Ty ph im ur iu m , B re de ne y 5/ 15 56 C , 63 P / 27 2/ 9 A us tr al ia (1 99 6) , U ni te d St at es o f A m er ic a (2 0 0 4 E , 20 0 7, 2 0 0 9, 2 0 12 ) Th e 19 96 o ut br ea k im pl ic at ed c on ta m in at ed ro as te d pe an ut s 3 cf u/ g. 2 0 0 4 , s m al l r es ta ur an t as so ci at ed ou tb re ak . 2 0 0 7 an d 20 0 9 ha d >7 0 0 c as es e ac h. R ec al ls oc cu rr ed in 2 0 0 7, 2 0 0 9 an d 20 12 . (S he pp ar d et a l., 2 0 12 ) C . b ot ul in um 1/ 5/ 5/ 0 C an ad a (2 0 0 6- 8) P in e N ut s (C D C , 2 0 11 ) S al m on el la E nt er it id is 1/ 4 3/ 2/ 0 U ni te d St at es o f A m er ic a (2 0 11 ) P in e nu ts fr om T ür ki ye w er e re ca lle d. P is ta ch io s (C D C , 2 0 0 9) (F D A , 2 0 14 ) S al m on el la M on te vi de o, N ew po rt , a nd Se nft en be rg 2/ 9/ 0 /0 U ni te d St at es o f A m er ic a (2 0 0 9) U ni te d St at es o f A m er ic a (2 0 13 ) P ro du ct s w er e id en ti fie d as c on ta m in at ed b y th e FD A an d re ca lle d. O nl y on e ca se h ad a m at ch in g P FG E p at te rn (2 0 0 9) a nd e ig ht w er e id en ti fie d in 2 0 13 . H az el nu ts (M ill er e t al ., 20 12 ) E . c ol i O 15 7: H 7 1/ 16 /1 2/ 0 U ni te d St at es o f A m er ic a & C an ad a (2 0 11 ) In s he ll ha ze ln ut s im pl ic at ed , c on ta m in at io n on -f ar m su sp ec te d. W al nu ts (P H A C , 2 0 11 ) E . c ol i O 15 7: H 7 1/ 14 /1 0 /1 C an ad a (2 0 11 ) C on ta m in at ed w al nu ts fr om t he U ni te d St at es o f A m er ic a w er e im pl ic at ed . a Su pe rs cr ip t C in di ca te s co nfi rm ed c as es ; p in di ca te s pr es um pt iv e ca se s. b S up er sc ri pt E in di ca te s th e lin k be tw ee n hu m an c as es a nd im pl ic at ed p ro du ct w as e pi de m io lo gi ca l o nl y; o th er w is e, t he li nk w as la bo ra to ry c on fir m ed . ANNEX 1 153 were all <1 percent. Average generic E. coli prevalence estimates were also very low (<1 percent) across all nut categories. Only one study found positive samples of E. coli O157:H7, identified in 3 of 10 162 samples of raw, shelled runner peanuts from the United States of America processing facilities (Miksch et al., 2013). L. monocytogenes was identified only in two studies and trials: from 1/1 walnut sample in Saudi Arabia (Alwakee and Nasser, 2011), and from 2/43 ready-to-eat mixed nuts in Australia (Eglezos, 2010). C. perfringens and S. aureus were not isolated from nuts or nut products in any study. Concentration information for positive microbial hazard samples was reported in only a few studies (not shown in the table below). Two studies from the United States of America found Salmonella concentrations ranging from 0.003 to 2.4 MPN/g in peanuts (Calhoun et al., 2013; Miksch et al., 2013) and 0.013 to 0.023 MPN/g in almonds (Danyluk et al., 2007; Bansal et al., 2010). Retail samples from the United Kingdom of Great Britain and Northern Ireland reported Salmonella spp. concentrations of 0.09, 0.23 and <0.01 MPN/g in two positive Brazil nut samples and a mixed nut sample, respectively (Little et al., 2010). For generic E. coli, Little et al. (2009) found a concentration of 3.6 MPN/g in two positive retail samples of roasted Brazil nuts and walnuts in the United Kingdom of Great Britain and Northern Ireland, and they found a concentration of 4 MPN/g in a positive sample of roasted almonds. Generic E. coli concentrations ranging from 0.4 to 0.9 MPN/g were found in almonds in the United States of America that were also Salmonella positive (Bansal et al., 2010). TA B LE A 1. 22 S um m ar y of g lo ba lly re po rt ed o ut br ea ks re la te d to n ut s an d nu t pr od uc ts N ut o r N ut P ro du ct (r ef er en ce ) M ic ro bi al h az ar d( s) O ut br ea ks / ca se sa / ho sp it al iz ed / de at hs Co un tr y (y ea r) b Co m m en ts : s us ce pt ib le p op ul at io ns /a tt ac k ra te / co nc en tr at io n of m ic ro bi al h az ar d in th e pr od uc t A lm on ds (I sa ac s et a l., 2 0 0 5) ; ( K ea dy et a l., 2 0 0 4 ); (M ul le r et a l., 20 0 7) ; ( E fo od al er t, 2 0 12 ) S al m on el la (E nt er it id is P T3 0 , P T9 + & N ST 3+ a nd Ty ph im ur iu m ) 4 /2 19 C . 4 7P /1 4 /1 U ni te d St at es o f A m er ic a & C an ad a (2 0 0 1 & 2 0 0 4 E ), Sw ed en (2 0 0 6) E , A us tr al ia (2 0 12 ) R aw a lm on ds im pl ic at ed (3 ) a nd u nk no w n (1 ). T ra ce ba ck t o C al if or ni a (3 ), A us tr al ia (1 ), C al if or ni a st ar te d pa st eu ri za ti on in 2 0 0 7. A lm on ds w er e la bo ra to ry co nfi rm ed o nl y in 2 0 0 1 a nd 2 0 12 . C as he w s (E FS A , 2 0 13 ) S al m on el la P oo na 1/ 16 /0 /0 Sw ed en (2 0 11 )E E pi de m io lo gi ca l e vi de nc e on ly C as he w a nd P ea nu t m ix (O zF oo dN et , 2 0 10 ) S al m on el la Ty ph im ur iu m D T1 70 1/ 19 P / 0 /0 A us tr al ia (2 0 10 )E Th e nu t m ix tu re t es te d po si ti ve fo r S . T yp h im u ri u m . P ea nu ts (K ir k et a l., 2 0 0 4 ); (H ar ri s et al ., 20 14 ) S al m on el la S ta nl ey , N ew po rt a nd Th om ps on 2/ 21 1/ 0 /0 A us tr al ia , C an ad a & U ni te d K in gd om o f G re at B ri ta in an d N or th er n Ir el an d (2 0 0 1) , U ni te d St at es o f A m er ic a (2 0 0 6) Fl av ou re d an d ro as te d in s he ll pe an ut s fr om C hi na (2 0 0 1) . C on ce nt ra ti on < 0 .0 3– 2 or ga ni sm s/ g. B oi le d pe an ut s fr om fa ir v en do r im pl ic at ed in (2 0 0 6) . P ea nu t B ut te r (S ch ei l e t al ., 19 98 ); (S al m on el la L aw ye r, 2 0 0 4 ); (S he th e t al ., 20 11 ); (C av al la ro et a l. 20 11 ); (M ac D on al d et a l., 20 13 ) S al m on el la M ba nd ak a, G ro up B , T en ne ss ee , Ty ph im ur iu m , B re de ne y 5/ 15 56 C , 63 P / 27 2/ 9 A us tr al ia (1 99 6) , U ni te d St at es o f A m er ic a (2 0 0 4 E , 20 0 7, 2 0 0 9, 2 0 12 ) Th e 19 96 o ut br ea k im pl ic at ed c on ta m in at ed ro as te d pe an ut s 3 cf u/ g. 2 0 0 4 , s m al l r es ta ur an t as so ci at ed ou tb re ak . 2 0 0 7 an d 20 0 9 ha d >7 0 0 c as es e ac h. R ec al ls oc cu rr ed in 2 0 0 7, 2 0 0 9 an d 20 12 . (S he pp ar d et a l., 2 0 12 ) C . b ot ul in um 1/ 5/ 5/ 0 C an ad a (2 0 0 6- 8) P in e N ut s (C D C , 2 0 11 ) S al m on el la E nt er it id is 1/ 4 3/ 2/ 0 U ni te d St at es o f A m er ic a (2 0 11 ) P in e nu ts fr om T ür ki ye w er e re ca lle d. P is ta ch io s (C D C , 2 0 0 9) (F D A , 2 0 14 ) S al m on el la M on te vi de o, N ew po rt , a nd Se nft en be rg 2/ 9/ 0 /0 U ni te d St at es o f A m er ic a (2 0 0 9) U ni te d St at es o f A m er ic a (2 0 13 ) P ro du ct s w er e id en ti fie d as c on ta m in at ed b y th e FD A an d re ca lle d. O nl y on e ca se h ad a m at ch in g P FG E p at te rn (2 0 0 9) a nd e ig ht w er e id en ti fie d in 2 0 13 . H az el nu ts (M ill er e t al ., 20 12 ) E . c ol i O 15 7: H 7 1/ 16 /1 2/ 0 U ni te d St at es o f A m er ic a & C an ad a (2 0 11 ) In s he ll ha ze ln ut s im pl ic at ed , c on ta m in at io n on -f ar m su sp ec te d. W al nu ts (P H A C , 2 0 11 ) E . c ol i O 15 7: H 7 1/ 14 /1 0 /1 C an ad a (2 0 11 ) C on ta m in at ed w al nu ts fr om t he U ni te d St at es o f A m er ic a w er e im pl ic at ed . a Su pe rs cr ip t C in di ca te s co nfi rm ed c as es ; p in di ca te s pr es um pt iv e ca se s. b S up er sc ri pt E in di ca te s th e lin k be tw ee n hu m an c as es a nd im pl ic at ed p ro du ct w as e pi de m io lo gi ca l o nl y; o th er w is e, t he li nk w as la bo ra to ry c on fir m ed . RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 154 TABLE A1.23 Prevalence of selected microbial hazards within nut categories (Each cell includes the number of observations/trials/studies contributing to the average or median prevalence estimate, the proportion of trials that did not find any positive samples and measures of heterogeneity and risk of selection bias. See the table footnotes for detailed explanations on each of these parameters.) Nuts and Nut Products Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Almonds Other tree nuts Peanuts Mixed/ unspecified nuts B. cereus 33/2/2 (50%) 9.6 (1.5–22.4)M Low/High 64/8/4 (88%) 6.4 (1.6–13.8)M Low/High 11/2/2 (100%) 0 (0–0)R Low/High N/A C. perfringens N/A 2/1/1 (100%) 0 N/A/High 2/1/1 (100%) 0 N/A/High N/A Cronobacter spp. N/A N/A N/A 2/1/1 (0%) 100 N/A/Low Generic E. coli 3261/6/6 (33%) 0.7 (0–4.8)R High/Low 2957/23/5 (42%) 0.8 (0.5–1.2)M Low/Low 1170/4/4 (75%) 0.1 (0–0.4)M Low/Low 435/3/3 (67%) 0.6 (0.04–1.6)M Low/Low E. coli O157:H7 15/1/1 (100%) 0 n/a/High 51/6/2 (100%) 0 (0–0)R Low/High 10184/4/3 (75%) 0.03 (0.004–0.08)M Low/High 16/1/1 (100%) 0 n/a/High Enterobacteriaceae 30/1/1 (0%) 10 N/A/High N/A N/A N/A L. monocytogenes 45/2/2 (100%) 0 (0–0)R Low/Med. 147/8/2 (88%) 1.4 (0–4.4)M Low/Med. 350/2/2 (100%) 0 (0–0)R Low/Med. 43/1/1 (0%) 4.7 N/A/High S. aureus 30/1/1 (100%) 0 N/A/High 29/5/2 (100%) 0 (0–0)R Low/High 4/2/1 (100%) 0 (0–0)R Low/High N/A Salmonella spp. 13774/8/7 (50%) 0.4 (0–2.7)R High/Low 3051/36/9 (81%) 0 (0–67)R High/Low 12287/9/8 (78%) 0 (0–2.3)R High/Low 114/7/5 (86%) 0.2 (0–0.5)M Low/Low (cont.) ANNEX 1 155 N/A = No data identified for this product-hazard combination. Med. = medium. a Observations/trials/studies: The observations are the total number of samples for all studies included in the summarized category. The number of studies is the number of articles captured. In some cases, articles report data on multiple prevalence trials or sampling frames. While the observations for each trial are independent by time and sample, they are part of a larger study where the methods and investigators are the same. Thus, there is not full independence in these observations, and we note this by acknowledging there are multiple trials within a study. b Superscript M indicates an average prevalence estimate (and 95 percent confidence interval) from a random-effects meta-analysis. Meta-analysis estimates were calculated only if heterogeneity was low or medium (I2 0-60 percent) and if at least one trial found a positive sample. Superscript R indicates a median (and range) of trial prevalence estimates, calculated if heterogeneity was high (I2 >60 percent). Ranges not provided when only one trial was identified. c I2 is a measure of the degree of heterogeneity between trials combined in the meta-analysis. Heterogeneity rating definitions: low = I2 0–30 percent; medium = 31–60 percent; high = >60 percent. Selection bias rating definitions: high = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. Studies that conducted random or systematic sampling were considered representative. The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. Taking into consideration the number of studies in the meta-analysis, high confidence in the meta-analysis results can be inferred when heterogeneity is low and the risk of selection bias is low and low confidence can be inferred when both are high; see the methods section for more information. A1.10.5 Interventions A total of 51 experimental studies (consisting of 265 unique trials) were identified evaluating the effects of various interventions and processing conditions to reduce contamination of microbial hazards in nuts and nut products. More than half (55 percent) of the studies have been published since 2010, which was the median publication year (publication range 1969 to 2014). Most studies (84 percent) were conducted in North America (the United States of America). All studies were challenge trials with artificially inoculated samples. Most studies were conducted under laboratory and non-commercial conditions (although many of the interventions investigated are used in the commercial nut industry), and most studies used a small sample size (e.g. 2–20 samples per intervention combination). Of the 265 trials, 84 percent investigated tree nuts and 16 percent investigated peanut butter and spreads. Most of the tree nut trials (82 percent) investigated pecans (92 trials) and almonds (90 trials). Most trials investigated Salmonella spp. (83 percent) and E. coli (14 percent), with only seven and three investigating L. monocytogenes and B. cereus, respectively. Most trials found that the applied interventions achieved statistically significant reductions in microbial hazard concentrations in nuts and nut products, and for several intervention categories the number of trials finding a significant RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 156 TABLE A1.24 Forest plot of the prevalence of selected microbial hazards within nut categories LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% Microbial hazard/LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs. /trials/ studies Heterogeneity Selection bias Median (range) B. cereus Almonds 9.6 1.5 22.4 33/2/2 Low High - Other tree nuts 6.4 1.6 13.8 64/8/4 Low High - Peanuts 0.0 0.0 0.0 11/2/2 Low High - Overall 7.3 3.1 12.9 Low - Generic E. coli Almonds 1.3 0.0 4.3 3 261/6/6 High Low 0.7 (0–4.8) Other tree nuts 0.8 0.5 1.2 2 957/23/5 Low Low - Peanuts 0.1 0.0 0.4 1 170/4/4 Low Low - Mixed/unspecified nuts 0.6 0.0 1.6 435/3/3 Low Low - Overall 0.8 0.3 1.4 High 0 (0–4.8) E. coli O157 Almonds 0.0 - - 15/1/1 N/A High - Other tree nuts 0.0 0.0 0.0 51/6/2 Low High - Peanuts 0.0 0.0 0.1 10 184/4/3 Low High - Mixed/unspecified nuts 0.0 - - 16/1/1 N/A High - Overall 0.0 0.0 0.1 Low - L. monocytogenes Almonds 0.0 0.0 0.0 45/2/2 Low Med. - Other tree nuts 1.4 0.0 4.4 147/8/2 Low Med. - Peanuts 0.0 0.0 0.0 350/2/2 Low Med. - Mixed/unspecified nuts 4.7 - - 43/1/1 N/A High - Overall 0.9 0.0 2.9 Med. - Salmonella spp. Almonds 0.9 0.5 1.5 13 774/8/7 High Low 0.4 (0–2.7) Other tree nuts 0.8 0.3 1.6 3 051/36/9 High Low 0 (0–66.7) Peanuts 0.5 0.0 1.2 12 287/9/8 High Low 0 (0–2.3) Mixed/unspecified nuts 0.2 0.0 0.5 114/7/5 Low Low - Overall 0.6 0.4 0.9 High 0 (0–66.7) CI = confidence interval; Med = medium; No. obs. = number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: C.perfringens and S. aureus evidence not shown in this figure because no positive samples were identified in these categories. Cronobacter spp. evidence is not shown in this figure because only one trial/study was identified. ANNEX 1 157 intervention effect was greater than we would expect by chance alone. However, in many cases these reductions were only minimal (e.g. <1–5 log CFU/g) and did not decrease microbial hazard counts to non-detectable levels. For some interventions, treatment efficacies may be limited due to natural nut proteins and fats acting as protective barriers (Shachar and Yaron, 2006; Grasso et al., 2010). The most common interventions were various types of heat (e.g. hot air, water and oil) and chemical treatments (e.g. acid solutions and fumigations). While some interventions were found to be very effective in a reduction of microbial concentrations, the doses and/or duration of treatment required to achieve suitable reductions in microbial hazard concentrations may also negatively affect the sensory quality (e.g. taste and texture) of nuts and nut products (Beuchat and Mann, 2011b; Prakash et al., 2010). Since 2007, all almonds produced in California, the United States of America, and marketed in North America must undergo a mandatory pasteurization step necessary to achieve a 5-log reduction in Salmonella spp., which could include roasting, blanching, steam treatments, or propylene oxide treatment (Almond Board of California, 2012). Due to the difficulties in reliabily reducing levels of microbial hazards on nuts and nut products without unduly affecting their quality, emphasis in the industry should be placed on preventing contamination during harvesting and processing (e.g. shelling) operations (Beuchat, Mann and Alali, 2013). 0% 20% 40% 60% 80% 100% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 158 TA B LE A 1. 25 S um m ar y ta bl e of e xp er im en ta l s tu di es e va lu at in g th e eff ec ts o f i nt er ve nt io ns t o re du ce c on ta m in at io n of s el ec te d m ic ro bi al h az ar ds in nu ts a nd n ut p ro du ct s N ut ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) St ud y re fe re nc e ID sa ,b M ic ro bi al h az ar d( s) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc Tr ee n ut s C he m ic al s M et hy l b ro m id e ga s (3 2– 96 m g/ L; 4 –8 h r) P ro py le ne o xi de g as (4 0 –8 0 0 p pm ; 2 0 –3 7° C ; 4 –1 6 hr ) 38 93 67 4 9 E . c ol i ( H –2 3 an d K -1 2) 2/ 2 0 10 0 C he m ic al s So di um h yp oc hl or it e sp ra y (2 5– 50 p pm ; 1 5 m in ) P er ox ya ce ti c ac id s pr ay (8 0 –1 20 p pm ; 1 5 m in ) A ci di fie d so di um c hl or it e sp ra y (4 50 –1 0 13 p pm ; 1 5 m in ) So di um h yp oc hl or it e di p (3 0 0 0 0 p pm ; 2 m in ) So di um d od ec yl s ul fa te d ip (0 .0 5% ; 2 –2 0 m in ) C hl or in at ed w at er d ip (2 0 0 -1 0 0 0 µ g/ m l; 1– 20 m in ) La ct ic a ci d di p (0 .5 –2 % ; 2 –2 0 m in ) Le vu lin ic a ci d di p (0 .5 -2 % ; 2 –2 0 m in ) M ix ed p er ox ya ci d sa ni ti ze r (4 0 –8 0 µ g/ m l; 2– 20 m in ) La ct ic a ci d/ so di um d od ec yl s ul fa te d ip (2 –2 0 m in ) Le vu lin ic a ci d/ so di um d od ec yl s ul fa te d ip (2 –2 0 m in ) C hl or in at ed w at er d ip (1 0 0 –4 0 0 µ g/ m l; 1 m in t o 24 h r) A ci di c el ec tr ol yz ed w at er (m ild t o st ro ng ; 1 0 s ) P ro py le ne o xi de g as (0 .5 k g/ m 3; 4 h r) M et hy l b ro m id e ga s (1 6– 96 m g/ L; 4 –8 h r) A ce ti c ac id s pr ay (5 –1 5% ; 1 –4 0 m in ) C it ri c ac id s pr ay (5 –1 5% ; 1 –4 0 m in ) A ci di fie d so di um c hl or it e sp ra y (≤ 4 0 0 p pm ; 1 –4 0 m in ) P er ox ya ce ti c ac id s pr ay (8 0 -5 0 0 p pm ; 1 –4 0 m in ) 22 22 22 62 14 0 /2 79 14 0 /2 79 14 0 /2 79 14 0 /2 79 14 0 /2 79 14 0 /2 79 14 0 /2 79 72 9 11 29 19 50 a 38 93 56 57 56 57 56 57 56 57 S al m on el la s pp . 68 /9 28 97 * D ry in g A m bi en t te m pe ra tu re ; 2 4 h r A m bi en t te m pe ra tu re ; 7 2 hr A m bi en t te m pe ra tu re ; 7 d ay s 62 35 6 4 96 E . c ol i O 15 7: H 7, L . m on oc yt og en es 5/ 3 20 10 0 D ry in g A m bi en t te m pe ra tu re ; 2 4 h r A m bi en t te m pe ra tu re ; 7 2 hr A m bi en t te m pe ra tu re ; 7 d ay s 15 –3 7° C ; 2 4 h r 62 35 6 4 96 18 33 S al m on el la s pp . 7/ 4 4 3 10 0 * H ea t tr ea tm en t H ot w at er d ip (B oi lin g; 0 .2 5– 6 m in ) H ot o il di p (1 0 0 –1 50 °C ; 0 .2 5– 6 m in ) 4 0 39 G en er ic E . c ol i 2/ 1 0 10 0 (c on t. ) ANNEX 1 159 N ut ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) St ud y re fe re nc e ID sa ,b M ic ro bi al h az ar d( s) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc H ea t tr ea tm en t H ot w at er d ip (7 0 –8 0 °C ; 8 0 –9 0 s ) H ot o il di p (1 21 °C ; 0 .5 –2 m in ) H ot o il di p (1 10 –1 38 °C ; 0 .5 –4 2 m in ) D ry a ir (6 0 –1 70 °C ; 5 –2 0 m in ) St ea m p as te ur iz at io n (1 21 –2 0 4 °C ; 0 –9 0 % M v; 1– 1 2 0 6 s) H ot w at er d ip (7 5– 95 °C ; 5 –2 0 m in ) H ot o il di p (9 3– 12 7° C ; 0 .5 –4 m in ) St ea m p as te ur iz at io n (1 4 3 kP a; 9 5° C ; 5 –6 5 s) St ea m p as te ur iz at io n (1 21 –2 32 °C ; 5 –9 0 % M v; 1– 1 8 0 0 s ) H ot w at er b at h (8 5– 89 °C ; 2 0 –4 0 s ) D ry h ea t (5 5– 60 °C ; 1 –4 d ay s) H ot w at er d ip (6 0 –9 9° C ; 1 –6 m in ) H ot o il di p (1 0 0 °C ; 1 5– 30 m in ) H ot w at er d ip (6 0 –8 8° C ; 0 .5 –1 2 m in ) St ea m p as te ur iz at io n (9 3° C ; 5 –6 5 s) St ea m p as te ur iz at io n (9 9° C ) 23 0 51 1 61 5 61 5 72 8 72 9 90 4 99 5 11 0 9 11 29 11 29 39 53 4 54 2 4 54 8 56 39 66 21 a S al m on el la s pp . 4 0 /1 4 58 95 * H ig h- hy dr os ta ti c pr es su re 4 14 a nd 4 83 M pa ; 5 0 °C ; 1 .5 –6 m in 50 0 0 0 –7 0 0 0 0 p si ; 2 5– 55 °C ; 5 –1 0 m in 13 84 56 16 S al m on el la s pp . 8/ 2 0 88 Ir ra di at io n X -r ay (0 .3 –5 .5 k G y; 2 0 G y/ s) C at al yt ic in fr ar ed (7 0 s ) C at al yt ic in fr ar ed (3 0 0 0 -5 4 58 W /m 2; 7 4 –1 13 °C ; 2 0 –4 5 s) G am m a (1 –3 k G y) 53 6 11 29 13 72 4 95 3 S al m on el la s pp . 12 /4 8 58 M ul ti pl e E le ct ro n be am r ad ia ti on (0 .2 –0 .8 k G y) + m od ifi ed at m os ph er e pa ck ag in g (v ac uu m , n it ro ge n an d ox yg en ) 4 0 85 G en er ic E . c ol i 3/ 1 10 0 10 0 (c on t. ) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 160 N ut ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) St ud y re fe re nc e ID sa ,b M ic ro bi al h az ar d( s) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc M ul ti pl e In te rm it te nt v ac uu m a nd a m bi en t at m os ph er ic pr es su re (1 6– 98 3 m ba r; 5 –2 0 m in ) + c he m ic al d ip s (s ee ab ov e) H ot w at er b at h (7 5– 95 °C ; 5 –2 0 m in ) + c hl or in at ed w at er d ip (2 0 0 µ g/ m l; 1 m in ) C at al yt ic in fr ar ed -r ad ia ti on (7 0 s ) + S up er he at ed s te am (1 15 °C ; 2 0 –1 20 s ) C at al yt ic in fr ar ed -r ad ia ti on (7 0 s ) + d ry h ea t (6 0 °C ; 1 –4 da ys ) C at al yt ic in fr ar ed -r ad ia ti on + h ot w at er b at h (8 5– 89 °C ; 20 –4 0 s ) C at al yt ic in fr ar ed -r ad ia ti on + o zo ne d ip (5 p pm ; 1 0 s ) C at al yt ic in fr ar ed -r ad ia ti on + a ci di c el ec tr ol yz ed w at er (m ild t o st ro ng ; 1 0 s ) H ig h- hy dr os ta ti c pr es su re (4 14 a nd 4 83 M pa ; 5 0 °C ; 6 m in ) + D ry h ea t (5 5– 11 5° C ; 5 –2 5 m in ) E le ct ro n be am r ad ia ti on (0 .2 –0 .8 k G y) + m od ifi ed at m os ph er e pa ck ag in g (v ac uu m , n it ro ge n an d ox yg en ) C it ri c ac id s pr ay (1 0 % ; 2 0 m in ) + s he lli ng a nd s to ra ge (2 4 °C ; 1 –7 d ay s) C it ri c ac id s pr ay + d ei on iz ed w at er r in se (5 0 m L/ 25 g ), ai r- dr yi ng (2 5° C ; 2 h r) a nd s to ra ge (2 4 °C ; 1 –7 d ay s) C hl or in e di ox id e ga s (5 –1 0 m g/ L; 8 0 –9 0 % R H ; 1 0 –3 0 m in ) + v ac uu m -a tm os ph er ic p re ss ur e (2 0 kp a– 80 kP a) 14 0 72 9 97 5 11 29 11 29 11 29 11 29 13 84 4 0 85 56 57 56 57 67 12 S al m on el la s pp . 27 /8 4 4 10 0 * N on -t he rm al / co ld p la sm a 54 9 W ; 4 7 kH z; 10 –2 0 s 16 –2 5 kV ; 1 0 0 0 –2 50 0 H z; 10 –3 0 s 4 79 15 12 E . c ol i ( ge ne ri c an d pa th og en ic ) 6/ 2 0 10 0 * N on -t he rm al / co ld p la sm a 54 9 W ; 4 7 kH z; 10 –2 0 s 4 79 S al m on el la s pp . 3/ 1 0 10 0 N ut e xt ra ct s Sh uc k, s he ll, p it h, s he ll- pi th (1 –5 m in ) 27 9 S al m on el la s pp . 8/ 1 0 75 O zo ne G as (0 .1 –1 p pm ; 6 0 –3 60 m in ) 56 15 B . c er eu s, G en er ic E . c ol i 3/ 1 0 10 0 O zo ne D ip (5 p pm ; 1 0 s ) 11 29 S al m on el la s pp . 1/ 1 0 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (- 19 t o 24 °C ; 1 –3 65 d ay s) In cr ea se d te m pe ra tu re (- 7 to 3 0 °C ; 1 –2 4 w ee ks ) In cr ea se d te m pe ra tu re (5 –3 7° C ; 1 –1 9 w ee ks ) 35 6 67 4 9 66 28 E . c ol i ( ge ne ri c an d pa th og en ic ) 4 /3 0 10 0 (c on t. ) ANNEX 1 161 N ut ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) St ud y re fe re nc e ID sa ,b M ic ro bi al h az ar d( s) N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc St or ag e co nd it io ns In cr ea se d te m pe ra tu re (- 19 t o 24 °C ; 1 –3 65 d ay s) 35 6 L. m on oc yt og en es 2/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (4 °C t o am bi en t; 2 1– 1 1 4 3 da ys ) In cr ea se d te m pe ra tu re (- 19 t o 24 °C ; 1 –3 65 d ay s) In cr ea se d te m pe ra tu re (- 20 t o 23 °C ; 1 –3 64 d ay s) In cr ea se d te m pe ra tu re (4 a nd 2 3° C ; 1 –4 8 w ee ks ) In cr ea se d te m pe ra tu re (- 20 t o 37 °C ; 2 –7 8 w ee ks ) In cr ea se d te m pe ra tu re (- 20 t o 35 °C ; 7 –1 71 d ay s) In cr ea se d te m pe ra tu re (- 18 t o 21 °C ; 2 –3 2 w ee ks ) 62 35 6 4 96 51 1 90 3 17 62 39 53 S al m on el la s pp . 12 /7 17 10 0 * V ac uu m - at m os ph er ic pr es su re 33 c m ; 6 m in 39 53 S al m on el la s pp . 1/ 1 0 0 P ea nu t bu tt er / sp re ad s H ea t tr ea tm en t H ot w at er d ip (7 2 an d 90 °C ; 1 0 –6 0 m in ) 60 2 E . c ol i O 15 7: H 7 4 /1 10 0 10 0 H ea t tr ea tm en t H ot w at er d ip (7 2 an d 90 °C ; 1 0 –6 0 m in ) H ot w at er d ip (7 1– 90 °C ; 2 .5 –5 0 m in ) H ot w at er d ip (7 0 –9 0 °C ; 5 –5 0 m in ) 60 2 11 10 17 0 8 S al m on el la s pp . 7/ 3 10 0 86 H ig h- hy dr os ta ti c pr es su re 4 0 0 –6 0 0 M P a; 4 –1 8 m in 60 0 M pa ; 4 5° C ; 5 m in 52 2 71 0 S al m on el la s pp . 4 /2 50 50 Ir ra di at io n R ad io -f re qu en cy (2 7. 12 M H z; 10 –9 0 s ) 18 2 E . c ol i O 15 7: H 7 2/ 1 10 0 10 0 Ir ra di at io n G am m a (1 –3 k G y) R ad io -f re qu en cy (2 7. 12 M H z; 10 –9 0 s ) E le ct ro n be am (0 .5 –3 .1 k G y) E le ct ro n be am (0 .5 –3 .1 k G y) 10 18 2 70 6 10 17 S al m on el la s pp . 9/ 4 10 0 10 0 * St or ag e co nd it io ns In cr ea se d te m pe ra tu re (4 a nd 2 5° C ; 1 –4 w ee ks ) In cr ea se d te m pe ra tu re (4 a nd 2 5° C ; 1 –1 5 w ee ks ) 60 2 67 58 E . c ol i O 15 7: H 7 5/ 2 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (4 a nd 2 5° C ; 1 –4 w ee ks ) In cr ea se d te m pe ra tu re (5 a nd 2 1° C ; 1 –2 4 w ee ks ) In cr ea se d te m pe ra tu re (4 a nd 2 5° C ; 1 –1 5 w ee ks ) 60 2 25 86 67 58 S al m on el la s pp . 12 /3 58 10 0 * a I nd ic at es t he se s tu di es w er e co nd uc te d un de r co m m er ci al c on di ti on s. b D is ti lle rS R re fe re nc e ID n um be r. R ef er t o ci ta ti on li st a t th e en d of t hi s su m m ar y fo r fu ll ci ta ti on o f e ac h re fe re nc e m at ch ed t o th e re fe re nc e ID . c I nt er ve nt io n ca te go ri es m ar ke d w it h an a st er is k (* ) i nd ic at e th at m or e tr ia ls fo un d a st at is ti ca lly s ig ni fic an t re du ct io n in m ic ro bi al c on ce nt ra ti on o r pr ev al en ce t ha n w ou ld b e ex pe ct ed b y ch an ce a lo ne (s ig n te st P v al ue < 0 .0 5) . RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 162 A1.10.6 References in A1.10 References used in summary narrative: Almond Board of California. 2012. The Food Safety Program & Almond Pasteurization. In: California Almonds [online]. Modesto, California, USA. [Cited 20 July 2021]. http://www.almondboard.com/Handlers/FoodQualitySafety/Pasteurization/ Pages/Default.aspx. Alwakee, S. S., & Nasser, L. A. 2011. Microbial contamination and mycotoxins from nuts in Riyadh, Saudi Arabia. American Journal of Food Technology, 6(8): 613–630. Ref #: 4757. Bansal, A., Jones, T. M., Abd, S. J., Danyluk, M. D. & Harris, L. J. 2010. Most-probable- number determination of Salmonella levels in naturally contaminated raw almonds using two sample preparation methods. Journal of Food Protection, 73(11): 1986– 1992. Ref #: 788. Calhoun, S., Post, L., Warren, B., Thompson, S. & Bontempo, A. R. 2013. Prevalence and concentration of Salmonella on raw shelled peanuts in the United States. Journal of Food Protection, 76(4): 575–579. Ref #: 157. Danyluk, M. D., Jones, T. M., Abd, S. J., Schlitt-Dittrich, F., Jacobs, M. & Harris, L. J. 2007. Prevalence and amounts of Salmonella found on raw California almonds. Journal of Food Protection, 70 (4): 820–827. Ref #: 1622. Eglezos, S. 2010. The bacteriological quality of retail-level peanut, almond, cashew, hazelnut, Brazil, and mixed nut kernels produced in two Australian nut-processing facilities over a period of 3 years. Foodborne Pathogens and Disease, 7(7): 863–866. Ref #: 996. FAO. 1995. Edible nuts [online] Non-wood forest products 5. [Cited 20 July 2021]. http:// www.fao.org/3/v8929e/v8929e.pdf Little, C. L., Jemmott, W., Surman-Lee, S., Hucklesby, L., & De Pinna, E. 2009. Assessment of the microbiological safety of edible roasted nut kernels on retail sale in England, with a focus on Salmonella. Journal of Food Protection, 72 (4): 853–855. Ref #: 1187. Miksch, R. R., Leek, J., Myoda, S., Nguyen, T., Tenney, K., Svidenko, V., Greeson, K. & Samadpour, M. 2013. Prevalence and counts of Salmonella and enterohemorrhagic Escherichia coli in raw, shelled runner peanuts. Journal of Food Protection, 76(10): 1668–1675. Ref #: 45. ANNEX 1 163 Citation list of burden of illness studies (n=20 unique citations): (Distiller ID = Ref #, Outbreak # =OB # where a Distiller ID is not available – for unpublished outbreaks) Cavallaro, E., Date, K., Medus, C., Meyer, S., Miller, B., Kim, C., Nowicki, S., Cosgrove, S., Sweat, D., Phan, Q., Flint, J., Daly, E. R., Adams, J., Hyytia-Trees, E., Gerner- Smidt, P., Hoekstra, R. M., Schwensohn, C., Langer, A., Sodha, S. V., Rogers, M. C., Angulo, F. J., Tauxe, R. V., Williams, I. T. & Behravesh, C. B. 2011. Salmonella typhimurium infections associated with peanut products. New England Journal of Medicine, 365(7): 601–610. Ref #: 625. CDC. 2011. Multistate Outbreak of Human Salmonella enteritidis infections linked to Turkish Pine Nuts. In: Center for Disease Control [online]. [Cited 20 July 2021]. https://www.cdc.gov/salmonella/2011/pine-nuts-11-17-2011.html OB#177. CDC. 2009. Salmonella in Pistachio Nuts, 2009. In: Center for Disease Control [online]. [Cited 20 July 2021]. https://www.cdc.gov/salmonella/2009/pistachio- nuts-4-14-2009.html Ref #: 6620. Efoodalert. 2012. Contaminated almonds sicken 37 in Australia. In: Efoodalert [online]. [Cited 20 July 2021]. http://efoodalert.wordpress.com/2012/10/29/contaminated- almonds-sicken-37-in-australia/ Ref #: OB# 203. EFSA. 2013. Scientific opinion on the risk posed by pathogens in food of non- animal origin. Part 1 (outbreak data analysis and risk ranking of food/pathogen combinations). EFSA Journal 11: 3025. OB# 196. FDA. 2014. FDA Investigation Summary - Multistate Outbreak of Salmonella Senftenberg Infections Associated with Pistachios from a California Roaster [online]. Washington, D.C. [Cited 20 July 2021]. http://outbreakdatabase.com/reports/2013_Salmonella_ Senftenberg_Linked_to_Pistachos.pdf OB# 300. Harris, L. J., Beuchat, L.R., Danyluk M.D. & Palumbo M. 2014. Outbreaks of foodborne illness associated with the consumption of tree nuts, peanuts, and sesame seeds [Table and references]. In: UC Food Safety [online]. [Cited 20 July 2021]. http:// ucfoodsafety.ucdavis.edu/Nuts_and_Nut_Pastes. OB#279. Isaacs, S., Aramini, J., Ciebin, B., Farrar, J. A., Ahmed, R., Middleton, D., Chandran, A. U., Harris, L. J., Howes, M., Chan, E., Pichette, A. S., Campbell, K., Gupta, A., Lior, L. Y., Pearce, M., Clark, C., Rodgers, F., Jamieson, F., Brophy, I. & Ellis, A. 2005. An international outbreak of salmonellosis associated with raw almonds contaminated with a rare phage type of Salmonella Enteritidis. Journal of Food Protection 68(1): 191–198. Ref #: 2407. Keady, S., Briggs, G., Farrar, J., Mohle-Boetani, J. C., O’Connell, J., Werner, S. B., Anderson, D., Tenglesen, L., Bidols, S., Albanese, B., DeBess, E., Hatch, J., Keene, W. E., Plantenga, M., Tierheimer, J., Hackman, A.L., Rinehardt, C. E., Sandt, RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 164 C.E., Ingram, A., Hansen, S., Hurt, S., Poulson, M., Pallipamu, R.,Wicklund, J., Braden, C., Lockett, J., Van Duyne, S., Dechet, A. & Smelser, C. 2004. Outbreak of Salmonella serotype enteritidis infections associated with raw almonds - United States and Canada, 2003-2004. MMWR Morbidity and Mortality Weekly Report 53(22): 484–487. Ref #: 5769. Kirk, M. D., Little, C. L., Lem, M., Fyfe, M., Genobile, D., Tan, A., Threlfall, J., Paccagnella, A., Lightfoot, D., Lyi, H., McIntyre, L., Ward, L., Brown, D. J., Surnam, S. & Fisher, I. S. 2004. An outbreak due to peanuts in their shell caused by Salmonella enterica serotypes Stanley and Newport--sharing molecular information to solve international outbreaks. Epidemiology and Infection, 132(4): 571–577. Ref #:2125. MacDonald, J. K., Julian, E., Chu, A., Dion, J., Beal, J., Lanier, W., Nguyen, T., Burnworth, L., Williams, I., Gieraltowski, L. & Hancock, W.T. 2013. Notes from the field: Salmonella Bredeney infections linked to a brand of peanut butter--United States, 2012. MMWR Morbidity and Mortality Weekly Report 62(6): 107. Ref #: 203. Miller, B. D., Rigdon, C. E., Ball, J., Rounds, J. M., Klos, R. F., Brennan, B. M., Arends, K. D., Kennelly, P., Hedberg, C. & Smith, K. E. 2012. Use of traceback methods to confirm the source of a multistate Escherichia coli O157:H7 outbreak due to in-shell hazelnuts. Journal of Food Protection, 75(2): 320–327. Ref #:495. Muller, L., Hjertqvist, M., Payne, L., Pettersson, H., Olsson, A., Plym Forshell, L. & Andersson, Y. 2007. Cluster of Salmonella Enteritidis in Sweden 2005-2006 - suspected source: almonds. Eurosurveillance. 12(6): E9–10. Ref #:1517. OzFoodNet. 2010. Quarterly report, 1 April to 30  June 2010. Communicable Diseases Intelligence, 34(3). OB# 148. Public Health Agency of Canada (PHAC). 2011. Public Advisory: E. coli Outbreak [online]. [Cited 20 July 2021]. https://www.healthycanadians.gc.ca/recall-alert- rappel-avis/inspection/2011/33573r-eng.php OB# 175. Salmonella Lawyer. 2004. Toss Dinnerbell PB and jam, officials warn [online]. [Cited 20 July 2021]. http://www.salmonellablog.com/salmonella-watch/toss-dinnerbell-pb- and-jam-officials-warn/#.Uxovmc62nSh. OB#210. Scheil, W., Cameron, S., Dalton, C., Murray, C. & Wilson, D. A. 1998. South Australian Salmonella Mbandaka outbreak investigation using a database to select controls. Australian and New Zealand Journal of Public Health. 22(5): 536–539. Ref #:2766. Sheppard, Y. D., Middleton, D., Whitfield, Y., Tyndel, F., Haider, S., Spiegelman, J., Swartz, R. H., Nelder, M. P., Baker, S. L., Landry, L., Maceachern, R., Deamond, S., Ross, L., Peters, G., Baird, M., Rose, D., Sanders, G. & Austin, J. W. 2012. Intestinal toxemia botulism in 3 adults, Ontario, Canada, 2006-2008. Emerging Infectious Diseases. 18(1): 1–6. Ref #: 513. ANNEX 1 165 Sheth, A. N., Hoekstra, M., Patel, N., Ewald, G., Lord, C., Clarke, C., Villamil, E., Niksich, K., Bopp, C., Nguyen, T. A., Zink, D. & Lynch, M. 2011. A national outbreak of Salmonella serotype Tennessee infections from contaminated peanut butter: a new food vehicle for salmonellosis in the United States. Clinical Infectious Diseases, 53(4): 356–362. Ref #: 633. Citation list of prevalence studies (N=24): (Distiller ID = Ref #) Al-Moghazy, M., Boveri, S. & Pulvirenti, A. 2014. Microbiological safety in pistachios and pistachio containing products. Food Control, 36(1): 88–93. Ref #: 4089. Alwakee, S. S. & Nasser, L. A. 2011. Microbial contamination and mycotoxins from nuts in Riyadh, Saudi Arabia. American Journal of Food Technology, 6(8): 613–630. Ref #: 4757. Arrus, K., Blank, G., Clear, R., Holley, R. A. & Abramson, D. 2005. Microbiological and aflatoxin evaluation of Brazil nut pods and the effects of unit processing operations. Journal of Food Protection, 68(5): 1060–1065. Ref #: 1986. Bansal, A., Jones, T. M., Abd, S. J., Danyluk, M. D., & Harris, L. J. 2010. Most-probable- number determination of Salmonella levels in naturally contaminated raw almonds using two sample preparation methods. Journal of Food Protection, 73(11): 1986– 992. Ref #: 788. Calhoun, S., Post, L., Warren, B., Thompson, S. & Bontempo, A. R. 2013. Prevalence and concentration of Salmonella on raw shelled peanuts in the United States. Journal of Food Protection, 76(4): 575–579. Ref #: 157. Candlish, A. A. G., Pearson, S. M., Aidoo, K. E., Smith, J. E., Kelly, B. & Irvine, H. 2001. A survey of ethnic foods for microbial quality and aflatoxin content. Food Additives and Contaminants, 18(2): 129–136. Ref #: 2535. Danyluk, M. D., Jones, T. M., Abd, S. J., Schlitt-Dittrich, F., Jacobs, M. & Harris, L. J. 2007. Prevalence and amounts of Salmonella found on raw California almonds. Journal of Food Protection, 70 (4): 820–827. Ref #: 1622. EFSA & ECDC. 2010. The community summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in the European Union in 2008. EFSA Journal, 8: 1496. Ref #: 6636. EFSA & ECDC. 2011. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2009. EFSA Journal, 9(3): 2090. Ref #: 6637. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 166 EFSA & ECDC. 2012. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2010. EFSA Journal, 10(3): 2597. Ref #: 6757. Eglezos, S. 2010. The bacteriological quality of retail-level peanut, almond, cashew, hazelnut, Brazil, and mixed nut kernels produced in two Australian nut-processing facilities over a period of 3 years. Foodborne Pathogens and Disease, 7(7): 863–866. Ref #: 996. Eglezos, S., Huang, B. & Stuttard, E. 2008. A survey of the bacteriological quality of preroasted peanut, almond, cashew, hazelnut, and Brazil nut kernels received into three Australian nut-processing facilities over a period of 3 years. Journal of Food Protection, 71(2): 402–404. Ref #: 1425. Freire, F. d. C. O. & Offord, L. 2002. Bacterial and yeast counts in brazilian commodities and spices. Brazilian Journal of Microbiology, 33: 145–148. Ref #: 6644. Iversen, C. & Forsythe, S. 2004. Isolation of Enterobacter sakazakii and other enterobacteriaceae from powdered infant formula milk and related products. Food Microbiology, 21(6): 771–777. Ref #: 6660. La Rosa, R., Russo, A., Verdone, A. & Aloschi, S. 2000. Investigation on hygienic- sanitary quality of almond paste produced in Sicily. Industrie Alimentari, 39(389): 137–143. Ref #: 6088. Little, C. L., Jemmott, W., Surman-Lee, S., Hucklesby, L. & De Pinna, E. 2009. Assessment of the microbiological safety of edible roasted nut kernels on retail sale in England, with a focus on Salmonella. Journal of Food Protection, 72 (4): 853–855. Ref #: 1187. Little, C. L., Rawal, N., de Pinna, E. & McLauchlin, J. 2010. Survey of Salmonella contamination of edible nut kernels on retail sale in the UK. Food Microbiology, 27(1): 171–174. Ref #: 1052. Mena, C., Almeida, G., Carneiro, L., Teixeira, P., Hogg, T. & Gibbs, P. A. 2004. Incidence of Listeria monocytogenes in different food products commercialized in Portugal. Food Microbiology, 21(2): 213–216. Ref #: 6759. Miksch, R. R., Leek, J., Myoda, S., Nguyen, T., Tenney, K., Svidenko, V., Greeson, K. & Samadpour, M. 2013. Prevalence and counts of Salmonella and enterohemorrhagic Escherichia coli in raw, shelled runner peanuts. Journal of Food Protection, 76(10): 1668–1675. Ref #: 45. Mozrova, V., Brenova, N., Mrazek, J., Lukesova, D. & Marounek, M. 2014. Surveillance and characterisation of Cronobacter spp. in Czech retail food and environmental samples. Folia Microbiologica, 59(1): 63–68. Ref #: 95. Riyaz-Ul-Hassan, S., Verma, V., Malik, A. & Qazi, G. N. 2003. Microbiological quality of walnut kernels and apple juice concentrate. World Journal of Microbiology and Biotechnology, 19(8): 845–850. Ref #: 5864. ANNEX 1 167 Rosenkvist, H. & Hansen, Ã. 1995. Contamination profiles and characterisation of Bacillus species in wheat bread and raw materials for bread production. International Journal of Food Microbiology, 26(3): 353–363. Ref #: 6283. Turcovsky, I., Kunikova, K., Drahovska, H. & Kaclikova, E. 2011. Biochemical and molecular characterization of Cronobacter spp. (formerly Enterobacter sakazakii) isolated from foods. Antonie Van Leeuwenhoek, 99(2): 257–269. Ref #: 899. Vural, A. & Erkan, M. E. 2008. The research of microbiological quality in some edible nut kinds. Journal of Food Technology, 6(1): 25–28. Ref #: 6750. Citation list of interventions studies (N=51): (Distiller ID = Ref #) Abd, S. J., McCarthy, K. L. & Harris, L. J. 2012. Impact of storage time and temperature on thermal inactivation of Salmonella Enteritidis PT 30 on oil-roasted almonds. Journal of Food Science, 77(1): M42–7. Ref #: 511. Akbas, M. Y. & Ozdemir, M. 2006. Effectiveness of ozone for inactivation of Escherichia coli and Bacillus cereus in pistachios. International Journal of Food Science and Technology, 41(5): 513–519. Ref #: 5615. Ban, G. H. & Kang, D. H. 2014. Effects of gamma irradiation for inactivating Salmonella Typhimurium in peanut butter product during storage. International Journal of Food Microbiology, 171: 48–53. Ref #: 10. Bari, M. L., Nei, D., Sotome, I., Nishina, I., Isobe, S. & Kawamoto, S. 2009. Effectiveness of sanitizers, dry heat, hot water, and gas catalytic infrared heat treatments to inactivate Salmonella on almonds. Foodborne Pathogens and Disease, 6(8): 953– 958. Ref #: 1129. Bari, L., Nei, D., Sotome, I., Nishina, I. Y., Hayakawa, F., Isobe, S. & Kawamoto, S. 2010. Effectiveness of superheated steam and gas catalytic infrared heat treatments to inactivate Salmonella on raw almonds. Foodborne Pathogens and Disease, 7(7): 845–850. Ref #: 975. Beuchat, L.R. 1973. Escherichia coli on pecans: Survival under various storage conditions and disinfection with propylene oxide. Journal of Food Science, 38(6): 1063–1066. Ref #: 6749. Beuchat, L. R. & Heaton, E. K. 1975. Salmonella survival on pecans as influenced by processing and storage conditions. Applied Microbiology, 29(6): 795–801. Ref #: 3953. Beuchat, L. R. & Mann, D. A. 2010. Factors affecting infiltration and survival of Salmonella on in-shell pecans and pecan nutmeats. Journal of Food Protection, 73(7): 1257–1268. Ref #: 903. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 168 Beuchat, L. R. & Mann, D. A. 2011a. Inactivation of Salmonella on in-shell pecans during conditioning treatments preceding cracking and shelling. Journal of Food Protection, 74(4): 588–602. Ref #: 729. Beuchat, L. R. & Mann, D. A. 2011b. Inactivation of Salmonella on pecan nutmeats by hot air treatment and oil roasting. Journal of Food Protection, 74(9): 1441–1450. Ref #: 615. Beuchat, L. R., Mann, D. A. & Alali, W. Q. 2012. Evaluation of sanitizers for inactivating Salmonella on in-shell pecans and pecan nutmeats. Journal of Food Protection, 75(11): 1930–1938. Ref #: 279. Beuchat, L. R., Mann, D. A. & Alali, W. Q. 2013. Efficacy of sanitizers in reducing Salmonella on pecan nutmeats during cracking and shelling. Journal of Food Protection, 76(5): 770–778. Ref #: 140. Blessington, T., Mitcham, E. J. & Harris, L. J. 2012. Survival of Salmonella enterica, Escherichia coli O157:H7, and Listeria monocytogenes on inoculated walnut kernels during storage. Journal of Food Protection, 75(2): 245–254. Ref #: 496. Blessington, T., Theofel, C. G. & Harris, L. J. 2013. A dry-inoculation method for nut kernels. Food Microbiology, 33(2): 292–297. Ref #: 62. Brandl, M. T., Pan, Z., Huynh, S., Zhu, Y. & McHugh, T. H. 2008. Reduction of Salmonella Enteritidis population sizes on almond kernels with infrared heat. Journal of Food Protection, 71(5): 897–902. Ref #: 1372. Burnett, S. L., Gehm, E. R., Weissinger, W. R., & Beuchat, L. R. 2000. Survival of Salmonella in peanut butter and peanut butter spread. Journal of Applied Microbiology, 89(3): 472–477. Ref #: 2586. Ceylan, E., Huang, G. & Carter, M. 2008. Comparison of moist heat inactivation rates of Salmonella Enteritidis and Pediococcus spp. NRRL B-2354 on whole almonds under commercial plant conditions. In IAFP 2008 Abstract Book, pp. 1–30. IAFP Annual Meeting, 3–4 August, Columbus, Ohio. Ref #: 6621. Chang, S. S., Han, A. R., Reyes-De-Corcuera, J. I., Powers, J. R. & Kang, D. H. 2010. Evaluation of steam pasteurization in controlling Salmonella serotype Enteritidis on raw almond surfaces. Letters in Applied Microbiology, 50(4): 393–398. Ref #: 995. Danyluk, M. D., Uesugi, A. R. & Harris, L. J. 2005. Survival of Salmonella Enteritidis PT 30 on inoculated almonds after commercial fumigation with propylene oxide. Journal of Food Protection, 68(8): 1613–1622. Ref #: 1950. Deng, S., Ruan, R., Mok, C. K., Huang, G., Lin, X. & Chen, P. 2007. Inactivation of Escherichia coli on almonds using nonthermal plasma. Journal of Food Science, 72(2): M62–M66. Ref #: 1512. ANNEX 1 169 Deng, Y., Ryu, J. H. & Beuchat, L. R. 1998. Influence of temperature and pH on survival of Escherichia coli O157:H7 in dry foods and growth in reconstituted infant rice cereal. International Journal of Food Microbiology, 45(3): 173–184. Ref #: 6628. D’Souza, T., Karwe, M., & Schaffner, D. W. 2012. Effect of high hydrostatic pressure and pressure cycling on a pathogenic Salmonella enterica serovar cocktail inoculated into creamy peanut butter. Journal of Food Protection, 75(1): 169–173. Ref #: 522. Du, W. X., Danyluk, M. D. & Harris, L. J. 2010. Efficacy of aqueous and alcohol-based quaternary ammonium sanitizers for reducing Salmonella in dusts generated in almond hulling and shelling facilities. Journal of Food Science, 75(1): M7–13. Ref #: 904. Goodridge, L. D., Willford, J. & Kalchayanand, N. 2006. Destruction of Salmonella Enteriditis inoculated onto raw almonds by high hydrostatic pressure. Food Research International, 39(4): 408–412. Ref #: 5616. Grasso, E. M., Somerville, J. A., Balasubramaniam, V. M. & Lee, K. 2010. Minimal effects of high-pressure treatment on Salmonella enterica serovar Typhimurium inoculated into peanut butter and peanut products. Journal of Food Science, 75(8): E522–E526. Ref #: 710. Ha, J. W., Kim, S. Y., Ryu, S. R. & Kang, D. H. 2013. Inactivation of Salmonella enterica serovar Typhimurium and Escherichia coli O157:H7 in peanut butter cracker sandwiches by radio-frequency heating. Food Microbiology, 34(1): 145–150. Ref #: 182. Harris, L. J., Uesugi, A. R., Abd, S. J. & McCarthy, K. L. 2012. Survival of Salmonella Enteritidis PT 30 on inoculated almond kernels in hot water treatments. Food Research International, 45(2): 1093–1098. Ref #: 4548. He, Y., Guo, D., Yang, J., Tortorello, M. L. & Zhang, W. 2011. Survival and heat resistance of Salmonella enterica and Escherichia coli O157:H7 in peanut butter. Applied and Environmental Microbiology, 77(23): 8434–8438. Ref #: 602. Hvizdzak, A. L., Beamer, S., Jaczynski, J. & Matak, K. E. 2010. Use of electron beam radiation for the reduction of Salmonella enterica serovars Typhimurium and Tennessee in peanut butter. Journal of Food Protection, 73(2): 353–357. Ref #: 1017. Izurieta, W. P. & Komitopoulou, E. 2012. Effect of moisture on Salmonella spp. heat resistance in cocoa and hazelnut shells. Food Research International, 45(2): 1087– 1092. Ref #: 4542. Jeong, S., Marks, B. P. & Orta-Ramirez, A. 2009. Thermal inactivation kinetics for Salmonella Enteritidis PT30 on almonds subjected to moist-air convection heating. Journal of Food Protection, 72(8): 1602–1609. Ref #: 1109. Jeong, S., Marks, B. P. & Ryser, E. T. 2011. Quantifying the performance of Pediococcus sp. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 170 (NRRL B-2354: Enterococcus faecium) as a nonpathogenic surrogate for Salmonella Enteritidis PT30 during moist-air convection heating of almonds. Journal of Food Protection, 74(4): 603–609. Ref #: 728. Jeong, S., Marks, B. P., Ryser, E. T. & Harte, J. B. 2012. The effect of X-ray irradiation on Salmonella inactivation and sensory quality of almonds and walnuts as a function of water activity. International Journal of Food Microbiology, 153(3): 365–371. Ref #: 536. Karagöz, I., Moreira, R. G. & Castell-Perez, M. 2014. Radiation D10 values for Salmonella Typhimurium LT2 and an Escherichia coli cocktail in pecan nuts (kanza cultivar) exposed to different atmospheres. Food Control, 39(1): 146–153. Ref #: 4085. Kilonzo-Nthenge, A., Rotich, E., Godwin, S. & Huang, T. 2009. Consumer storage period and temperature for peanut butter and their effects on survival of Salmonella and Escherichia coli O157:H7. Food Protection Trends 29: 787–792. Ref #: 6758. Kimber, M. A., Kaur, H., Wang, L., Danyluk, M. D. & Harris, L. J. 2012. Survival of Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes on inoculated almonds and pistachios stored at -19, 4, and 24 degrees C. Journal of Food Protection, 75(8): 1394–1403. Ref #: 356. Lee, S. Y., Oh, S. W., Chung, H. J., Reyes-De-Corcuera, J. I., Powers, J. R. & Kang, D. H. 2006. Reduction of Salmonella enterica serovar Enteritidis on the surface of raw shelled almonds by exposure to steam. Journal of Food Protection, 69(3): 591–595. Ref #: 5639. Ma, L., Zhang, G., Peter, G., Vijaya, M., Ifeoma, E. & Michael, P. D. 2009. Thermal inactivation of Salmonella in peanut butter. Journal of Food Protection, 72(8): 1596– 1601. Ref #: 1110. Matak, K. E., Hvizdzak, A. L., Beamer, S. & Jaczynski, J. 2010. Recovery of Salmonella enterica serovars Typhimurium and Tennessee in peanut butter after electron beam exposure. Journal of Food Science, 75(7): M462–7. Ref #: 706. Meyer, M. T. & Vaughn, R. H. 1969. Incidence of Escherichia coli in black walnut meats. Applied Microbiology, 18(5): 925–931. Ref #: 4039. Niemira, B. A. 2012. Cold plasma reduction of Salmonella and Escherichia coli O157: H7 on almonds using ambient pressure gases. Journal of Food Science, 77(3): M171– M175. Ref #: 479. Pao, S., Kalantari, A. & Huang, G. 2006. Utilizing acidic sprays for eliminating Salmonella enterica on raw almonds. Journal of Food Science, 71(1): M14–M19. Ref #: 5657. Prakash, A., Lim, F. T., Duong, C., Caporaso, F. & Foley, D. 2010. The effects of ionizing irradiation on Salmonella inoculated on almonds and changes in sensory properties. Radiation Physics and Chemistry, 79(4): 502–506. Ref #: 4953. ANNEX 1 171 Schade, J. E. & King Jr., A. D. 1977. Methyl bromide as a microbicidal fumigant for tree nuts. Applied and Environmental Microbiology, 33(5): 1184–1191. Ref #: 3893. Shachar, D. & Yaron, S. 2006. Heat tolerance of Salmonella enterica serovars Agona, Enteritidis, and Typhimurium in peanut butter. Journal of Food Protection, 69(11): 2687–2691. Ref #: 1708. Uesugi, A. R., Danyluk, M. D. & Harris, L. J. 2006. Survival of Salmonella Enteritidis phage type 30 on inoculated almonds stored at -20, 4, 23, and 35 degrees C. Journal of Food Protection, 69(8): 1851–1857. Ref #: 1762. Villa-Rojas, R., Tang, J., Wang, S., Gao, M., Kang, D. H., Mah, J. H., Gray, P., Sosa- Morales, M. E. & López-Malo, A. 2013. Thermal inactivation of Salmonella Enteritidis PT 30 in almond kernels as influenced by water activity. Journal of Food Protection, 76(1): 26–32. Ref #: 230. Weller, L. D., Daeschel, M. A., Durham, C. A. & Morrissey, M. T. 2013. Effects of water, sodium hypochlorite, peroxyacetic acid, and acidified sodium chlorite on in-shell hazelnuts inoculated with Salmonella enterica serovar Panama. Journal of Food Science, 78(12): M1885–M1891. Ref #: 22. Wilhodo, M., Han, Y., Selby, T. L., Lorcheim, P., Czarneski, M., Huang, G., & Linton, R. H. 2005. Decontamination of raw almonds using chlorine dioxide gas. IFT Annual Meeting, 15–20 July, 2005, New Orleans, Louisiana, 99E-12. Ref #: 6712. Willford, J., Mendonca, A. & Goodridge, L. D. 2008. Water pressure effectively reduces Salmonella enterica serovar Enteritidis on the surface of raw almonds. Journal of Food Protection, 71(4): 825–829. Ref #: 1384. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 172 A1.11 SUMMARY CARD: SEEDS FOR CONSUMPTION A1.11.1 Low-moisture food category description This summary covers seeds for consumption, which includes dried sunflower seeds, pumpkin seeds, melon seeds, poppy seeds, flax seeds, sesame seeds and sesame products, and other edible seeds. Specific sesame seed products covered in this summary include tahini (sesame paste), which is produced from roasted and milled sesame seeds, and halva/helva, which is a confectionery produced from mixing tahini, sugar, glucose syrup, and other ingredients (Brockmann et al., 2004; Kotzekidou, 1998). Excluded from this summary are other seeds traditionally referred to as nuts (e.g. almonds, pecans, etc., which are covered in a separate summary) and sprouted seeds (FAO, 1995). For the purposes of summarizing prevalence and intervention information, seeds were classified into the following categories: (1) sesame seeds, (2) tahini, (3) halva/ helva, and (4) other/unspecified seeds for consumption. A1.11.2 Evidence summary In total, 28 articles14 and outbreak reports15 were identified that investigated the burden of illness, the prevalence or concentration of selected microbial hazards, and interventions to reduce contamination of microbial hazards in seeds. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in Appendix F: Summary Card Evidence Charts. Salmonella spp. was the most frequently investigated microbial hazard in seeds for burden of illness (n=8 outbreak reports), prevalence (n=14 articles), and intervention (n=3 articles) information. A1.11.3 Burden of illness Burden of illness evidence related to seeds includes eight reported outbreaks between 1995 and 2013; all outbreaks were related to seed-based products and not ready-to-eat retail seeds. Salmonella was implicated in all outbreaks that affected 376 individuals (median 23, range 13–137), including four hospitalizations and one death. Seed outbreaks are shown in the summary table below and were reported from the United States of America (3), Australia (3), New Zealand (2), Germany, Norway and Sweden. 14 Articles refer to peer-reviewed journal publications as well as government and research agency reports. 15 For burden of illness information, multiple articles often reported complementary and/or overlapping information on the same outbreak. In addition, outbreak data were supplemented from other literature sources, including line lists from various countries, news reports, or annual summaries of country outbreaks. Thus, to avoid counting the same outbreak more than once, the term “outbreak report” is used instead of “article” to count the total number of unique outbreaks. ANNEX 1 173 The outbreaks notably had small numbers of confirmed cases; however, all sesame outbreaks (except 1995 as details could not be verified) resulted in large product recalls. In Australia and New Zealand 2003, the recalls extended to many sesame- based products and triggered recalls in Canada and the United Kingdom of Great Britain and Northern Ireland. The United States of America as another example reported recalls associated with outbreaks in 2011 and 2013, and there were tahini recalls due to Salmonella contamination reported in 2007 and 2009 with no associated illness. TABLE A1.26 Summary table of globally reported outbreaks on seeds Seed category/ specific spice (Source) Microbial hazard(s) Outbreaks/ cases/ hospitalized/ deathsa Country (year)b Comments: susceptible populations/attack rate/concentration of microbial hazard in the product Sesame Seeds (Unicomb, 2005); (Anon., 2003); (Anon., 2012); (Anon., 2013); (Aavitsland et al., 2001); (Brockmann, 2001); (De Jong et al., 2001); (Little, 2001); (O’Grady, 2001) Salmonella Montevideo, Bovismorbificans, Brandenburg, Mbandaka, Maastricht, Typhimurium DT104, Senftenberg, Oranienburg 7/327P, 11C/1/1 Australia (2002, 2003), New Zealand (2003, 2012), United States of America (1995E, 2011, 2013), Norway, Sweden and Australia (2001) Sesame seeds or products were imported from Egypt, Lebanon and Türkiye. Implicated product usually tahini and helva although some recalls involved more products not linked to human illness. Testing and product recalls occurred in all outbreaks except 1995 in the outbreak country and in other countries with no reported illness in 2001, 2003 & 2011. Hemp Seeds (Stocker et al., 2011) Salmonella Montevideo 1/4C, 34P/3/0 Germany (2010) The contaminated product was an herbal diet supplement. The supplement and hemp flour at the mill tested positive. a Superscript C indicates confirmed cases; p indicates presumptive cases. b Superscript E indicates the link between human cases and implicated product was epidemiological only; otherwise, the link was laboratory confirmed. A1.11.4 Prevalence A total of 18 studies containing 86 unique trials were identified that investigated the prevalence and/or concentration of one or more selected microbial hazards in edible seeds, which were summarized in the following categories: sesame seeds, RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 174 halva/helva, and other/unspecified seeds. The median publication year was 2010 (range 1995–2014). Most studies were conducted in Europe (67 percent) > Asia/ the Middle East (22 percent) > the United States of America (11 percent). Most studies (61 percent) sampled products during a specific or defined period, while seven reported on the results of systematic surveillance programmes. More than 60 percent of studies sampled products at retail (e.g. markets and grocery stores), while two sampled from manufacturing and processing facilities and two from imported products. Only 4/18 studies (22 percent) specified the country(s) of product origin. Salmonella spp. was the most investigated microbial hazard across all seed categories. It was found at a low average prevalence in other (alfalfa, flax, hemp, karela, melon, poppy, pumpkin, and sunflower) and mixed/unspecified seeds (0.5 percent) and halva/helva (6.0 percent), and a low median prevalence in sesame seeds (6.5 percent). An average prevalence of 9.1 (95 percent CI: 8.2–10.0) was identified for generic E. coli in poppy and unspecified seeds in two studies, respectively, with nearly all observations coming from a retail survey of unspecified seeds for consumption in the United Kingdom of Great Britain and Northern Ireland (Willis et al., 2009). Only one study conducted in Germany sampled sesame products other than seeds and halva/helva (not shown in the table below), finding Salmonella spp. in 1/12 samples of tahini (produced in Türkiye) and 0/6 samples of sesame cereal (Brockmann et al., 2004). B. cereus was identified at an average prevalence of 7.0 (95 percent CI: 0.4 to 18.9) in other seeds for consumption (flax, karela, poppy, pumpkin, sunflower) in three studies, while Cronobacter spp. was identified at highly variable (9–67 percent) prevalence levels across three trials in two studies of poppy, pumpkin and sesame seeds, respectively. Enterobacteriaceae was found in only one study, in 6/6 samples of retail poppy seeds from India (Banerjee and Sarkar, 2003). C. perfringens, E. coli O157:H7, L. monocytogenes and S. aureus were not identified in any study. Few studies reported extractable concentration data on levels of selected microbial hazards in seeds and seed products (not shown in the table below). Average concentrations of Salmonella spp. in halva from Türkiye ranged with 3.8 to 87 CFU/g, with minimum and maximum values ranging from <10 to 850 CFU/g (Sengun et al., 2005). In another study of halva from Greek manufacturing plants, average concentrations of Enterobacteriaceae and S. aureus ranged from <10–30 CFU/g and 70–80 CFU/g, respectively (Kotzekidou, 1998). ANNEX 1 175 TABLE A1.27 Prevalence of selected microbial hazards within seed categories (Each cell includes the number of observations/trials/studies contributing to the average or median prevalence estimate, the proportion of trials that did not find any positive samples and measures of heterogeneity and risk of selection bias. See the table footnotes for detailed explanations on each of these parameters.) Seeds Number of observations/trials/studies (% trials with zero prevalence)a Meta-analysis prevalence (%) estimates (95% CI) OR prevalence median (range)b Heterogeneity rating/Risk of selection bias (low, medium or high)c Microbial hazard Sesame seeds Halva/helva Other/unspecified seedsd B. cereus 4/1/1 (100%) 0 N/A/High N/A 30/6/3 (83%) 7.0 (0.4–18.9)M Low/High C. perfringens N/A N/A 6/1/1 (100%) 0 N/A/Low Cronobacter spp. 12/1/1 (0%) 67 N/A/High N/A 22/2/1 (0%) 27.3 (9.1–5.5)R High/High Generic E. coli 1/1/1 (100%) 0 N/A/High N/A 3741/2/2 (50%) 9.1 (8.2–10.0)M Low/Low E. coli O157:H7 N/A N/A 66/4/1 (100%) 0 (0–0)R Low/High Enterobacteriaceae N/A 63/1/1 (100%) 0 N/A/High 6/1/1 (0%) 100 N/A/Low L. monocytogenes N/A N/A 15/3/1 (100%) 0 (0–0)R Low/High S. aureus N/A 69/2/2 (100%) 0 (0–0)R Low/High 6/1/1 (100%) 0 N/A/Low Salmonella spp. 965/4/4 (25%) 6.5 (0–12.5)R High/Med. 97/3/2 (67%) 6.0 (0–15.6)M Med./High 3509/15/5 (53%) 0.5 (0.1–1.1)M Med./Low N/A = No data identified for this product-hazard combination. Med. = medium. a Observations/trials/studies: The observations are the total number of samples for all studies included in the summarized category. The number of studies is the number of articles captured. In some cases, articles report data on multiple prevalence trials or sampling frames. While the observations for each trial are independent by time and sample, they are part of a larger study where the methods and investigators are the same. Thus, there is not full independence in these observations, and we note this by acknowledging there are multiple trials within a study. b Superscript M indicates an average prevalence estimate (and 95 percent confidence interval) from a random-effects meta-analysis. Meta-analysis estimates were calculated only if heterogeneity was low or medium (I2 0-60 percent) and if at least one trial found a positive sample. Superscript R indicates a median (and range) of trial prevalence estimates, calculated if heterogeneity was high (I2 >60 percent). Ranges not provided when only one trial was identified. (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 176 c I2 is a measure of the degree of heterogeneity between trials combined in the meta-analysis. Heterogeneity rating definitions: low = I2 0-30 percent; medium = 31–60 percent; high = >60 percent. Selection bias rating definitions: high = 0–30 percent of trials used a representative sample; medium = 31–60 percent of trials used a representative sample; low = >60 percent of trials used a representative sample. Studies that conducted random or systematic sampling were considered representative. The overall robustness of the meta-analysis prevalence estimates can be inferred from the heterogeneity and selection bias ratings. Taking into consideration the number of studies in the meta-analysis, high confidence in the meta-analysis results can be inferred when heterogeneity is low and the risk of selection bias is low, and low confidence can be inferred when both are high; see the methods section (page 11) for more information. d “Other” seeds included the following for each microbial hazard: B. cereus (flax, karela, poppy, pumpkin and sunflower); C. perfingens, Enterobacteriaceae, and S. aureus (poppy); Cronobacter spp. (poppy, pumpkin); E. coli (poppy, mixed/unspecified); E. coli O157:H7 (melon, pumpkin, sunflower and watermelon); L. monocytogenes (karela, pumpkin, sunflower); Salmonella spp. (alfalfa, flax, hemp, karela, melon, poppy, pumpkin, sunflower and mixed/unspecified). A1.11.5 Interventions A total of only four experimental studies (consisting of eight unique trials) were identified evaluating the effects of various interventions to reduce contamination of microbial hazards in seeds: specifically, sesame seeds or their products, tahini and halva/helva. The median publication year was 2009 (range 1998 to 2013). The studies were conducted in Türkiye (n=2), Greece and Jordan. All studies reported on challenge trials with artificially inoculated samples, while one also included a controlled trial. None of the studies were conducted under commercial conditions, and they all included only a small number of samples (2–6 replicates per intervention combination). Two studies each investigated the effect of various storage and packaging conditions on Enterobacteriaceae, E. coli O157:H7, S. aureus, and Salmonella spp. in halva/ helva and tahini paste. Microbial hazards were reduced but not necessarily to levels that did not constitute any risk to human health during storage at higher temperatures and at higher levels of initial contamination. One study found that roasting sesame seeds for 60 min can reduce Salmonella counts by >5 logs, but these roasting conditions could affect consumer acceptability of the final product (Torlak, Sert and Serin, 2013). Given the potential for microbial hazards to survive sesame seed processing and storage, and for subsequent cross-contamination, good agricultural and manufacturing practices, and hazard analysis critical control point (HACCP) food safety management systems should be implemented during sesame seed harvesting and throughout the production process (Al-Nabulsi et al., 2013; Torlak, Sert and Serin, 2013). ANNEX 1 177 TABLE A1.28 Forest plot of the prevalence of selected microbial hazards within seed categories Microbial hazard/LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs. /trials/ studies Heterogeneity Selection bias Median (range) B. cereus Sesame seeds 0.0 - - 4/1/1 N/A High - Other/ unspecified seeds 7.0 0.4 18.9 30/6/3 Low High - Overall 6.7 0.5 17.6 Low - Cronobacter spp. Sesame seeds 66.7 - - 12/1/1 N/A High - Other/ unspecified seeds 7.0 0.3 18.9 22/2/1 High High 27.3 (9.1–45.5) Overall 38.6 7.5 75.1 High 45.5 (9.1–66.7) Generic E. coli Sesame seeds 0.0 - - 1/1/1 N/A High - Other/ unspecified seeds 9.1 8.2 10.0 3 741/2/2 Low Low - Overall 9.1 8.2 10.0 Low - Salmonella spp. Sesame seeds 6.2 0.0 18.2 965/4/4 High Med. 6.5 (0–12.5) Halva/helva 6.0 0.0 15.6 97/3/2 Med. High - Other/ unspecified seeds 0.5 0.1 1.1 3 509/15/5 Med. Low - Overall 1.9 0.8 3.3 High 0.1 (0–16.7) CI = confidence interval; Med = medium; No. obs. = number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: C. perfringens, E. coli O157, L. monocytogenes and S. aureus evidence is not shown in this figure because no positive samples were identified in these categories. LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 178 TA B LE A 1. 29 S um m ar y ta bl e of e xp er im en ta l s tu di es e va lu at in g th e eff ec ts o f i nt er ve nt io ns t o re du ce c on ta m in at io n of s el ec te d m ic ro bi al ha za rd s in s ee ds Fo od ca te go ry In te rv en ti on ty pe In te rv en ti on d et ai ls (d os e an d/ or d ur at io n) So ur ce (s ) M ic ro bi al ha za rd (s ) St ud y ty pe a N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io n H al va / he lv a M od ifi ed pa ck ag in g V ac uu m v s. a ir -s ea le d (6 da ys t o 8 m on th s) (K ot ze ki du , 19 98 ) E nt er ob ac - te ri ac ea e C .T . 1/ 1 0 10 0 M od ifi ed pa ck ag in g V ac uu m v s. a ir -s ea le d (6 da ys t o 8 m on th s) (K ot ze ki du , 19 98 ) S al m on el la sp p. C h. T. 1/ 1 10 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (6 –2 0 °C ; 6 d ay s to 8 m on th s) (K ot ze ki du , 19 98 ) E nt er ob ac - te ri ac ea e C .T . 1/ 1 0 10 0 St or ag e co nd it io ns 4 a nd 2 0 °C ; 1 –9 m on th s (S en gu n et al ., 20 0 5) S . a ur eu s C h. T. 1/ 1 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (6 –2 0 °C ; 6 d ay s to 8 m on th s) (K ot ze ki du , 19 98 ) S al m on el la sp p. C h. T. 1/ 1 10 0 10 0 Se sa m e se ed s H ea t tr ea tm en t R oa st in g (1 10 –1 50 °C ; 10 –6 0 m in ) (T or la k an d Se ri n, 2 0 13 ) S al m on el la sp p. C h. T. 1/ 1 0 10 0 Ta hi ni St or ag e co nd it io ns In cr ea se d te m pe ra tu re (1 0 –3 7° C ; 1 –2 8 da ys ) (A l- N ab ul si et a l., 2 0 13 ) E . c ol i O 15 7: H 7 C h. T. 1/ 1 10 0 10 0 St or ag e co nd it io ns In cr ea se d te m pe ra tu re (4 an d 22 °C ; 1 –1 6 w ee ks ) (T or la k an d Se ri n, 2 0 13 ) S al m on el la sp p. C h. T. 1/ 1 0 10 0 a C h. T. = c ha lle ng e tr ia l; C .T . = c on tr ol le d tr ia l. ANNEX 1 179 A1.11.6 References in A1.11 References used in summary narrative: Al-Nabulsi, A., Osaili, T. M., Shaker, R. R., Olaimat, A. N., Attlee, A., Al-Holy, M., Holley, R. & A. 2013. Survival of E. coli O157:H7 and Listeria innocua in tahini (sesame paste). Journal of Food, Agriculture and Environment, 11(3–4): 303–306. Banerjee, M. & Sarkar, P. K. 2003. Microbiological quality of some retail spices in India. Food Research International, 36(5): 469–474. Brockmann, S. O., Piechotowski, I. & Kimmig, P. 2004. Salmonella in sesame seed products. Journal of Food Protection, 67(1): 178-180. FAO. 1995. Edible nuts [online]. Non-wood forest products 5. [Cited 20 July 2021]. http:// www.fao.org/3/v8929e/v8929e.pdf Kotzekidou, P. 1998. Microbial stability and fate of Salmonella Enteritidis in halva, a low- moisture confection. Journal of Food Protection, 61(2): 181–185. Sengun, I. Y., Hancioglu, O. & Karapinar, M. 2005. Microbiological profile of helva sold at retail markets in Izmir City and the survival of Staphylococcus aureus in this product. Food Control, 16(10): 840–844. Torlak, E., Sert, D. & Serin, P. 2013. Fate of Salmonella during sesame seeds roasting and storage of tahini. International Journal of Food Microbiology, 163(2–3): 214–217. Willis, C., Little, C. L., Sagoo, S., de Pinna, E. & Threlfall, J. 2009. Assessment of the microbiological safety of edible dried seeds from retail premises in the United Kingdom with a focus on Salmonella spp. Food Microbiology, 26(8): 847–852. Citation list of burden of illness studies (n= unique citations): (Distiller ID = Ref #, Outbreak # =OB # where a Distiller ID is not available – for unpublished outbreaks) Aavitsland P., Alvseike, O., Guérin, P. J. & Stavnes, T. L. 2001. International outbreak of Salmonella Typhimurium DT104 – update from Norway. Eurosurveillance, (5): 1701. Ref #: 6600. Anonymous. 2003. Foodborne disease in Australia: incidence, notifications and outbreaks. Annual report of the OzFoodNet network, 2002. Communicable Diseases Intelligence Report, 27(2): 209–243. Ref #: 2250. Anonymous. 2012. Multistate outbreak of Salmonella serotype Bovismorbificans infections associated with hummus and tahini–United States, 2011. MMWR Morb Mortal Wkly Rep., 61(46): 944–947. Ref #: 275. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 180 Anonymous. 2014. Human Salmonella isolates, 2012: National cluster of Salmonellosis linked to imported contaminated tahini. In: Public Health Surveillance, Information for New Zealand Public Health Action [online]. Wellington, New Zeland. [Cited 20 July 2021]. https://surv.esr.cri.nz/index.php?we_objectID=3315 . OB#=280. Anonymous. 2013. Multistate Outbreak of Salmonella Montevideo and Salmonella Mbandaka Infections linked to Tahini Sesame paste (final update). In: Centers for Disease Control and Prevention (CDC) [online]. Atlanta, Georgia. [Cited 20 July 2021]. http://www.cdc.gov/salmonella/montevideo-tahini-05-13/. OB#=206. Bouckley, B. 2011. EC bans Egyptian seed imports as fenugreek linked to deadly E. coli outbreaks. Food Manufacture: (7). Ref #: 4724. Brockmann. S. 2001. International outbreak of Salmonella Typhimurium DT104 due to contaminated sesame seed products – update from Germany (Baden- Werttemberg). Eurosurveillance, (5): 1699. Ref #: 6613. de Jong B., Andersson, Y., Giesecke, J., Hellström, L., Stamer, U. & Wollin, R. 2001. Salmonella Typhimurium outbreak in Sweden from contaminated jars of helva (or halva). Eurosurveillance, (5): 1698. Ref #: 6627. King, L. A., Nogareda, F., Weill, F. X., Mariani-Kurkdjian, P., Loukiadis, E., Gault, G., Jourdan-DaSilva, N., Bingen, E., Mace, M., Thevenot, D., Ong, N., Castor, C., Noel, H., Van Cauteren, D., Charron, M., Vaillant, V., Aldabe, B., Goulet, V., Delmas, G., Couturier, E., Le Strat, Y., Combe, C., Delmas, Y., Terrier, F., Vendrely, B., Rolland, P. & de Valk, H. 2012. Outbreak of Shiga toxin-producing Escherichia coli O104:H4 associated with organic fenugreek sprouts, France, June 2011. Clinical Infectious Diseases, 54(11): 1588–1594. Ref #: 460. Little. C. 2001. International outbreak of Salmonella Typhimurium DT104 – update from the United Kingdom. Eurosurveillance, (5): 1700. Ref #: 6677. O Grady, K. 2011. Salmonella typhimurium DT104 - Australia, Sweden. Pro-MED Mail, 20010822.1980. Ref #: 6685. Robert Koch Institute. 2011. Report: Final presentation and evaluation of epidemiological findings in the EHEC O104:H4 outbreak, Germany 2011. Berlin, Germany. (also available at https://www.rki.de/EN/Content/infections/epidemiology/outbreaks/ EHEC_O104/EHEC_final_report.pdf?__blob=publicationFile). Ref #:OB#288. Stocker, P., Rosner, B., Werber, D., Kirchner, M., Reinecke, A., Wichmann-Schauer, H., Prager, R., Rabsch, W. & Frank, C. 2011. Outbreak of Salmonella Montevideo associated with a dietary food supplement flagged in the Rapid Alert System for Food and Feed (RASFF) in Germany, 2010. Eurosurveillance, 16(50): 20040. Ref #: 521. ANNEX 1 181 Unicomb, L. E., Simmons, G., Merritt, T., Gregory, J., Nicol, C., Jelfs, P., Kirk, M., Tan, A., Thomson, R., Adamopoulos, J., Little, C. L., Currie, A. & Dalton, C. B. 2005. Sesame seed products contaminated with Salmonella: three outbreaks associated with tahini. Epidemiol Infect., 133(6): 1065–1072. Ref #: 1900. Citation list of prevalence studies (N=18) (Distiller ID = Ref #) Alwakee, S. S. & Nasser, L. A. 2011. Microbial contamination and mycotoxins from nuts in Riyadh, Saudi Arabia. American Journal of Food Technology, 6(8): 613–630. Ref #: 4757. Banerjee, M. & Sarkar, P. K. 2003. Microbiological quality of some retail spices in India. Food Research International, 36(5): 469–474. Ref #: 6610. Brockmann, S. O., Piechotowski, I. & Kimmig, P. 2004. Salmonella in sesame seed products. Journal of Food Protection, 67(1): 178–180. Ref #: 2194. EFSA & ECDC. 2010. The community summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in the European Union in 2008. EFSA Journal, 8: 1496. Ref #: 6637. EFSA & ECDC. 2011. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2009. EFSA Journal, 9(3): 2090. Ref #: 6636. EFSA & ECDC. 2012. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2010. EFSA Journal, 10(3): 2597. Ref #: 6757. EFSA & ECDC. 2013. The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2011. EFSA Journal, 11(4): 3129. Ref #: 6756. Hochel, I., Ruzickova, H., Krasny, L. & Demnerova, K. 2012. Occurrence of Cronobacter spp. in retail foods. Journal of Applied Microbiology, 112(6): 1257–1265. Ref #: 463. Kolevska, I. S. & Kocic, B. 2009. Food contamination with Salmonella species in the Republic of Macedonia. Foodborne Pathogens and Disease, 6(5): 627–630. Ref #: 1155. Kotzekidou, P. 1998. Microbial stability and fate of Salmonella Enteritidis in halva, a low-moisture confection. Journal of Food Protection, 61(2): 181–185. Ref #: 2778. Mozrova, V., Brenova, N., Mrazek, J., Lukesova, D. & Marounek, M. 2014. Surveillance and characterisation of Cronobacter spp. in Czech retail food and environmental samples. Folia Microbiologica, 59(1): 63–68. Ref #: 95. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 182 Rosenkvist, H. & Hansen, Ã. 1995. Contamination profiles and characterisation of Bacillus species in wheat bread and raw materials for bread production. International Journal of Food Microbiology, 26(3): 353–363. Ref #: 6283. Sengun, I. Y., Hancioglu, O. & Karapinar, M. 2005. Microbiological profile of helva sold at retail markets in Izmir City and the survival of Staphylococcus aureus in this product. Food Control, 16(10): 840–844. Ref #: 5669. Stankovic, N., Comic, L. & Kocic, B. 2006. Microbiological correctness of spices on sale in health food stores and supermarkets in Nis. Acta Facultatis Medicae Naissensis, 23(2): 79–84. Ref #: 6745. Van Doren, J. M., Blodgett, R. J., Pouillot, R., Westerman, A., Kleinmeier, D., Ziobro, G. C., Ma, Y., Hammack, T. S., Gill, V., Muckenfuss, M. F. & Fabbri, L. 2013. Prevalence, level and distribution of Salmonella in shipments of imported capsicum and sesame seed spice offered for entry to the United States: Observations and modeling results. Food Microbiology, 36(2): 149–160. Ref #: 69. Van Doren, J.M., Kleinmeier, D., Hammack, T.S. & Westerman, A. 2013a. Prevalence, serotype diversity, and antimicrobial resistance of Salmonella in imported shipments of spice offered for entry to the United States, FY2007-FY2009. Food Microbiology, 34: 239–251. Ref #: 169. Vural, A. & Erkan, M. E. 2008. The research of microbiological quality in some edible nut kinds. Journal of Food Technology, 6(1): 25–28. Ref #: 6750. Willis, C., Little, C. L., Sagoo, S., de Pinna, E. & Threlfall, J. 2009. Assessment of the microbiological safety of edible dried seeds from retail premises in the United Kingdom with a focus on Salmonella spp. Food Microbiology, 26(8): 847–852. Ref #: 1080. Citation list of interventions studies (N=4): (Distiller ID = Rec #) Al-Nabulsi, A., Osaili, T. M., Shaker, R. R., Olaimat, A. N., Attlee, A., Al-Holy, M., Elabedeen, N. Z., Jaradat, Z. W. & Holley, R. A. 2013. Survival of E. coli O157:H7 and Listeria innocua in tahini (sesame paste). Journal of Food, Agriculture and Environment, 11(3-4): 303–306. Ref #: 4128. Kotzekidou, P. 1998. Microbial stability and fate of Salmonella Enteritidis in halva, a low-moisture confection. Journal of Food Protection, 61(2): 181–185. Ref #: 2778. Sengun, I. Y., Hancioglu, O. & Karapinar, M. 2005. Microbiological profile of helva sold at retail markets in Izmir City and the survival of Staphylococcus aureus in this product. Food Control, 16(10): 840–844. Ref #: 5669. Torlak, E., Sert, D. & Serin, P. 2013. Fate of Salmonella during sesame seeds roasting and storage of tahini. International Journal of Food Microbiology, 163(2–3): 214–217. Ref #: 160. ANNEX 1 183 A1.12 SUMMARY CARD: SPICES, DRIED HERBS AND TEA A1.12.1 Low-moisture food category description Spices are dried parts of fruits, seeds, bark, roots, leaves, or flowers of plants and herbs (EFSA, 2013; USFDA, 2013). They are often ground, crushed, or otherwise processed and used for seasoning, flavouring and/or preserving foods (EFSA, 2013; USFDA, 2013). For the purposes of this summary, and due to their similar nature, spices (including dried herbs) have been combined with tea – an aromatic beverage prepared by mixing hot water with dried leaves of the tea plant and/or other dried herbs such as chamomile. To facilitate summary and interpretation of this large area of research, “spices” have been grouped into hierarchical categories based primarily on the part of the plant from which they originated (Sagoo et al., 2009; USFDA, 2013; Van Doren et al., 2013a). Categories were also created for mixed/unspecified spices and dried herbs, and for tea (Appendix G: Spice Classification Table). A1.12.2 Evidence summary In total, 129 articles16 and outbreak reports17 were identified that investigated the burden of illness related to spices, the prevalence or contamination of selected microbial hazards in spices, and/or interventions to reduce contamination of microbial hazards in spices. The distribution of identified research stratified by microbial hazard investigated and research focus is shown in Appendix F: Summary Card Evidence Charts. Salmonella spp. was the most frequently investigated microbial hazard in spices for burden of illness (n=13 articles and outbreak reports), prevalence (n=42 articles), and intervention (n=12 articles) information. A1.12.3 Burden of illness Burden of illness evidence related to spices includes 28 reported outbreaks and non-outbreak burden of illness information in one cohort study and two case-control studies. Outbreaks affected 2 228 individuals, including 134 hospitalizations and two deaths between 1973 and 2012. Outbreaks were generally small: median 20 (range 1–1 000); however, they can be very large. Spice outbreaks, shown in the summary table below, were reported from Denmark (9), the United 16 Articles refer to peer-reviewed journal publications as well as government and research agency reports. 17 For burden of illness information, multiple articles often reported complementary and/or overlapping information on the same outbreak. In addition, outbreak data were supplemented from other literature sources, including line lists from various countries, news reports, or annual summaries of country outbreaks. Thus, to avoid counting the same outbreak more than once, the term “outbreak report” is used instead of “article” to count the total number of unique outbreaks. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 184 States of America (4), Finland (3), the United Kingdom of Great Britain and Northern Ireland (2), Germany, Norway, Canada, France, Hungary and Belgium. Several outbreaks occurred where the spice was added to the food product after the final pathogen reduction step. Spice outbreaks are likely significantly underreported as they are usually consumed in mixed ingredient foods and in small amounts. Salmonella spp. accounted for 77 percent of illnesses associated with spices > B. cereus 19.7 percent > C. perferingens 2.8 percent > C. botulinum 0.04 percent. A case-control study examining source association with Salmonella Enteritidis cases (n=719) in Germany found the consumption of dried herbs was associated with infection; OR 1.4 (95 percent CI: 1.04-1.73) (Ziehm et al., 2013). Ten of the 28 outbreaks (1973–2012) implicated black or white pepper as the contaminated ingredient. Other spices were implicated in one or two outbreaks each. All outbreaks associated with tea were in infants less than 18 months old in Germany, Serbia and Portugal and are detailed in the summary table below. One case-control study implicated tea in association with B. cereus infection in child cancer patients (El Saleeby et al., 2004). In contrast, a cohort study of Mexican infants from 0–1 year old (n=98) found that herbal tea was protective against diarrhea; hazard ratio 0.11 (95 percent CI: 0.067 to 0.62) (Long et al., 1994). TABLE A1.30 Summary table of globally reported outbreaks on spices Spice category/ specific spice (Source) Microbial hazard(s) Outbreaks/ cases/ hospitalized/ deathsa Country (year)b Comments: susceptible populations/attack rate/concentration of microbial hazard in the product Bark/flowers         Cinnamon (EU, No date) B. cereus 1/30c/0/0 Denmark (2011) Concentration: 5 000 organisms/g. Root         Turmeric (EFSA, 2013) B. cereus 2/23c/0/0 Finland (2011)   Fruit/seed         Cumin (EFSA, 2013) B. cereus C. perfringens Salmonella Caracas 1/3c/0/0 Finland (2011) Concentration: B. cereus 16 000 CFU/g, C. perfringens 180 CFU/g and S. Caracas presence/25 g. (cont.) ANNEX 1 185 Spice category/ specific spice (Source) Microbial hazard(s) Outbreaks/ cases/ hospitalized/ deathsa Country (year)b Comments: susceptible populations/attack rate/concentration of microbial hazard in the product Capsicum spp. Dried chilies (EU, No date) C. perfringens 1/3c/0/0 Denmark (2011) Red Pepper (EU, No date) C. perfringens 1/37c/0/0 Denmark (2011) Paprika (Anon., No date) B. cereus 1/48c/0/0 Denmark (2009)   (Lehmacher, Bockemuhl and Aleksic, 1995) Salmonella Saintpaul, Rubislaw, Javiana (94 serovars isolated) 1/1000c/0/0 Germany (1993) Implicated paprika on potato chips. Attack rate= 1/1 000. Mostly affected children <14 years old. Concentrations: chips 0.04–11 MPN/g; paprika 2.5 MPN/g; spice mixture 0.04–0.4MPN/g. Piper nigrum Black pepper (EU, No date; EFSA, 2012a) C. perfringens 2/19c/0/0 Denmark (2011) Concentration 330 mill./g of pepper. (EFSA, 2013; Van Doren et al., 2013b) B. cereus 2/164c/0/0 Denmark (2010E & 2011)   (Gieraltowski et al., 2013; Gustavsen and Breen, 1984; Little, Omotoye and Mitchell, 2003; Van Doren et al., 2013b) Salmonella Weltevreden, Oranienburg, Enteritidis PT4, Montevideo, Seftenberg & Rissen 6/521c/94/2 Canada (1973), Norway (1981), United Kingdom of Great Britain and Northern Ireland (1996), United States of America (2009, 2009, 2008) Black pepper originated from India, Brazil [0.1 to >2.4 MPN/g], Viet Nam & China. White pepper from Viet Nam. Red pepper from India implicated in two outbreaks with black pepper. Mixed spices         Garlic salt & black pepper mix (Raevuori et al., 1976) B. cereus 1/18c/0/0 Finland (1975) Attack rate 50%, Concentration: garlic salt 100 organisms/g, white pepper 4 500 organisms/g. BBQ spices (EU, No date) C. perfringens 1/4c/0/0 Denmark (2011)   (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 186 Spice category/ specific spice (Source) Microbial hazard(s) Outbreaks/ cases/ hospitalized/ deathsa Country (year)b Comments: susceptible populations/attack rate/concentration of microbial hazard in the product Seasoning mix (Sotir et al., 2009) Salmonella Wandsworth & Typhimurium 1/87c/8/0 United States of America (2007) Seasoning applied to commercial puffed vegetable coated ready-to-eat snack after final pathogen reduction step. Spice blend (Van Doren et al., 2013b) B. cereus 1/146c/0/0 France (2007) Outbreak in school children. (EFSA, 2012b) Salmonella Enteritidis 1/41/6/0 Hungary (2012) EU category of herbs and spices. Curry powder (Van Doren et al. 2013b) Salmonella Braenderup 1/20c/1/0 United Kingdom of Great Britain and Northern Ireland (2002) Spice originated from India. (EFSA, 2013) B. cereus 1/7c/0/0 Belgium (2009)   a Superscipt C indicates confirmed cases; p indicates presumptive cases. b Superscript E indicates the link between human cases and implicated product was epidemiological only; otherwise, the link was laboratory confirmed. TABLE A1.31 Summary of globally reported outbreaks related to tea Tea category/ specific tea (Source) Microbial hazard(s) Outbreaks/ casesa/ hospitalized/ deaths Country (year)b Comments: susceptible populations/attack rate/concentration of microbial hazard in the product Tea         Chamomile tea (Saraiva et al., 2012) C. botulinum 1/1c/0/0 Portugal (2009) Case of infant botulism, both honey and chamomile tested positive. Anise seed in tea (Koch et al., 2005) Salmonella 1/42c/21/0 Germany (2002) Cases, infants <13 months. Anise seed (Pimpinella anisum) from Türkiye. Concentration: 0.036 MPN/g. Fennel seed in tea (Ilic, Duric and Grego, 2010) Salmonella 1/14c/4/0 Serbia (2007) Cases, infants <12 months. Fennel seed (Foeniculum vulgare) a Superscript C indicates confirmed cases; p indicates presumptive cases. b Superscript E indicates the link between human cases and implicated product was epidemiological only; otherwise, the link was laboratory confirmed. ANNEX 1 187 A1.12.4 Prevalence A total of 77 studies containing 1 275 unique trials were identified that investigated the prevalence and/or concentration of one or more selected microbial hazards in spices. The median publication year was 2009 (range 1991–2014). Most studies (>69 percent) were conducted in Europe (n=32) and Asia/the Middle East (n=21). Most studies (84 percent) sampled products during a specific or defined period, while two conducted sampling over multiple time points, and ten reported on the results of systematic surveillance programmes. Studies primarily sampled products at retail (e.g. markets and grocery stores) and/or from manufacturing plants (75 percent). Only eight studies specified the country(s) of product origin, while 12 studies sampled products produced in the country where the study was conducted. Salmonella spp. was the most investigated microbial hazard across most spice categories. Both Salmonella and S. aureus were infrequently isolated from most trials; in many cases, only one or a few trials found positive results for these pathogens. However, the prevalence estimates and ranges shown in the summary table indicate the potential for high contamination if appropriate good production and manufacturing practices are not followed (ASTA, 2011; USFDA, 2013). A summary of USFDA spice recalls (1970–2003) recorded 17 recalls all due to Salmonella contamination in spices and dried herbs (Vij et al., 2006). Generic E. coli was also infrequently found in prevalence trials except in the mixed/unspecified spice category, where it was found in 75 percent of trials with a median prevalence of 11 percent and range of 0–33 percent. B. cereus, C. perfringens, Cronobacter spp. and Enterobacteriaceae were found at variable and wideranging prevalence levels across most spice categories. When meta-analysis was possible for these hazards, average prevalence estimates ranged from 6 percent (95 percent CI: 3–7 percent) for C. perfringens in dried herbs to 37 percent (95 percent CI: 29–45 percent) for Enterobacteriaceae in fruit/seed spices. Some trials found very high prevalence levels (approaching 100 percent) for certain hazard/spice combinations. While most trials that investigated C. perfringens used a representative sample (i.e. samples were randomly or systematically selected), the opposite was true for Cronobacter spp., as the latter trials tended to sample multiple low-moisture and other food products and spices comprised only a small and non-representative category. Comparatively little research was identified in teas. Three studies from Argentina found a low to moderate prevalence of C. botulinum in tea (Bianco et al., 2008, RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 188 2009; De Jong et al., 2003), while the prevalence of other microbial hazards (e.g. Cronobacter spp. and generic E. coli) varied widely across difference studies. E. coli O157:H7 and L. monocytogenes were not isolated from spices or teas in any study. Only three studies were identified that reported extractable concentration (CFU or MPN) data for Enterobacteriaceae (Witkowska et al., 2011) and generic E. coli (Koohy-Kamaly-Dehkordy et al., 2013), respectively, in various spices, and C. botulinum in tea (De Jong et al., 2003), with an associated measure of variability (e.g. confidence interval and/or standard deviation). These data are summarized in a table below. There were 34 studies that measured concentration data for selected microbial hazards in spices, but these trials were excluded from this summary because they did not have appropriate extractable data. Required extractable data included a mean concentration value, a measure of variability, and the sample size. In addition, eight studies reported the prevalence of selected microbial hazards in spice shipments or batch samples (data not shown in the table below). A list of these studies can be found in Appendix H: Articles reporting non-extractable concentration data and prevalence in batch samples for spices, dried herbs and tea. The data reinforces that many spices can be contaminated, sometimes at a very high prevalence, with various microbial hazards. ANNEX 1 189 TA B LE A 1. 32 P re va le nc e of s el ec te d m ic ro bi al h az ar ds w it hi n sp ic e ca te go ri es E ac h ce ll in cl ud es t he n um be r of o bs er va ti on s/ tr ia ls /s tu di es c on tr ib ut in g to t he a ve ra ge o r m ed ia n pr ev al en ce e st im at e, t he p ro po rt io n of t ri al s th at d id n ot fi nd a ny p os it iv e sa m pl es a nd m ea su re s of h et er og en ei ty a nd r is k of s el ec ti on b ia s. S ee t he t ab le fo ot no te s fo r de ta ile d ex pl an at io ns o n ea ch o f t he se p ar am et er s. Sp ic e Ca te go ry N um be r of o bs er va ti on s/ tr ia ls /s tu di es (% tr ia ls w it h ze ro p re va le nc e) a M et a- an al ys is p re va le nc e (% ) e st im at es (9 5% C I) O R p re va le nc e m ed ia n (r an ge )b H et er og en ei ty r at in g/ R is k of s el ec ti on b ia s (l ow , m ed iu m o r hi gh )c M ic ro bi al h az ar d B ar k/ flo w er Fr ui t/ se ed H er bs M ix ed R oo t Te a B . c er eu s 15 4 /1 2/ 5 (5 0 % ) 1. 9 (0 –6 0 )R H ig h/ M ed . 10 0 1/ 76 /9 (4 2% ) 11 .7 (0 –8 5. 7) R H ig h/ Lo w 20 7/ 20 /5 (6 0 % ) 0 (0 –7 5) R H ig h/ M ed . 4 4 68 /2 0 /1 4 (1 0 % ) 26 .9 (0 –6 8. 8) R H ig h/ Lo w 14 2/ 15 /5 (4 0 % ) 20 .2 (1 0 .0 –3 2. 6) M M ed ./ Lo w 1/ 1/ 1 ( 10 0 % ) 0 n/ a/ H ig h C . b ot ul in um N /a N /a N /a 65 /1 /1 (1 0 0 % ) 0 n/ a/ H ig h N /a 4 23 /3 /3 (0 % ) 7. 5 (1 .5 –2 6. 1) R H ig h/ H ig h C . p er fr in g en s 11 4 /9 /4 (6 7% ) 0 (0 –4 6. 8) R H ig h/ Lo w 32 4 /7 6/ 4 9 (6 9% ) 10 .3 (7 .3 –1 3. 6) M Lo w /L ow 19 6/ 12 /5 (6 7% ) 6. 0 (3 .1 –9 .7 )M Lo w /L ow 38 89 /1 1/ 6 (4 5% ) 1. 4 (0 –3 2. 7) R H ig h/ Lo w 10 7/ 9/ 3 (7 8% ) 15 .0 (8 .9 –2 2. 3) M Lo w /L ow N /a C ro n ob ac te r sp p. 19 /4 /3 (7 5% ) 12 .4 (0 –3 4 .3 )M Lo w /H ig h 83 /1 8/ 3 (2 2% ) 34 .8 (2 0 .3 –5 0 .8 )M M ed ./ H ig h 51 /6 /3 (5 0 % ) 18 .8 (7 .3 –3 3. 1) M Lo w /H ig h 34 1/ 13 /1 1 ( 23 % ) 26 .9 (0 –7 3. 3) R H ig h/ H ig h 17 /4 /2 (2 5% ) 35 .3 (1 4 .8 –5 8. 7) M Lo w /H ig h 20 9/ 22 /6 (2 7% ) 34 .4 (0 –7 5) R H ig h/ H ig h G en er ic E . c ol i 17 9/ 11 /7 (8 2% ) 4 .2 (1 .7 –7 .6 )M Lo w /M ed . 82 6/ 57 /9 (7 2% ) 10 .2 (7 .3 –1 3. 6) M M ed ./ M ed . 11 8/ 18 /6 (8 3% ) 0 (0 –7 0 .6 )R H ig h/ H ig h 30 4 5/ 8/ 6 (2 5% ) 11 .2 (0 –3 3. 3) R H ig h/ M ed . 17 6/ 11 /5 (7 5% ) 0 (0 –3 5. 4 )R H ig h/ Lo w 68 /7 /5 (5 7% ) 0 (0 –6 6. 7) R H ig h/ H ig h E . c ol i O 15 7: H 7 16 /2 /2 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 20 9/ 12 /3 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 32 /2 /2 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 2/ 1/ 1 ( 10 0 % ) 0 n/ a/ H ig h 4 /2 /1 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 22 /1 /1 (1 0 0 % ) 0 n/ a/ H ig h E nt er ob ac te ri ac ea e 12 7/ 11 /5 (7 7% ) 0 (0 –8 0 )R H ig h/ M ed . 25 6/ 51 /5 (4 3% ) 36 .6 (2 8. 6– 4 4 .9 )M M ed ./ M ed . 28 /1 2/ 3 (6 7% ) 24 .7 (1 1. 4 –4 0 .9 )M Lo w /H ig h 12 9/ 4 /3 (2 5% ) 35 .1 (2 7. 1– 4 3. 5) M Lo w /H ig h 35 /8 /3 (7 5% ) 9. 7 (2 .0 –2 1. 4 )M Lo w /L ow 1/ 1/ 1 ( 0 % ) 10 0 n/ a/ H ig h (c on t. ) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 190 Sp ic e Ca te go ry N um be r of o bs er va ti on s/ tr ia ls /s tu di es (% tr ia ls w it h ze ro p re va le nc e) a M et a- an al ys is p re va le nc e (% ) e st im at es (9 5% C I) O R p re va le nc e m ed ia n (r an ge )b H et er og en ei ty r at in g/ R is k of s el ec ti on b ia s (l ow , m ed iu m o r hi gh )c M ic ro bi al h az ar d B ar k/ flo w er Fr ui t/ se ed H er bs M ix ed R oo t Te a L. m on oc yt og en es 17 /5 /2 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 14 1/ 27 /3 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 68 /1 7/ 2 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 17 4 /6 /4 (1 0 0 % ) 0 (0 –0 )R Lo w /M ed . 32 /7 /2 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h N /a S . a ur eu s 19 5/ 16 /8 (9 4 % ) 2. 6 (0 .8 –5 .3 )M Lo w /M ed . 91 4 /8 9/ 10 (9 2% ) 5. 6 (4 .2 –7 .1 )M Lo w /L ow 25 5/ 25 /7 (9 6% ) 2. 4 (0 .9 –4 .7 )M Lo w /M ed . 13 2/ 9/ 4 (7 8% ) 2. 8 (0 .6 –6 .4 )M Lo w /M ed . 14 4 /1 6/ 6 (8 1% ) 10 .6 (6 .2 –1 6. 1) M Lo w /M ed . 89 /5 /2 (1 0 0 % ) 0 (0 –0 )R Lo w /L ow S al m on el la s pp . 30 6/ 26 /1 3 (9 6% ) 1. 8 (0 .6 –3 .6 )M Lo w /M ed . 28 32 /1 60 /2 0 (8 7% ) 2. 3 (1 .0 –3 .9 )M Lo w /M ed . 50 3/ 52 /1 2 (1 0 0 % ) 0 (0 –0 )R Lo w /H ig h 18 31 5/ 4 7/ 17 (6 0 % ) 0 (0 –1 4 )R H ig h/ Lo w 36 7/ 26 /1 1 ( 88 % ) 4 .4 (2 .5 –6 .7 )M Lo w /M ed . 13 8/ 8/ 3 (8 8% ) 3. 1 ( 0 –8 )M M ed ./ Lo w N /a = N o da ta id en ti fie d fo r th is p ro du ct -h az ar d co m bi na ti on . M ed . = m ed iu m . a O bs er va ti on s/ tr ia ls /s tu di es : T he o bs er va ti on s ar e th e to ta l n um be r of s am pl es f or a ll st ud ie s in cl ud ed in t he s um m ar iz ed c at eg or y. T he n um be r of s tu di es is t he n um be r of a rt ic le s ca pt ur ed . I n so m e ca se s, a rt ic le s re po rt da ta o n m ul ti pl e pr ev al en ce tr ia ls o r s am pl in g fr am es . W hi le th e ob se rv at io ns fo r e ac h tr ia l a re in de pe nd en t b y ti m e an d sa m pl e, th ey a re p ar t o f a la rg er s tu dy w he re th e m et ho ds a nd in ve st ig at or s ar e th e sa m e. T hu s, th er e is n ot fu ll in de pe nd en ce in t he se o bs er va ti on s, a nd w e no te t hi s by a ck no w le dg in g th er e ar e m ul ti pl e tr ia ls w it hi n a st ud y. b S up er sc ri pt M in di ca te s an a ve ra ge p re va le nc e es ti m at e (a nd 9 5 pe rc en t c on fid en ce in te rv al ) f ro m a ra nd om -e ff ec ts m et a- an al ys is . M et a- an al ys is e st im at es w er e ca lc ul at ed o nl y if h et er og en ei ty w as lo w o r m ed iu m (I 2 0 –6 0 pe rc en t) a nd if a t le as t on e tr ia l f ou nd a p os it iv e sa m pl e. S up er sc ri pt R in di ca te s a m ed ia n (a nd r an ge ) o f t ri al p re va le nc e es ti m at es , c al cu la te d if h et er og en ei ty w as h ig h (I 2 > 60 p er ce nt ). R an ge s no t pr ov id ed w he n on ly o ne t ri al w as id en ti fie d. c I2 is a m ea su re o f t he d eg re e of h et er og en ei ty b et w ee n tr ia ls c om bi ne d in t he m et a- an al ys is . H et er og en ei ty r at in g de fin it io ns : l ow = I2 0 –3 0 p er ce nt ; m ed iu m = 3 1– 60 p er ce nt ; h ig h = >6 0 p er ce nt . S el ec ti on b ia s ra ti ng d efi ni ti on s: h ig h = 0 –3 0 p er ce nt o f t ri al s us ed a re pr es en ta ti ve s am pl e; m ed iu m = 3 1– 60 p er ce nt o f t ri al s us ed a re pr es en ta ti ve s am pl e; lo w = > 60 p er ce nt o f t ri al s us ed a re pr es en ta ti ve s am pl e. S tu di es th at c on du ct ed r an do m o r sy st em at ic s am pl in g w er e co ns id er ed re pr es en ta ti ve . T he o ve ra ll ro bu st ne ss o f t he m et a- an al ys is p re va le nc e es ti m at es c an b e in fe rr ed fr om t he h et er og en ei ty a nd s el ec ti on b ia s ra ti ng s. T ak in g in to c on si de ra ti on t he n um be r of s tu di es in t he m et a- an al ys is , h ig h co nfi de nc e in th e m et a- an al ys is re su lt s ca n be in fe rr ed w he n he te ro ge ne it y is lo w a nd t he r is k of s el ec ti on b ia s is lo w a nd lo w c on fid en ce c an b e in fe rr ed w he n bo th a re h ig h; s ee t he m et ho ds s ec ti on (p ag e 11 ) f or m or e in fo rm at io n. ANNEX 1 191 TA B LE A 1. 33 S um m ar y of s tu di es re po rt in g th e co nc en tr at io n of s el ec te d m ic ro bi al h az ar ds in s pi ce s an d te a w it h an a ss oc ia te d m ea su re o f v ar ia bi lit y Sp ec ifi c sp ic e M ic ro bi al h az ar d Co nc en tr at io n (S D or 9 5% C I) N o. o f ob se rv at io ns U ni ts So ur ce Sp ic es B as il E nt er ob ac te ri ac ea e 4 .0 1 ( 0 .1 5) 6 lo g C FU /g W it ko w sk a et a l., 2 0 11 a B la ck p ep pe r po w de r G en er ic E . c ol i 5. 8 (3 2. 8) 55 M P N /g K oo hy -K am al y- D eh ko rd y et a l., 2 0 13 b, c C ar aw ay G en er ic E . c ol i 15 7. 6 (5 98 .1 ) 16 M P N /g K oo hy -K am al y- D eh ko rd y et a l., 2 0 13 C el er y E n te ro b ac te ri ac ea e 4 .0 6 (0 .1 3) 6 lo g C FU /g W it ko w sk a et a l., 2 0 11 C or ia nd er E n te ro b ac te ri ac ea e 3. 19 (0 .2 5) 6 lo g C FU /g W it ko w sk a et a l., 2 0 11 C ow p ar sn ip G en er ic E . c ol i 38 .5 (1 73 .8 ) 4 0 M P N /g K oo hy -K am al y- D eh ko rd y et a l., 2 0 13 C um in E nt er ob ac te ri ac ea e 3. 0 8 (0 .2 4 ) 6 lo g C FU /g W it ko w sk a et a l., 2 0 11 C ur ry p ow de r G en er ic E . c ol i 14 .9 (7 9. 9) 33 M P N /g K oo hy -K am al y- D eh ko rd y et a l., 2 0 13 Fe nn el E nt er ob ac te ri ac ea e 4 .5 0 (0 .2 4 ) 6 lo g C FU /g W it ko w sk a et a l., 2 0 11 G ar lic G en er ic E . c ol i 2. 4 (1 3. 3) 31 M P N /g K oo hy -K am al y- D eh ko rd y et a l., 2 0 13 G ar lic E nt er ob ac te ri ac ea e 1. 86 (0 .4 3) 6 lo g C FU /g W it ko w sk a et a l., 2 0 11 P ar sl ey E n te ro b ac te ri ac ea e 3. 32 (0 .8 1) 6 lo g C FU /g W it ko w sk a et a l., 2 0 11 R ed p ep pe r po w de r G en er ic E . c ol i 5. 1 ( 22 .9 ) 4 5 M P N /g K oo hy -K am al y- D eh ko rd y et a l., 2 0 13 Tu rm er ic G en er ic E . c ol i 7. 1 ( 35 .0 ) 4 8 M P N /g K oo hy -K am al y- D eh ko rd y et a l., 2 0 13 Te a C ha m om ile C . b ot u lin um 0 .3 1 ( 0 .0 9, 1. 0 3) 23 Sp or es /g D e Jo ng e t al ., 20 0 3 SD = s ta nd ar d de vi at io n; C I = c on fid en ce in te rv al s. a S tu dy a ls o sa m pl ed t he f ol lo w in g sp ic es b ut d id n ot is ol at e E nt er ob ac te ri ac ea e fr om a ny o f th e sa m pl es : a ni se ed , b ay le av es , b la ck p ep pe r po w de r, c ay en ne p ep pe r, c in na m on , c lo ve s, c or ia nd er , d ill , F re nc h on io n, g in ge r, m ac e, m ar jo ra m , m us ta rd , n ut m eg , o ni on p ow de r, o re ga no , p ap ri ka , p im en to , r os em ar y, s ag e, t hy m e, t ur m er ic a nd w hi te p ep pe r po w de r. b S tu dy a ls o sa m pl ed t he fo llo w in g sp ic es b ut d id n ot is ol at e E . c ol i f ro m a ny o f t he s am pl es : c in na m on a nd s um ac . c S tu dy u se d a re pr es en ta ti ve (i .e . r an do m ly o r sy st em at ic al ly s el ec te d) s am pl e. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 192 TABLE A1.34 Forest plot of the prevalence of selected microbial hazards within spice categories LMF subcategories LMF category estimates Average prevalence (95% Cl) 0% 20% 40% 60% 80% 100% Microbial hazard/ LMF subcategory Average prevalence Low 95% CI High 95% CI No. obs./ trials/studies Heterogeneity Selection bias Median (range) B. cereus Bark/flower 14.2 4.7 27.3 154/12/5 High Med. 1.9 (0–60) Fruit/seed 28.8 20.4 38.1 1 001/76/9 High Low 11.7 (0–85.7) Dried herbs 13.6 5.0 25.1 207/20/5 High Med. 0 (0–75) Mixed/unspecified 29.9 20.2 40.6 4 468/20/14 High Low 26.9 (0–68.8) Root 20.2 10.0 32.6 142/15/5 Med. Low - Overall 24.5 20.1 29.2 High 11.7 (0–100) C. perfringens Bark/flower 14.6 2.1 33.7 114/9/4 High Low 0 (0–46.8) Fruit/seed 10.3 7.3 13.7 324/76/49 Low Low - Dried herbs 6.0 3.1 9.7 196/12/5 Low Low - Mixed/unspecified 9.1 3.6 16.4 3 889/11/6 High Low 1.4 (0–32.7) Root 15.0 8.9 22.3 107/9/3 Low Low - Overall 11.4 8.3 14.9 High 0 (0–50) Cronobacter spp. Bark/flower 12.5 0.0 34.3 19/4/3 Low High - Fruit/seed 34.8 20.3 50.8 83/18/3 Med. High - Dried herbs 18.6 7.3 33.1 51/6/3 Low High - Mixed/unspecified 27.0 13.6 42.7 341/13/11 High High 26.9 (0–73.3) Root 35.3 14.8 58.7 17/4/2 Low High - Overall 25.8 17.9 34.7 High 22.6 (0–100) Generic E. coli Bark/flower 4.2 1.7 7.6 179/11/7 Low Med. - Fruit/seed 10.2 7.3 13.6 826/57/9 Med. Med. - Dried herbs 15.6 4.6 30.9 118/18/6 High High 0 (0–70.6) Mixed/unspecified 14.6 6.3 25.3 3 045/8/6 High Med. 11.2 (0–33.3) Root 7.8 0.5 20.3 176/11/5 High Low 0 (0–35.4) Overall 10.7 8.0 13.7 High 0 (0–70.6) S. aureus Bark/flower 2.6 0.8 5.3 195/16/8 Low Med. - Fruit/seed 5.6 4.2 7.2 914/89/10 Low Low - Dried herbs 2.4 0.9 4.7 255/25/7 Low Med. - Mixed/unspecified 2.8 0.5 6.3 132/9/4 Low Med. - Root 10.6 6.2 16.1 144/16/6 Low Med. - Overall 4.9 3.9 5.9 Low - Salmonella spp. Bark/flower 2.3 1.0 3.9 306/26/13 Low Med. - Fruit/seed 4.3 3.6 5.0 2 832/160/20 Low Med. - Dried herbs 0.0 0.0 0.0 503/52/12 Low High - Mixed/unspecified 2.6 1.9 3.4 18 315/47/17 High Low 0 (0–14) Root 4.4 2.5 6.7 367/26/11 Low Med. - Overall 3.0 2.6 3.4 Low - CI = confidence interval; Med = medium; No. obs. = number of total samples tested per category. See the prevalence table for full explanations of all columns. Note: The tea subcategory was excluded from this figure. C. botulinum, E. coli O157, and L. monocytogenes evidence is not shown in this figure because no positive samples were identified in these categories. ANNEX 1 193 A1.12.5 Interventions A total of 20 experimental studies (consisting of 66 unique trials) and one summary of surveillance data were identified evaluating the effects of various interventions to reduce contamination of microbial hazards in spices and tea. The median publication year was 2011 (range 1984–2014). Half (50 percent) of the studies were conducted in Asia and the Middle East (with four studies each in the Republic of Korea and Türkiye). Twelve of the experimental studies were challenge trials with artificially inoculated samples, eight were controlled trials and one was a quasi-experiment (measuring changes in contamination before and after an applied intervention). All studies except the quasi-experiment were conducted under laboratory and non-commercial conditions. The most common interventions were heat treatments, chemical treatments, and irradiation (including ionizing radiation and non-ionizing such as UV and microwave). Most of these interventions are commonly applied in the spice industry (ASTA, 2011; USFDA, 2013). However, it is not a requirement for exporting countries to indicate if a pathogen reduction intervention has been applied. One study that summarized USFDA surveillance data (not shown in the table below) analysed imported spice shipments and found that spices labelled as “treated” had a lower Salmonella prevalence compared to spice shipments that were untreated or of unknown treatment status (3 percent compared to 6.8 percent), although the difference was not statistically significant (Van Doren et al., 2013a). Nearly all trials found that the applied interventions resulted in statistically significant reductions in the concentration or prevalence of microbial hazards. The interventions were applied against various microbial hazards, including Salmonella spp. (n=9 studies) > E. coli (9) > Enterobacteriaceae (4) > B. cereus (3) > C. perfringens (3) > Cronobacter spp. (2). The vast majority of trials (>70 percent) were applied to black (Piper spp.) or red (Capsicum spp.) pepper. Many trials did not report data on intervention efficacy in an extractable format, and typical sample sizes were small (e.g. two to four replicate samples per intervention combination). 0% 20% 40% 60% 80% 100% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 194 TA B LE A 1. 35 S um m ar y ta bl e of e xp er im en ta l s tu di es e va lu at in g th e eff ec ts o f i nt er ve nt io ns t o re du ce c on ta m in at io n of s el ec te d m ic ro bi al h az ar ds in sp ic es , d ri ed h er bs a nd t ea Sp ic e ca te go ry In te rv en ti on ca te go ry In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) So ur ce (s )a M ic ro bi al h az ar d( s) St ud y ty pe b N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc B ar k/ flo w er C he m ic al s P ol ye th yl en e pa ck ag in g w it h si lv er n an op ar ti cl es (u p to 3 0 0 p pm ) (H am id S al es , M ot am ed i S ed eh an d R aj ab if ar , 20 12 ) C . p er fr in g en s G en er ic E . co li, E nt er o- b ac te ri ac ea e C .T . 1/ 1 0 10 0 Ir ra di at io n G am m a (1 t o 4 k G y) (H am id S al es , M ot am ed i S ed eh an d R aj ab if ar , 20 12 ) C . p er fr in g en s G en er ic E . co li, E nt er o- b ac te ri ac ea e C .T . 1/ 1 0 10 0 Fr ui t/ se ed C he m ic al s C ol d pl as m a w it h ni tr og en , ni tr og en -o xy ge n, h el iu m , an d he liu m -o xy ge n ga se s (3 0 0 –9 0 0 W ; 2 67 –2 6 68 0 P a; 4 –2 0 m in ) (K im , L ee a nd M in , 20 14 ) B . c er eu s C h. T. 1/ 1 0 0 C he m ic al s E th yl en e ox id e ga s (7 0 kg /4 8m 3 ; 2 4 h r) (P af um i, 19 84 ) B . c er eu s, C . p er fr in g en s, S al m on el la s pp ., G en er ic E . c ol i C .T . 3/ 1 0 10 0 C he m ic al s P ho sp hi ne g as (3 –6 g /m 3 ; 24 –7 2 hr ) (C as tr o et a l., 2 0 11 ) S al m on el la s pp . C h. T. 1/ 1 0 10 0 C ha ng es to s to ra ge pa ra m et er s In cr ea se d te m pe ra tu re (2 5– 35 °C ; 0 –1 20 d ay s) In cr ea se d hu m id it y (< 4 0 –9 7% ; 0 –1 20 d ay s) In cr ea se d te m pe ra tu re (5 –3 5° C ; 0 –1 5 da ys ) In cr ea se d A w (0 .6 6 to 0 .9 4 ; 0 –1 5 da ys ) (K el le r et a l., 2 0 13 ); (K el le r et a l., 2 0 13 ); (R is to ri , d os S an to s P er ei ra a nd G el li, 20 0 7) ; ( R is to ri , d os Sa nt os P er ei ra a nd G el li, 2 0 0 7) S al m on el la s pp . C h. T. 4 /2 50 10 0 D es ic ca ti on D es ic ca ti on (5 8° C ; 5 0 m in ) (I ja ba de ni yi a nd N ok w an da , 2 0 13 ) C ro n ob ac te r sp p. C h. T. 2/ 1 10 0 10 0 H ea t tr ea tm en t H ot w at er d ip (7 0 –9 0 °C ; 10 –6 0 m in ) (K im , L ee a nd M in , 20 14 ) B . c er eu s C h. T. 1/ 1 0 10 0 (c on t. ) ANNEX 1 195 Sp ic e ca te go ry In te rv en ti on ca te go ry In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) So ur ce (s )a M ic ro bi al h az ar d( s) St ud y ty pe b N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc H ea t tr ea tm en t P as te ur iz at io n (7 2° C ; 1 5 s) (I ja ba de ni yi a nd N ok w an da , 2 0 13 ) C ro n ob ac te r sp p. C h. T. 2/ 1 0 0 Ir ra di at io n Fa r- in fr ar ed (3 0 0 –3 50 °C ; 1. 88 –5 .8 8 m in ) Fa r- in fr ar ed + U V -C ra di at io n (1 0 .5 m W /c m 2 ; 2 hr ) (E rd og du a nd E ki z, 20 13 ) B . c er eu s C .T . 2/ 1 10 0 10 0 Ir ra di at io n G am m a (5 –1 0 k G y) M ic ro w av e (2 4 50 ± 5 0 M H z; 2 0 -7 5 s) (E m am , F ar ag a nd A zi z, 19 95 ) C . p er fr in g en s. C .T . 2/ 1 0 10 0 Ir ra di at io n G am m a (2 t o 5 kG y; 6 –3 0 m in ) R ad io -f re qu en cy (2 7. 12 M H z; 5 7– 79 °C ; 4 0 –5 0 s ) N ea r- in fr ar ed (5 0 0 W ; 50 –7 5° C ; 1 –5 m in ) U V -C (1 6 W ; 5 0 –7 5° C ; 1 –5 m in ) N ea r- in fr ar ed + U V -C (S on g et a l., 2 0 14 ); (K im e t al ., 20 12 ); (H a an d K an g, 20 13 ); (H a an d K an g, 2 0 13 ); (H a an d K an g, 2 0 13 ) E . c ol i O 15 7: H 7, S al m on el la sp p. C h. T. 7/ 3 71 10 0 * Ir ra di at io n G am m a (5 –1 0 k G y) M ic ro w av e (2 4 50 ± 5 0 M H z; 2 0 –7 5 s) U V -C (1 0 .5 m W /c m 2 ; 2 h r) Fa r- in fr ar ed (6 50 W ; 30 0 -3 50 °C ; 1 .8 8– 5. 88 m in ) + U V -C (E m am , F ar ag a nd A zi z, 19 95 ); (E m am , F ar ag a nd A zi z, 19 95 ); (E rd og du a nd E ki z, 20 13 ); (E rd og du a nd E ki z, 20 13 ) G en er ic E . c ol i C .T . 4 /2 50 10 0 Ir ra di at io n E le ct ro n be am (2 .4 –1 2. 5 kG y) M ic ro w av e (2 4 50 ± 5 0 M H z; 5 0 -1 50 s ) (N ie to -S an da va l e t al ., 20 0 0 ); (A yd in a nd B os ta n, 20 0 6) E nt er o- b ac te ri ac ea e C .T . 2/ 2 10 0 10 0 (c on t. ) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 196 Sp ic e ca te go ry In te rv en ti on ca te go ry In te rv en ti on d et ai ls (d os e an d/ or d ur at io n, w he re av ai la bl e) So ur ce (s )a M ic ro bi al h az ar d( s) St ud y ty pe b N o. tr ia ls / st ud ie s % o f t ri al s w it h ex tr ac ta bl e da ta % o f t ri al s fin di ng a st at is ti ca lly si gn ifi ca nt re du ct io nc M in ci ng G ri nd in g in c ut te r (1 .5 m in ) an d m in ci ng in c or un du m m ill Sc hw ei gg er t, Sc hi eb er a nd C ar le , 20 0 5) a G en er ic E . c ol i Q ua si . 1/ 1 0 10 0 M ul ti pl e C ol d pl as m a + ho t w at er tr ea tm en t (7 0 –9 0 °C ; 10 –6 0 m in ) (K im , L ee a nd M in , 20 14 ) B . c er eu s C h. T. 1/ 1 0 10 0 O zo ne 0 .1 –1 .0 p pm ; 3 0 –3 60 m in (E m er , A kb as a nd O zd em ir, 2 0 0 8) G en er ic E . c ol i C h. T. 1/ 1 10 0 10 0 H er bs O zo ne 2. 8 an d 5. 3 m g/ L; 3 0 –1 20 m in (T or la k an d Se rt , 20 13 ) S al m on el la s pp . C h. T. 1/ 1 0 10 0 M ix ed Ir ra di at io n G am m a (5 k G y) (K is s et a l., 19 90 ) E nt er o- b ac te ri ac ea e C .T . 1/ 1 0 10 0 Te a H ea t tr ea tm en t H ot w at er (5 0 –7 0 °C ; 1 0 m in ) (A l- N ab ul si e t al ., 20 0 9) C ro n ob ac te r sp p. C .T . 3/ 1 0 10 0 H ea t tr ea tm en t H ot w at er (6 0 –6 5° C ; 5 m in ) (Z ha o et a l., 19 97 ) S al m on el la s pp . C .T . 2/ 1 0 10 0 M ul ti pl e B ov in e la ct of er ri n (1 –1 0 m g/ m L) + h ot w at er (5 0 –7 0 °C ; 1 0 m in ) (A l- N ab ul si e t al ., 20 0 9) C ro n ob ac te r sp p. C .T . 3/ 1 0 10 0 a I nd ic at es t he se s tu di es w er e co nd uc te d un de r co m m er ci al c on di ti on s. b C h. T. = c ha lle ng e tr ia l; C .T . = c on tr ol le d tr ia l; Q ua si . = q ua si -e xp er im en t (e .g . b ef or e an d aft er s tu dy ). c I nt er ve nt io n ca te go ri es m ar ke d w it h an a st er is k (* ) i nd ic at e th at m or e tr ia ls fo un d a st at is ti ca lly s ig ni fic an t re du ct io n in m ic ro bi al c on ce nt ra ti on o r pr ev al en ce t ha n w ou ld b e ex pe ct ed b y ch an ce a lo ne (s ig n te st P v al ue < 0 .0 5) . ANNEX 1 197 A1.12.6 References in A1.12 References used in summary narrative: ASTA. 2011. Clean, safe spices: guidance from the American Spice Trade Association. The American Spice Trade Association. Washington, DC. (also available at http:// www.astaspice.org/i4a/pages/index.cfm?pageid=4200). Bianco, M.I., Luquez, C., De Jong, L.I., & Fernandez, R.A. 2009. Linden flower (Tilia spp.) as potential vehicle of Clostridium botulinum spores in the transmission of infant botulism. Revista Argentina de Microbiología, 41: 232–236. Bianco, M.I., Luquez, C., De Jong, L.I. & Fernandez, R.A. 2008. Presence of Clostridium botulinum spores in Matricaria chamomilla (chamomile) and its relationship with infant botulism. International Journal of Food Microbiology, 121: 357–360. De Jong L. I. T., Fernández, R. A., Blanco, M. I., Lúquez, C. & Ciccarelli, A. S. 2003. Transmisión del botulismo del lactante. Prensa Médica Argentina, 90: 188–194. EFSA. 2013. Scientific opinion on the risk posed by pathogens in food of non- animal origin. Part 1 (outbreak data analysis and risk ranking of food/pathogen combinations). EFSA Journal 11: 3025. El Saleeby, C.M., Howard, S C., Hayden, R.T. & McCullers, J.A. 2004. Association between tea ingestion and invasive Bacillus cereus infection among children with cancer. Clinical Infectious Diseases 39: 1536–1539. Koohy-Kamaly-Dehkordy, P., Nikoopour, H., Siavoshi, F., Koushki, M. & Abadi, A. 2013. Microbiological quality of retail spices in Tehran, Iran. Journal of Food Protection, 76(5): 843–848. Long, K.Z., Wood, J.W., Vasquez Gariby, E., Weiss, K.M., Mathewson, J.J., de la Cabada, F.J., DuPont, H.L. & Wilson, R.A. 1994. Proportional hazards analysis of diarrhea due to enterotoxigenic Escherichia coli and breast feeding in a cohort of urban Mexican children. American Journal of Epidemiology, 139: 193–205. Sagoo, S.K., Little, C.L., Greenwood, M., Mithani, V., Grant, K.A., McLauchlin, J., de Pinna, E. & Threlfall, E.J. 2009. Assessment of the microbiological safety of dried spices and herbs from production and retail premises in the United Kingdom. Food Microbiology, 26: 39–43. USFDA. 2013. Draft risk profile: pathogens and filth in spices [online]. White Oak, Maryland, USA. [Cited 20 July 2021]. http://www.fda.gov/downloads/food/ foodscienceresearch/risksafetyassessment/ucm367337.pdf Van Doren, J.M., Kleinmeier, D., Hammack, T.S. & Westerman, A. 2013a. Prevalence, serotype diversity, and antimicrobial resistance of Salmonella in imported shipments of spice offered for entry to the United States, FY2007–FY2009. Food Microbiology 34: 239–251. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 198 Vij, V., Ailes, E., Wolyniak, C., Angulo, F. J. & Klontz, K. C. 2006. Recalls of spices due to bacterial contamination monitored by the U.S. food and drug administration: The predominance of salmonellae. Journal of Food Protection, 69(1): 233–237. Witkowska, A. M., Hickey, D. K., Alonso-Gomez, M. & Wilkinson, M. G. 2011. The microbiological quality of commercial herb and spice preparations used in the formulation of a chicken supreme ready meal and microbial survival following a simulated industrial heating process. Food Control, 22(3-4): 616–625. Ziehm, D., Dreesman, J., Rabsch, W., Fruth, A., Pulz, M., Kreienbrock, L. & Campe, A. 2013. Subtype specific risk factor analyses for sporadic human salmonellosis: a case-case comparison in Lower Saxony, Germany. International Journal of Hygiene and Environmental Health, 216: 428–434. Citation list of burden of illness studies (n=17 unique citations): (Distiller ID = Ref #, Outbreak # =OB # where a Distiller ID is not available – for unpublished outbreaks) Anonymous. No date. NOTE: Captured as unpublished data in the outbreak database and no other records located – likely from the EU line list. OB #: 120. El Saleeby, C.M., Howard, S C., Hayden, R.T. & McCullers, J.A. 2004. Association between tea ingestion and invasive Bacillus cereus infection among children with cancer. Clinical Infectious Diseases, 39: 1536–1539. Ref #: 2075. EFSA. 2013. Scientific opinion on the risk posed by pathogens in food of non- animal origin. Part 1 (outbreak data analysis and risk ranking of food/pathogen combinations). EFSA Journal 11: 3025. OB #s: 159, 161, 166, 160. EFSA & ECDC. 2010. The community summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in the European Union in 2008. EFSA Journal, 8: 1496. Ref #: 6637, OB #: 121. EU. No date. NOTE: Captured as unpublished data in the outbreak database and no other records located. OB #s: 165, 171, 169, 172, 170, 291. EFSA. 2012a. Trends and Sources of Zoonoses and Zoonotic Agents in Humans, Foodstuffs, Animals and Feedingstuffs, Denmark 2012. Parma, Italy. (also available at http:// www.efsa.europa.eu/en/zoonosesscdocs/zoonosescomsumrep.htm). OB#s:o306. EFSA. 2012b. Trends and Sources of Zoonoses and Zoonotic Agents in Humans, Foodstuffs, Animals and Feedingstuffs, Hungary 2012. Parma, Italy. (also available at http:// www.efsa.europa.eu/en/zoonosesscdocs/zoonosescomsumrep.htm). OB#s:305. ANNEX 1 199 Gieraltowski, L., Julian, E., Pringle, J., Macdonald, K., Quilliam, D., Marsden-Haug, N., Saathoff-Huber, L., Von Stein, D., Kissler, B., Parish, M., Elder, D., Howard- King, V., Besser, J., Sodha, S., Loharikar, A., Dalton, S., Williams, I. & Barton Behravesh, C. 2013. Nationwide outbreak of Salmonella Montevideo infections associated with contaminated imported black and red pepper: warehouse membership cards provide critical clues to identify the source. Epidemiology and Infection, 141: 1244–1252. Ref #: 269. Gustavsen, S. & Breen, O. 1984. Investigation of an outbreak of Salmonella oranienburg infections in Norway, caused by contaminated black pepper. American Journal of Epidemiology, 119: 806–812. Ref #: 3675. Ilic, S., Duric, P. & Grego, E. 2010. Salmonella Senftenberg infections and fennel seed tea, Serbia. Emerging Infectious Diseases, 16: 893–895. Ref #: 957. Koch, J., Schrauder, A., Alpers, K., Werber, D., Frank, C., Prager, R., Rabsch, W., Broll, S., Feil, F., Roggentin, P., Bockemuhl, J., Tschape, H., Ammon, A., & Stark, K. 2005. Salmonella Agona outbreak from contaminated aniseed, Germany. Emerging Infectious Diseases, 11: 1124–1127. Ref #: 1954. Lehmacher, A., Bockemuhl, J. & Aleksic, S. 1995. Nationwide outbreak of human salmonellosis in Germany due to contaminated paprika and paprika-powdered potato chips. Epidemiology and Infection, 115: 501–511. Ref #: 2987. Little, C.L., Omotoye, R, & Mitchell, R.T. 2003. The microbiological quality of ready- to-eat foods with added spices. International Journal of Environmental Health Research, 13: 31–42. Ref #: 2280. Long, K.Z., Wood, J.W., Vasquez Gariby, E., Weiss, K.M., Mathewson, J.J., de la Cabada, F.J., DuPont, H.L. & Wilson, R.A. 1994. Proportional hazards analysis of diarrhea due to enterotoxigenic Escherichia coli and breast feeding in a cohort of urban Mexican children. American Journal of Epidemiology, 139: 193–205. Ref #: 2674. Raevuori, M., Kiutamo, T., Niskanen, A. & Salminen, K. 1976. An outbreak of Bacillus cereus food-poisoning in Finland associated with boiled rice. Journal of Hygiene, 76: 319–327. Ref #: 3923. Saraiva, M., Campos Cunha, I., Costa Bonito, C., Pena, C., Toscano, M. M., Teixeira Lopes, T., Sousa, I. & Calhau, M. A. 2012. First case of infant botulism in Portugal. Food Control, 26: 79–80. Ref #: 4476. Sotir, M. J., Ewald, G., Kimura, A. C., Higa, J. I., Sheth, A., Troppy, S., Meyer, S., Hoekstra, R. M., Austin, J., Archer, J., Spayne, M., Daly, E. R. & Griffin, P. M. 2009. Outbreak of Salmonella Wandsworth and Typhimurium infections in infants and toddlers traced to a commercial vegetable-coated snack food. Pediatric Infectious Diseases Journal, 28: 1041–1046. Ref #: 1095. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 200 Van Doren, J.M., Neil, K.P., Parish, M., Gieraltowski, L., Gould, L. H. & Gombas, K.L. 2013b. Foodborne illness outbreaks from microbial contaminants in spices, 1973- 2010. Food Microbiol, 36: 456–464. OB #s: 54, 98, 1, 109, 137. Ziehm, D., Dreesman, J., Rabsch, W., Fruth, A., Pulz, M., Kreienbrock, L. & Campe, A. 2013. Subtype specific risk factor analyses for sporadic human salmonellosis: a case-case comparison in Lower Saxony, Germany. International Journal of Hygiene and Environmental Health, 216: 428–434. Ref #: 328. Citation list of prevalence studies (N=77): (Distiller ID = Ref #) Abou Donia, M. A. 2008. Microbiological quality and aflatoxinogenesis of Egyptian spices and medicinal plants. Global Veterinaria, 2(4): 175–181. Ref #: 6737. Arias-Echandi, M. L., Utzinger-Villiger, D. & Monge-Rojas, R. 1997. Microbiological quality of some powder spices of common use in Costa Rica. Revista De Biología Tropical, 45: 692–694. Ref #: 6607. Banerjee, M. & Sarkar, P. K. 2003. Microbiological quality of some retail spices in india. Food Research International, 36(5): 469–474. Ref #: 6610. Baumgartner, A., Grand, M., Liniger, M. & Iversen, C. 2009. Detection and frequency of Cronobacter spp. (Enterobacter sakazakii) in different categories of ready-to-eat foods other than infant formula. International Journal of Food Microbiology, 136(2): 189–192. Ref #: 1191. Beki, L. & Ulukanli, Z. 2008. Enumeration of microorganisms and detection of some pathogens in commonly used spices sold openly from retail stores in Kars. Gazi University Journal of Science, 21(3): 79–85. Ref #: 6738. Belal, M., Al-Mariri, A., Hallab, L. & Hamad, I. 2013. Detection of Cronobacter spp. (formerly Enterobacter sakazakii) from medicinal plants and spices in Syria. Journal of Infection in Developing Countries, 7(2): 82–89. Ref #: 202. Bianco, M.I., Luquez, C., De Jong, L.I. & Fernandez, R.A. 2008. Presence of Clostridium botulinum spores in matricaria chamomilla (chamomile) and its relationship with infant botulism. International Journal of Food Microbiology, 121(3): 357–360. Ref #: 1463. Bianco, M.I., Luquez, C., De Jong, L.I. & Fernandez, R.A. 2009. Linden flower (Tilia spp.) as potential vehicle of Clostridium botulinum spores in the transmission of infant botulism. Revista Argentina De Microbiologia, 41(4): 232–236. Ref #: 1025. Candlish, A. A. G., Pearson, S. M., Aidoo, K. E., Smith, J. E., Kelly, B. & Irvine, H. 2001. A survey of ethnic foods for microbial quality and aflatoxin content. Food Additives and Contaminants, 18(2): 129–136. Ref #: 2535. ANNEX 1 201 Carlin, F., Broussolle, V., Perelle, S., Litman, S. & Fach, P. 2004. Prevalence of Clostridium botulinum in food raw materials used in REPFEDs manufactured in France. International Journal of Food Microbiology, 91(2): 141–145. Ref #: 2177. 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T. 2003. The microbiological quality of ready- to-eat foods with added spices. International Journal of Environmental Health Research, 13(1): 31–42. Ref #: 2280. Merzougui, S., Lkhider, M., Grosset, N., Gautier, M. & Cohen, N. 2014. Prevalence, PFGE Typing, and Antibiotic Resistance of Bacillus cereus Group Isolated from Food in Morocco. Foodborne Pathogens and Disease, 11(2): 145–149 [online]. [Cited 20 July 2021]. http://www.liebertpub.com/doi/10.1089/fpd.2013.1615 Ref #: 31. Molloy, C., Cagney, C., O’Brien, S., Iversen, C., Fanning, S. & Duffy, G. 2009. Surveillance and characterisation by pulsed-field gel electrophoresis of Cronobacter spp. in farming and domestic environments, food production animals and retail foods. International Journal of Food Microbiology, 136(2): 198–203. Ref #: 1113. Moreira, P. L., Lourencao, T. B., Pinto, J. P. & Rall, V. L. 2009. Microbiological quality of spices marketed in the city of Botucatu, Sao Paulo, brazil. Journal of Food Protection, 72(2): 421–424. Ref #: 1209. Mozrova, V., Brenova, N., Mrazek, J., Lukesova, D. & Marounek, M. 2014. Surveillance and characterisation of Cronobacter spp. in Czech retail food and environmental samples. Folia Microbiologica, 59(1): 63–68. Ref #: 95. Mpuchane, S. F. & Gashe, B. A. 1996. Presence of Escherichia coli, Klebsiella pneumoniae and Enterobacter species in dried bush okra (corchorus olitorius) and African spider herb (cleome gynandra). Food Control, 7(3): 169–172. Ref #: 6256. Nunes, M. M., Mota, A. L. A. D. A. & Caldas, E. D. 2013. Investigation of food and water microbiological conditions and foodborne disease outbreaks in the federal district, Brazil. Food Control, 34(1): 235–240. Ref #: 4142. Oh, S., Koo, M. & Kim, H. J. 2012. Contamination patterns and molecular typing of Bacillus cereus in red pepper powder processing. Journal of the Korean Society for Applied Biological Chemistry, 55(1): 127–131. Ref #: 4570. Osmar Aguilera, M., Stagnitta, P. V., Micalizzi, B. & de Guzman, A. M. 2005. Prevalence and characterization of Clostridium perfringens from spices in Argentina. Anaerobe, 11(6): 327–334. Ref #: 1817. ANNEX 1 205 Psomas, E., Papantoniou, D., Petridis, D. & Panou, E. 2009. Evaluation of the microbiological quality of Greek oregano samples. Archiv Fur Lebensmittelhygiene, 60(3): 98–103. Ref #: 5145. Rampersad, F. S., Laloo, S., La Borde, A., Maharaj, K., Sookhai, L., Teelucksingh, J., Reid, S., McDougall, L. & Adesiyun, A. A. 1999. Microbial quality of oysters sold in western Trinidad and potential health risk to consumers. Epidemiology and Infection, 123(2): 241–250. Ref #: 2681. Rodriguez, M., Alvarez, M. & Zayas, M. 1991. Microbiological quality of spices consumed in Cuba [Calidad microbiologica de especias consumidas en Cuba]. Revista Latinoamericana De Microbiologia, 33(2–3): 149–151. Ref #: 3315. Rodriguez-Romo, L. A., Heredia, N. L., Labbe, R. G. & Garcia-Alvarado, J. S. 1998. Detection of enterotoxigenic Clostridium perfringens in spices used in Mexico by dot blotting using a DNA probe. Journal of Food Protection, 61(2): 201–204. Ref #: 2777. Rusul, G. 1995. Prevalence of Bacillus cereus in selected foods and detection of enterotoxin using TECRA-VIA and BCET-RPLA. International Journal of Food Microbiology, 25(2): 131–139. Ref #: 3029. Sagoo, S. K., Little, C. L., Greenwood, M., Mithani, V., Grant, K. A., McLauchlin, J., de Pinna, E. & Threlfall, E. J. 2009. Assessment of the microbiological safety of dried spices and herbs from production and retail premises in the United Kingdom. Food Microbiology, 26(1): 39–43. Ref #: 1279. Salari, R., Najafi, M. B. H., Boroushaki, M. T., Mortazavi, S. A. & Najafi, M. F. 2012. Assessment of the microbiological quality and mycotoxin contamination of Iranian red pepper spice. Journal of Agricultural Science and Technology, 14: 1511–1521. Ref #: 4361. Shaker, R., Osaili, T., Al-Omary, W., Jaradat, Z. & Al-Zuby, M. 2007. Isolation of Enterobacter sakazakii and other Enterobacter sp. from food and food production environments. Food Control, 18(10): 1241–1245. Ref #: 5421. Sheth, M., Patel, J., Sharma, S. & Seshadri, S. 2000. Hazard analysis and critical control points of weaning foods. Indian Journal of Pediatrics, 67(6): 405–410. Ref #: 2598. Simango, C. 1995. Isolation of Escherichia coli in foods. Central African Journal of Medicine, 41(6): 181–185. Ref #: 3022. Sospedra, I., Soriano, J. M. & Mañes, J. 2010. Assessment of the microbiological safety of dried spices and herbs commercialized in Spain. Plant Foods for Human Nutrition, 65(4): 364–368. Ref #: 856. Stankovic, N., Comic, L. & Kocic, B. 2006. Microbiological correctness of spices on sale in health food stores and supermarkets in Nis. Acta Facultatis Medicae Naissensis, 23(2): 79–84. Ref #: 6745. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 206 Stojanovic, M. M., Katić, V. & Kuzmanović, J. 2011. Isolation of Cronobacter sakazakii from different herbal teas. Vojnosanitetski Pregled, 68(10): 837–841. Ref #: 4691. Te Giffel, M. C., Beumer, R. R., Leijendekkers, S. & Rombouts, F. M. 1996. Incidence of Bacillus cereus and Bacillus subtilis in foods in the Netherlands. Food Microbiology, 13(1): 53–58. Ref #: 6272. Turcovsky, I., Kunikova, K., Drahovska, H. & Kaclikova, E. 2011. Biochemical and molecular characterization of Cronobacter spp. (formerly Enterobacter sakazakii) isolated from foods. Antonie Van Leeuwenhoek, 99(2): 257–269. Ref #: 899. Van Doren, J. M., Blodgett, R. J., Pouillot, R., Westerman, A., Kleinmeier, D., Ziobro, G. C., Ma, Y., Hammack, T. S., Gill, V., Muckenfuss, M. F. & Fabbri, L. 2013. Prevalence, level and distribution of Salmonella in shipments of imported capsicum and sesame seed spice offered for entry to the United States: Observations and modeling results. Food Microbiology, 36(2): 149–160. Ref #: 69. Van Doren, J.M., Kleinmeier, D., Hammack, T.S. & Westerman, A. 2013a. Prevalence, serotype diversity, and antimicrobial resistance of Salmonella in imported shipments of spice offered for entry to the United States, FY2007-FY2009. Food Microbiology, 34: 239-251. Ref #: 169. Verdi, S., Younes, S. & Bertol, C. D. 2013. Microbiological quality evaluation of herbal capsules and teas to assist the treatment of obesity. Revista Brasileira De Plantas Medicinais, 15(4): 494–502. Ref #: 4098. Vij, V., Ailes, E., Wolyniak, C., Angulo, F. J. & Klontz, K. C. 2006. Recalls of spices due to bacterial contamination monitored by the U.S. food and drug administration: The predominance of salmonellae. Journal of Food Protection, 69(1): 233–237. Ref #: 1871. Vitullo, M., Ripabelli, G., Fanelli, I., Tamburro, M., Delfine, S. & Sammarco, M. L. 2011. Microbiological and toxicological quality of dried herbs. Letters in Applied Microbiology, 52(6): 573–580. Ref #: 743. Witkowska, A. M., Hickey, D. K., Alonso-Gomez, M. & Wilkinson, M. G. 2011. The microbiological quality of commercial herb and spice preparations used in the formulation of a chicken supreme ready meal and microbial survival following a simulated industrial heating process. Food Control, 22(3–4): 616–625. Ref #: 4776. Zhao, T., Clavero, M. R. S., Doyle, M. P. & Beuchat, L. R. 1997. Health relevance of the presence of fecal coliforms in iced tea and leaf tea. Journal of Food Protection, 60(3): 215–218. Ref #: 6228. ANNEX 1 207 Citation list of interventions studies (N=21): (Distiller ID = Ref #) Al-Nabulsi, A. A., Osaili, T. M., Shaker, R. R., Olaimat, A. N., Ayyash, M. M. & Holley, R. A. 2009. Survival of Cronobacter species in reconstituted herbal infant teas and their sensitivity to bovine lactoferrin. Journal of Food Science, 74(9): M479-84. Ref #: 994. Aydin, A. & Bostan, K. 2006. Microbial decontamination of powdered black pepper (Piper nigrum L.) by using microwave. Journal of Food Science and Technology, 43(6): 575–578. Ref #: 5558. Castro, M. F., Rezende, A. C., Benato, E. A., Valentini, S. R., Furlani, R. P. & Tfouni, S. A. 2011. Studies on the effects of phosphine on Salmonella enterica serotype enteritidis in culture medium and in black pepper (piper nigrum). Journal of Food Protection, 74(4): 665–671. Ref #: 727. Emam, O. A., Farag, S. A. & Aziz, N. H. 1995. Comparative effects of gamma and microwave irradiation on the quality of black pepper. Zeitschrift Fur Lebensmittel- Untersuchung Und -Forschung, 201(6), 557–561. Ref #: 2986. Emer, Z., Akbas, M. Y. & Ozdemir, M. 2008. Bactericidal activity of ozone against escherichia coli in whole and ground black peppers. Journal of Food Protection, 71(5): 914–917. Ref #: 1371. Erdogdu, S. B. & Ekiz, H. I. 2013. Far infrared and ultraviolet radiation as a combined method for surface pasteurization of black pepper seeds. Journal of Food Engineering, 116(2): 310–314. Ref #: 4316. Ha, J. W. & Kang, D. H. 2013. Simultaneous near-infrared radiant heating and UV radiation for inactivating escherichia coli O157:H7 and Salmonella enterica serovar typhimurium in powdered red pepper (capsicum annuum L.). Applied and Environmental Microbiology, 79(21): 6568–6575. Ref #: 79. Hamid Sales, E., Motamedi Sedeh, F. & Rajabifar, S. 2012. Effects of gamma irradiation and silver nano particles on microbiological characteristics of saffron, using hurdle technology. Indian Journal of Microbiology, 52(1): 66–69. Ref #: 194. Ijabadeniyi, O. A. & Nokwanda, M. 2013. Food borne bacteria isolated from spices and fate of Cronobacter sakazakii ATCC 29544 in black pepper exposed to drying and various temperature conditions. Journal of Food, Agriculture and Environment, 11(3–4): 492–495. Ref #: 4127. Keller, S. E., Van Doren, J. M., Grasso, E. M. & Halik, L. A. 2013. Growth and survival of Salmonella in ground black pepper (Piper nigrum). Food Microbiology, 34(1): 182–188. Ref #: 181. Kim, J. E., Lee, D. U. & Min, S. C. 2014. Microbial decontamination of red pepper powder by cold plasma. Food Microbiology, 38: 128–136. Ref #: 18. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 208 Kim, S. Y., Sagong, H. G., Choi, S. H., Ryu, S. & Kang, D. H. 2012. Radio-frequency heating to inactivate Salmonella Typhimurium and Escherichia coli O157:H7 on black and red pepper spice. International Journal of Food Microbiology, 153(1–2): 171–175. Ref #: 548. Kiss, I. F., Beczner, J., Zachariev, G. & Kovacs, S. 1990. Irradiation of meat products, chicken and use of irradiated spices for sausages. Radiation Physics and Chemistry, 36(3): 295–299. Ref #: 6376 Nieto-Sandoval, J. M., Almela, L., Fernandez-Lopez, J. A. & Munoz, J. A. 2000. Effect of electron beam irradiation on color and microbial bioburden of red paprika. Journal of Food Protection, 63(5), 633–637. Ref #: 2615. Pafumi, J. 1984. Assessment of the microbiological quality of spices and herbs. Journal of Food Protection, 49(12): 958–963. Ref #: 6686. Ristori, C. A., dos Santos Pereira, M. & Gelli, D. S. 2007. Behavior of Salmonella rubislaw on ground black pepper (Piper nigrum L.). Food Control, 18(3): 268–272. Ref #: 5506. Schweiggert, U., Mix, K., Schieber, A. & Carle, R. 2005. An innovative process for the production of spices through immediate thermal treatment of the plant material. Innovative Food Science and Emerging Technologies, 6(2): 143–153. Ref #: 5721. Song, W., Sung, H., Kim, S., Kim, K., Ryu, S. & Kang, D. 2014. Inactivation of Escherichia coli O157: H7 and Salmonella Typhimurium in black pepper and red pepper by gamma irradiation. International Journal of Food Microbiology, 172: 125–129. Ref #: 4. Torlak, E., Sert, D. & Ulca, P. 2013. Efficacy of gaseous ozone against Salmonella and microbial population on dried oregano. International Journal of Food Microbiology, 165(3): 276–280. Ref #: 105. Van Doren, J.M., Kleinmeier, D., Hammack, T.S. & Westerman, A. 2013a. Prevalence, serotype diversity, and antimicrobial resistance of Salmonella in imported shipments of spice offered for entry to the United States, FY2007-FY2009. Food Microbiology, 34: 239–251. Ref #: 169. Zhao, T., Clavero, M. R. S., Doyle, M. P. & Beuchat, L. R. 1997. Health relevance of the presence of fecal coliforms in iced tea and leaf tea. Journal of Food Protection, 60(3): 215–218. Ref #: 6228. ANNEX 1 209 A1.13 APPENDICES Appendix A. LMF product categories and subcategories TABLE A1.36 LMF product categories and subcategories LMF Categories/ Subcategories Examples of included food products Cereals and grains Whole grains other than rice Wheat, barley, maize/corn, oats, rye, millet, sorghum, buckwheat Rice and rice products Rice, rice noodles Milled grains Milled grain products (e.g. flours, starches) Other dry cereals and cereal products Breakfast cereals, cereal and baking mixes, unspecified/ mixed cereals Confections and snacks Cocoa and chocolate products Dried cocoa beans, cocoa powder, chocolate, cocoa and chocolate-based products (e.g. hot chocolate mix) Other and unspecified confections Fondants/creams, marshmallows, caramels/toffees, candies, chewing gum, other/unspecified confections and sweets Snacks Savoury snacks (e.g. chips, crackers, biscuits) Yeast Yeast extract (as LMF additive or flavouring) Dried fruits and vegetables Dried fruits Raisins, prunes, dates, dried mangos, dried apricots, desiccated coconut, fruit powders Dried vegetables Dried vegetables (e.g. tomatoes), vegetable powders and mixes (e.g. dry soup mixes), dehydrated vegetables (e.g. potato flakes, carrot slices), vegetable flours (e.g. potato starch), dried legumes Dried mushrooms Dried/dehydrated mushrooms Dried seaweed Dried seaweed Dried protein products Dried dairy products Milk/whey powders, other dairy powders (e.g. cheese), milk-based powders and mixes Dried egg products Egg powders Dried fish/seafood products Dried fish and seafood, fish flour/meal Dried meats other than sausages/salamis/jerky Meat powders, gelatin Honey and preserves Honey Honey Preserves Jams, syrups (e.g. corn syrup) (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 210 LMF Categories/ Subcategories Examples of included food products Nuts and nut products Almonds Almonds Other tree nuts Brazil nuts, cashews, hazelnuts/filberts, macadamia nuts, pecans, pine nuts, pistachios and walnuts Peanuts and peanut products Peanuts, peanut butter, other peanut products (e.g. peanut spreads) Mixed and unspecified nuts Mixed/unspecified nuts Seeds for consumption Sesame seeds Sesame seeds Tahini Tahini (sesame seed paste) Halva/helva Halva/helva (confection made from sesame paste/tahini) Other and unspecified seeds Pumpkin seeds, sunflower seeds, poppy seeds, melon seeds, flax seeds, mixed/unspecified seeds for consumption (does not include sprouted seeds) Spices and dried aromatic plants Spices – fruit/seed-based Capsicum spp. (paprika, cayenne pepper, chili peppers, other hot and sweet dried capsicum peppers) Piper spp. (black, white, green, long pepper) Apiaceae (aniseed, caraway, celery, coriander, dill seed, fennel, chervil, cumin) Allspice, nutmeg/mace, other (e.g. cardamom, fungreek, mustard, sumac) Spices– root-based Garlic, ginger, turmeric, other (e.g. galangal, onion, asafoetida) Spices – herb/leaf-based Origanum spp. (e.g. oregano, marjoram), basil, bay leaf, other (e.g. mint, rosemary, parsley, sage, thyme, dill weed/leaves Spices – bark/flower-based Cinnamon, cloves, saffron, other (e.g. geranium, safflower) Spices – mixed/ unspecified Curry powder, Indian spices (e.g. garam masala, tandoori), herb mixes (e.g. Herbs de province, other/ unspecified), other mixed/unspecified spices Tea Herbal (e.g. chamomile, spearmint, peppermint, linden flower, hibiscus), other/unspecified (e.g. black, green, rooibos) ANNEX 1 211 Appendix B. Final search algorithm TABLE A1.37 Final search algorithm Category Terms Hazards “bacillus cereus” OR “clostridium botulinum” OR “clostridium perfringens” OR “cronobacter” OR “enterobacter sakazakii” OR “enterobacteriaceae” OR “escherichia coli” OR “e. coli” OR “salmonella” OR “staphylococcus aureus” OR “listeria monocytogenes” LMF (“low-moisture food” OR “low-moisture foods” OR “low moisture foods” OR “low moisture food”) OR (“dried fruit” OR “dried fruits” OR “dehydrated fruit” OR “dehydrated fruits” OR “raisin” OR “raisins” OR “dried vegetables” OR “dried vegetable” OR “dehydrated vegetables” OR “dehydrated vegetable” OR “preserved vegetable” OR “preserved vegetables” OR “preserved fruit” OR “preserved fruits” OR “desiccated coconut”) OR (“peanut” OR “peanut butter” OR “peanuts” OR “nut” OR “nuts” OR walnut OR walnuts OR pecan OR pecans OR almond OR almonds OR hazelnut OR hazelnuts OR pistachio OR pistachios OR “pine nut” OR “pine nuts” OR cashew OR cashews OR “mixed nuts” OR chestnut OR chestnuts OR “sesame seed” OR “sesame seeds” OR “sunflower seed” OR “sunflower seeds” OR “poppy seed” OR “poppy seeds” OR “edible seed” OR “edible seeds” OR “tahini”) OR (cereals OR cereal OR oats OR granola OR flour OR buckwheat OR millet OR rye OR wheat OR maize OR corn OR rice) OR (“dry milk” OR “dehydrated milk” OR “whey protein” OR “powdered milk” OR “milk powder” OR “rice protein” OR “soy protein” OR “dry protein” OR “dry sausage” OR “dry cured sausage” OR “ cured sausage” OR “jerky” OR “fermented sausage” OR “egg powder” OR “beef powder” OR “fermented seafood” OR “meat powder”) OR (confection OR confections OR confectionery OR candies OR candy OR sweets OR chocolate OR cocoa OR marshmallow OR halva) OR (snack OR “potato chips”) OR (spice OR “dried herb” OR “dried herbs” OR “dehydrated herb” OR “dehydrated herbs” OR basil OR “curry” OR “ginger” OR coriander OR pepper OR “chili powder” OR turmeric OR paprika OR cardamom OR nutmeg OR allspice OR aniseed OR “bay leaves” OR caraway OR cinnamon OR chive OR chives OR clove OR cloves OR cumin OR dill OR fennel OR fenugreek OR galanga OR marjoram OR mustard OR oregano OR parsley OR peppermint OR rosemary OR sage OR spearmint OR tarragona OR thyme OR vanilla OR annatto OR saffron) OR (tea OR teas) OR (honey OR jam OR jams OR jelly OR syrup) Outcome illness OR illnesses OR case OR cases OR outbreak OR recall OR recalls OR prevalence OR frequency OR detection OR surveillance OR contamination OR intervention OR inactivate OR treatment OR pasteurization OR disinfect OR hygiene OR haccp OR “hazard analysis” OR “agricultural practices” OR “manufacturing practices” RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 212 Search notes: • Each category of terms was combined with the AND operator. • The Scopus search was conducted in the Title/Abstract/Keywords. • The PubMed search was conducted in the Title/Abstract. • There were no language or date restrictions on the search. ANNEX 1 213 Appendix C. Final search algorithm TABLE A1.38 Final search algorithm Question Options Definitions/additional notes 1. Does the citation describe research investigating or discussing the prevalence, cases/ outbreaks of human illness, or interventions for any relevant microbial hazards in low-moisture foods? □ Yes □ No Low-moisture foods (LMF) – for the purposes of this study, refers to any food item that has a water activity (aw) level <0.85. Categories of LMF for inclusion: dehydrated/dried fruit and vegetables, cereals, dry protein products (excluding infant milk formula), confections, snacks, tree nuts, peanuts/peanut butter, seeds for consumption, spices and dried aromatic plants, lipid-based supplementary foods, and preserves (e.g. jams and honey). If a product is suspected of being a LMF (e.g. “dry fermented sausage”) and the aw level is not explicitly stated in the study, the study should be included. Microbiological hazards (MH) – for the purposes of this study, refers to Bacillus cereus, Clostridium botulinum, Clostridium perfringens, Cronobacter spp. (formally, Enterobacter sakazakii), Escherichia coli, Salmonella spp., Staphylococcus aureus, and Listeria monocytogenes, Enterobacteriaceae Include citations that do not provide sufficient detail to determine the article’s relevancy (e.g., “confectionary items”, “snacks”, “sausages” may not refer LMFs). Exclude • Articles describing the validation of tests/tools for the detection of MHs in LMFs • Reviews (non-primary research) • Consumer-level interventions (e.g. cooking) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 214 Appendix D. Relevance confirmation and article characterization form TABLE A1.39 Relevance confirmation and article characterization form Question Comments 1. Does the article describe research investigating or discussing the prevalence/risk factors, cases/ outbreaks of human illness, or interventions for any relevant microbial hazards in low-moisture foods? □ Prevalence or risk factors □ Cases/outbreaks □ Interventions □ None of the above, specify: ○ Not a LMF of interest ○ Not a microbial hazard of interest ○ Aw is >0.85 ○ Other, specify:____________ Low-moisture foods (LMF) – for the purposes of this study, refers to as any food item that has a water activity (aw) level <0.85. Categories of LMF for inclusion: dehydrated/dried fruit and vegetables, cereals, dry protein products (excluding infant milk formula), confections, snacks, tree nuts, peanuts/peanut butter, seeds for consumption, spices and dried aromatic plants, lipid-based supplementary foods, and preserves (e.g. jams and honey). If a product is suspected of being a LMF (e.g. “dry fermented sausage”) and the aw level is not explicitly stated in the study, the study should be included. Microbiological hazards (MH) – for the purposes of this study, refers to Bacillus cereus, Clostridium botulinum, Clostridium perfringens, Cronobacter spp. (formally, Enterobacter sakazakii), Escherichia coli, Salmonella spp., Staphylococcus aureus, Listeria monocytogenes, and Enterobacteriaceae. NOTE: Articles investigating “semi-dry” sausages without mention of aw values should be considered aw >0.85 and excluded. 2. Is the article written in English, French or Spanish? □ Yes □ No, but abstract contains extractable data; specify article language:________ □ No, non-English abstract or non-extractable data in abstract; specify language:________ (cont.) ANNEX 1 215 Question Comments 3. What LMFs were investigated or discussed? □ Dried or dehydrated fruit and/or vegetables □ Nuts and nut products ○ Tree nuts ○ Peanuts and peanut-based products □ Cereals/grains ○ Whole and dried cereals/grains, and products thereof ○ Rice □ Dried protein products ○ Dried/fermented sausages/ salamis ○ Dried meats/meat products other than sausages/salamis ○ Dried dairy products ○ Dried egg products ○ Dried fish/seafood products □ Confections □ Snacks □ Seeds for consumption □ Spices/dried aromatic plants/teas □ Lipid-based supplementary foods 4. What microbial hazards were investigated or discussed? □ Bacillus cereus □ Clostridium botulinum □ Clostridium perfringens □ Cronobacter spp. (Enterobacter sakazakii) □ Escherichia coli □ Salmonella spp. □ Listeria monocytogenes □ Staphylococcus aureus □ Enterobacteriaceae RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 216 Appendix E. Data extraction forms TABLE A1.40 Burden of illness extraction form Question Comments 1. Outbreak Ref: □ Outbreak database #: □ Distiller REFID: □ Source of info: 2. What type of document is the article? □ Journal article □ Research report □ Conference proceedings □ Non-peer reviewed data from line listing, government report or other source □ Other:____________ Non-peer reviewed data from line listing, government report or other source (e.g. ProMed, Eurosurveillance, newspapers) 3. When did the outbreak occur? □ Enter year:___________ 4. Where did the outbreak occur? Please specify exact country in separate column. □ Africa □ Asia □ Australia/New Zealand □ Europe □ North America □ Latin America/Caribbean □ Other:_____________ □ Not stated 5. Specify exact country where outbreak occurred. 6. From what region did the implicated product originate? □ Africa □ Asia □ Australia/New Zealand □ Europe □ North America □ Latin America/Caribbean □ Other:_____________ □ Not stated □ N/A – same as outbreak location 7. Specify exact country of origin. 8. How was the outbreak source confirmed? □ Laboratory □ Epidemiologically □ Other:_____________ Lab confirmed source Epi association to source (cont.) ANNEX 1 217 Question Comments 9. What LMF product category was implicated? 10. What specific product was implicated? 11. Epidemiological association with the implicated product (if provided) 12. What microbial hazard was implicated? 13. What was the specific bacteria species/ serovar? 14. Extract quantitative outcomes □ No. presumed cases: □ No. confirmed cases: □ No. hospitalizations: □ No. deaths: □ No. exposed (if provided): □ Attack rate (if provided): 15. How were the cases confirmed to be part of the outbreak? a. Laboratory b. Epidemiologically c. Other:_____________ Lab confirmed to be part of the outbreak Epi association to outbreak 16. If provided, what was the concentration of the hazard in the implicated product (specify units)? 17. Additional Comments RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 218 TABLE A1.41 Prevalence extraction form Question Comments 1. REFID: _____ 2. What type of document is the article? □ Journal article □ Research report □ Conference proceedings □ Other:____________ 3. First author’s last name: Enter name:___________ 4. When was the article published? Enter year:___________ 5. When was the study conducted? □ Enter month/year to month/ year:_________ □ Not reported 6. Where was the study conducted? □ Africa □ Asia □ Australia/New Zealand □ Europe □ North America □ Latin America/Caribbean □ Other:_____________ □ Not stated 7. Specify exact country where study was conducted. (cont.) ANNEX 1 219 Question Comments 8. What was the study design? □ Prevalence survey □ Longitudinal prevalence □ Surveillance □ Challenge trial (ChT) □ Controlled trial (CT) □ Quasi-experiment (QE) □ Cohort study □ Case-control study (C-C) □ Cross-sectional study (XS) □ Case report or series □ Outbreak report/investigation □ Other, please specify: Prevalence survey: A study that measures, and may describe (e.g. concentration), the degree of contamination of a LMF by one or more MH at a particular point in time. It does not investigate risk factors for contamination. Longitudinal prevalence: A study that measures, and may describe (e.g. concentration), the degree of contamination of a LMF by one or more MH over two or more time intervals. Samples may either be at the level of the location (e.g. supermarkets and processing facilities) or the product (e.g. a set of 10 dry-fermented sausages sampled three times over several weeks). It does not investigate risk factors for contamination. Surveillance: A system that continuously gathers, analyses and interprets data about diseases (or contamination of certain LMFs) and disseminates conclusions of the analyses to relevant organizations in a timely manner. Challenge trial: An experiment where LMF are artificially challenged or exposed to the MH for the purpose of characterizing the MH in the LMF. Controlled trial: An experiment where an intervention is applied to contaminated LMF or relevant environment(s) (e.g. processing facilities) for the purpose of reducing or eliminating the MH. Quasi-experimental: An experiment where an intervention is applied to contaminated LMF or relevant environment(s) (e.g. processing facilities) in a non-randomized fashion for the purpose of reducing or eliminating the MH (e.g. before and after trial). Cohort study: An observational study where multiple measurements of a sample population of LMF or affected persons or relevant environment(s) (e.g. processing facilities) are obtained over two or more time periods to identify risk factors for contamination with one or more MH. Can be either retrospective or prospective. Case-control study: An observational study where contaminated LMFs or affected persons or relevant environments (e.g. processing facilities) are matched with non-contaminated LMFs, affected persons or relevant environments, respectively, to identify risk factors for contamination with MH or vehicles of MHs. Cross-sectional study: An observational study where LMFs, or relevant environment(s) (e.g. processing facilities) are sampled for the purpose of identifying or characterizing the degree of contamination, as well as potential risk factors for contamination of one or more MH. Case report or series: A descriptive study that tracks affected persons with a foodborne disease for the purpose of identifying the aetiological agent (MH), vehicle of transmission (LMF) and source/point of contamination. Includes preliminary assessment that includes qualitative/quantitative questionnaires of affected persons, collection of clinical specimens, collection of food and environmental samples, but does not include further epidemiological investigation (e.g. case-controls). (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 220 Question Comments 9. Where was the sampling conducted? □ Farm □ Processing plant □ Retail/markets □ Ready-to-eat □ Import/export □ Research/lab facility □ Other:_____________ □ Not reported Farm: Location of commercial production/harvesting of LMF (e.g. farm, almond orchard, etc.) (i.e. products that will later be sold to consumers). Commercial processing plant: Location of processing and/ or packaging of LMF (e.g. dry sausage processing facility, facilities to process fresh spices and herbs into LMF products). Retail: Any location where consumers can purchase LMF (e.g. local grocery stores, supermarkets, farmer’s markets and butcher’s shops). Ready-to-eat: Locations that serve/offer LMF and products containing LMF that can be immediately consumed (e.g. restaurants, delicatessens, cafeterias and buffets, etc.). Import/Export: LMF are sampled immediately before they leave the country of production or immediately after they enter the country of sale. Research/laboratory facility: Articles that report on a study sampling products in a laboratory setting. 10. Was the LMF product sampling representative of the larger/target population? □ Yes □ No Quantitative DE section – complete multiple rows for each study as appropriate for each product/hazard combination 11. What LMF product category was measured? 12. What specific product was measured? 13. What microbial hazard was measured? 14. What was the specific bacteria species/serovar? 15. From what region did the samples originate? □ Africa □ Asia □ Australia/New Zealand □ Europe □ North America □ Latin America/Caribbean □ Other:_____________ □ Multiple □ Not stated □ N/A – same as study location 16. Specify exact country of origin. (cont.) ANNEX 1 221 Question Comments 17. How was the outcome reported? Check all that apply □ Prevalence □ Concentration (e.g. MPN or CFU counts) 18. Is raw/unadjusted data or measures of association/effect provided? □ Yes, for all outcomes □ Yes, for some outcomes, specify:_______ □ No, specify reason:______________ Yes: For prevalence data, the following data must be reported • Numerator and denominator, or • proportion + EITHER numerator or denominator For measures of association/effect: • OR/RR/IR/RD reported and its measure of variability (SE, SD, CI) or P-value is provided For continuous measures: • Mean value, sample size and SD • Mean value and SE/CIs Examples of no: a. Graphical data only b. No reporting of raw results c. Just median d. Only p-value e. Only denominator f. Only numerator 19. What lab method was used to identify the microbial hazard? □ Culture □ PCR □ Other:_______________ 20. Extract quantitative prevalence and concentration outcomes (each in a separate column) Prevalence □ Number positive □ Sample size Concentration □ Mean value □ Sample size □ SD □ SE □ Lower CI □ Upper CI □ Units (e.g. MPN and CFU):______________ 21. Other comments: (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 222 TABLE A1.42 Interventions extraction form Question Comments 1. REFID: 2. What type of document is the article? □ Journal article □ Research report □ Conference proceedings □ Other:____________ 3. First author’s last name: □ Enter name:___________ 4. When was the article published? □ Enter year:___________ 5. When was the study conducted? □ Enter month/year to month/year:___ □ Not reported 6. Where was the study conducted? □ Africa □ Asia □ Australia/New Zealand □ Europe □ North America □ Latin America/Caribbean □ Multiple □ Other:_____________ □ Not stated 7. Specify exact country. (cont.) ANNEX 1 223 Question Comments 8. What was the study design? □ Prevalence survey □ Longitudinal prevalence □ Surveillance □ Challenge trial (ChT) □ Controlled trial (CT) □ Quasi-experiment (QE) □ Cohort study □ Case-control study (C-C) □ Cross-sectional study (XS) □ Case report or series □ Outbreak report/investigation □ Other, please specify: Prevalence survey: A study that measures, and may describe (e.g. concentration), the degree of contamination of a LMF by one or more MH at a particular point in time. It does not investigate risk factors for contamination. Longitudinal prevalence: A study that measures, and may describe (e.g. concentration), the degree of contamination of a LMF by one or more MH over two or more time intervals. Samples may either be at the level of the location (e.g. supermarkets and processing facilities) or the product (e.g. a set of ten dry-fermented sausages sampled three times over several weeks). It does not investigate risk factors for contamination. Surveillance: A system that continuously gathers, analyses and interprets data about diseases (or contamination of certain LMFs) and disseminates conclusions of the analyses to relevant organizations in a timely manner. Challenge trial: An experiment where LMF are artificially challenged or exposed to the MH for the purpose of characterizing the MH in the LMF. Controlled trial: An experiment where an intervention is applied to contaminated LMF or relevant environment(s) (e.g. processing facilities) for the purpose of reducing or eliminating the MH. Quasi-experimental: An experiment where an intervention is applied to contaminated LMF or relevant environment(s) (e.g. processing facilities) in a non-randomized fashion for the purpose of reducing or elimination the MH (e.g. before and after trial). Cohort study: An observational study where multiple measurements of a sample population of LMF or affected persons or relevant environment(s) (e.g. processing facilities) are obtained over two or more time periods to identify risk factors for contamination with one or more MH; can be either retrospective or prospective. Case-control study: An observational study where contaminated LMFs or affected persons or relevant environments (e.g. processing facilities) are matched with non-contaminated LMFs, affected persons or relevant environments, respectively, to identify risk factors for contamination with MH or vehicles of MHs. Cross-sectional study: An observational study where LMFs, or relevant environment(s) (e.g. processing facilities) are sampled for the purpose of identifying or characterizing the degree of contamination, as well as potential risk factors for contamination of one or more MH. Case report or series: A descriptive study that tracks affected persons with a foodborne disease for the purpose of identifying the aetiological agent (MH), vehicle of transmission (LMF) and source/point of contamination. Includes preliminary assessment that includes qualitative/quantitative questionnaires of affected persons, collection of clinical specimens, collection of food and environmental samples, but does not include further epidemiological investigation (e.g. case-controls). (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 224 Question Comments 9. Was the intervention conducted under field conditions? □ Yes □ No, laboratory-based under simulated commercial conditions □ No, laboratory-based not simulated conditions Simulated conditions should be applicable or potentially applicable for implementation in a real-world setting. Enter the following section on a separate row for each product/MH combination 10. What LMF product category was investigated? 11. What specific products were investigated? 12. What microbial hazard was investigated? 13. What was the specific bacteria species/ serovar? 14. What intervention(s) was investigated? (For each category specify the exact intervention and dose/duration if available) □ Change in storage conditions: □ pH □ aw □ Temperature □ Starter culture □ Inactivation/lethality step: □ Heat treatment □ High-hydrostatic pressure □ Irradiation □ Ozone □ Chemical(s):______ □ Other:_____ □ Other:_________ 15. At what level in the food chain is the intervention designed to be applied? □ Farm □ Processing plant □ Storage □ Retail □ Ready-to-eat □ Other:_____________ Farm: Location of commercial production/harvesting of LMF (e.g. farm and almond orchard, etc). (i.e. products that will later be sold to consumers). Commercial processing plant: Location of processing and/or packaging of LMF (e.g. dry sausage processing facility, facilities to process fresh spices and herbs into LMF products). Retail: Any location where consumers can purchase LMF (e.g. local grocery stores, supermarkets, farmer’s markets and butcher’s shops). Ready-to-eat: Locations that serve/offer LMF and products containing LMF that can be immediately consumed (e.g. restaurants, delicatessens, cafeterias and buffets, etc). (cont.) ANNEX 1 225 Question Comments 16. For this LMF/microbial hazard/ intervention combination, was there a significant effect? □ Significant (P<0.05) □ Non-significant (P≥0.05) □ No differences assessed Significant: Differences to the microbial levels in the product were significantly impacted by this intervention. Non-significant: There was no significant difference in the microbial hazard reported. 17. For this LMF/microbial hazard/ intervention combination, what was the direction of effect (regardless of significance)? □ Treatment effective □ Treatment not effective □ Not measured 18. How was the outcome reported? Check all that apply □ Prevalence □ Concentration (e.g. MPN or CFU counts) □ D value □ Other:______________ 19. What lab method was used to identify the microbial hazards? □ Culture □ PCR □ Other:_______________ 20. Is raw/unadjusted data or measures of association/effect provided? □ Yes, for all outcomes □ Yes, for some outcomes, specify:_______ □ No, specify reason:______________ Yes: For prevalence data, the following data must be reported • Numerator and denominator, or • proportion + EITHER numerator or denominator For measures of association/effect: • OR/RR/IR/RD reported and its measure of variability (SE, SD, CI) or P-value is provided For continuous measures: • Mean value, sample size and SD • Mean value and SE/CIs Examples of no: a. Graphical data only b. No reporting of raw results c. Just median d. Only p-value e. Only denominator f. Only numerator 21. What was the sample size? 22. Additional comments: RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 226 Appendix F. Summary card evidence charts F1. Cereals and grains Bubble size is proportional to the total number of articles and reports (Total N=142). F2. Confections and snacks Bubble size is proportional to the total number of articles and reports (Total N=87). 44 2 105 11 8 3 41 34 41 12 11 7 5 410 2 3 7 8 18 717137 8 32 B . c er eu s B . c er eu s C . b ot ul in um C . b ot ul in um C . P er fr in g en s C . P er fr in g en s C ro n oc ac te r sp p. C ro n oc ac te r sp p. E . C ol i E . C ol i S al m on el la s pp s. S al m on el la s pp s. L. m on oc yt og en es L. m on oc yt og en es S ta p h. A ur eu s S ta p h. A ur eu s E nt er ob ac te ri ac ea e E nt er ob ac te ri ac ea e Burden of illness Burden of illness Interventions Interventions Prevalence Prevalence 1 1 1 1 1 1 1 ANNEX 1 227 F4. Dried protein products Bubble size is proportional to the total number of articles and reports (Total N=66). F3. Dried fruits and vegetables Bubble size is proportional to the total number of articles and reports (Total N=39). 4 3 6 7 10 12 10 5 2 5 4 4 5 5 5 6 20 22 21 7 10 6 32 3 11 1 B . c er eu s B . c er eu s C . b ot ul in um C . b ot ul in um C . P er fr in g en s C . P er fr in g en s C ro n oc ac te r sp p. C ro n oc ac te r sp p. E . C ol i E . C ol i S al m on el la s pp s. S al m on el la s pp s. L. m on oc yt og en es L. m on oc yt og en es S ta p h. A ur eu s S ta p h. A ur eu s E nt er ob ac te ri ac ea e E nt er ob ac te ri ac ea e Burden of illness Burden of illness Interventions Interventions Prevalence Prevalence RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 228 F5. Honey and preserves Bubble size is proportional to the total number of articles and reports (Total N=58). F6. Nuts and nut products Bubble size is proportional to the total number of articles and reports (Total N=95). 27 16 46 19 3 7 3 2 13 13326 1 22 1 111 932216 1 B . c er eu s B . c er eu s C . b ot ul in um C . b ot ul in um C . P er fr in g en s C . P er fr in g en s C ro n oc ac te r sp p. C ro n oc ac te r sp p. E . C ol i E . C ol i S al m on el la s pp s. S al m on el la s pp s. L. m on oc yt og en es L. m on oc yt og en es S ta p h. A ur eu s S ta p h. A ur eu s E nt er ob ac te ri ac ea e E nt er ob ac te ri ac ea e Burden of illness Burden of illness Interventions Interventions Prevalence Prevalence ANNEX 1 229 F8. Spices, dried herbs and tea Bubble size is proportional to the total number of articles and reports (Total N=129). F7. Seeds for consumption Bubble size is proportional to the total number of articles and reports (Total N=28). 4 12 4 30 2 1 4 2 5 3 12 4 1 2 93 3015 8 14 3 13 12 42 33 1 3 2210 3 1 1 4 14 B . c er eu s B . c er eu s C . b ot ul in um C . b ot ul in um C . P er fr in g en s C . P er fr in g en s C ro n oc ac te r sp p. C ro n oc ac te r sp p. E . C ol i E . C ol i S al m on el la s pp s. S al m on el la s pp s. L. m on oc yt og en es L. m on oc yt og en es S ta p h. A ur eu s S ta p h. A ur eu s E nt er ob ac te ri ac ea e E nt er ob ac te ri ac ea e Burden of illness Burden of illness Interventions Interventions Prevalence Prevalence RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 230 Appendix G. Spice classification table TABLE A1.43 Spice classification table Category Product subcategorya Specific products/notes Fruit/seed Capsicum spp. Paprika, cayenne pepper, chili peppers, other hot and sweet dried capsicum peppers Piper spp. Black, white, green, long pepper Apiaceae Family of aromatic plants including: aniseed, caraway, celery, coriander, dill seed, fennel, chervil Allspice Cumin Also, part of Apiaceae family but separated due to large amount of prevalence data available Nutmeg/mace Other Cardamom, fungreek, mustard, sumac, star anise, ajmud, Bishop’s weed/ajowan, Juniper Root Garlic Ginger Turmeric Other Galangal, onion, asafoetida Herbs/ leaves Origanum spp. Oregano and marjoram Basil Bay leaf Other Mint, rosemary, parsley, sage, thyme, dill weed/ leaves, African spider herb Bark/flower Cinnamon Cloves Saffron Other Geranium, safflower Mixes/ unspecified Curry powder Indian spices Garam masala, tandoori Herb mixes Herbs de province, other/unspecified Unspecified/mixed spices Teas Herbal Chamomile, spearmint, peppermint, lemon balm, linden flower, common nettle, St. John’s-wort, hibiscus, Jews mallow Other/unspecified Black, green, rooibos a NOTE: Raw data has been classified to this level, but prevalence summaries (and meta-analyses) presented in subsequent sections are at the category level. ANNEX 1 231 Appendix H. Articles reporting non-extractable concentration data and prevalence in batch samples for spices, dried herbs and tea TABLE A1.44 Articles reporting non-extractable concentration data for selected microbial hazards in spices Spices/teas investigated Microbial hazards investigated Sources Aniseed, basil, black pepper, caraway, celery, coriander, cumin, dill, fennel, geranium, marjoram, parsley, saffron, tea E. coli, S. aureus, Salmonella spp. (Abou Donia, 2008) Ajmud, allspice, aniseed, asafoetida, black pepper, Bishop’s weed, caraway, cardamom, chili powder, cloves, coriander, cumin, fenugreek, garlic, ginger, mustard, tejpat, turmeric B. cereus, E. coli, Enterobacteriaceae, S. aureus, Salmonella spp. (Banerjee and Sarkar, 2003) Allspice, black pepper, cinnamon, cumin, red pepper Enterobacteriaceae (Beki and Ulukanli, 2008) Unspecified/mixed spices and herbs Enterobacteriaceae (Baumgartner et al., 2009) Tea - herbal C. botulinum (Bianco et al., 2008) Tea - herbal C. botulinum (Bianco et al., 2009) Bay leaves, black pepper powder, chili powder, cloves, curry powder, garlic, ginger, paprika, white pepper C. perfringens, E. coli, S. aureus, Salmonella spp. (Candlish et al., 2001) Unspecified/mixed spices and herbs C. botulinum (Carlin et al., 2004) Red pepper B. cereus (Choo et al., 2007) Tea - herbal E. coli (Cioancă, 2011) Saffron B. cereus, C. perfringens, E. coli, Enterobacteriaceae, S. aureus, Salmonella spp. (Cosano et al., 2009) Unspecified/mixed spices and herbs B. cereus (Daelman et al., 2013) Caraway, chili powder, cloves, coriander, cumin, fennel, fenugreek, garam masala, ginger, mustard, nutmeg, mixed spices, sumac, tandoori, turmeric B. cereus, C. perfringens (Department of Health, State Government of Victoria, Australia, 2007) Unspecified/mixed spices and herbs E. coli (Dogan-Halkman et al., 2003) Black pepper B. cereus, E. coli, S. aureus, Salmonella spp. (Erdogdu and Ekiz, 2013) Tea - black B. cereus, E. coli, Enterobacteriaceae, S. aureus, Salmonella spp. (Favet, 1992) (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 232 Spices/teas investigated Microbial hazards investigated Sources Black pepper powder, white pepper B. cereus, Cronobacter spp., E. coli, S. aureus (Freire and Offord, 2002) Allspice, black pepper powder, coriander, cumin, ginger, red pepper, white pepper B. cereus, E. coli, S. aureus (Hampikyan et al., 2009) Black pepper powder, cinnamon, chili powder, masala S. aureus (Ijabadeniyi and Nokwanda, 2013) Unspecified/mixed spices and herbs Enterobacteriaceae, Cronobacter spp. (Iversen and Forsythe, 2004) Red pepper B. cereus, Enterobacteriaceae (Jeong et al., 2010) Black pepper, cumin, peppermint, red pepper, thyme B. cereus, E. coli, S. aureus, Salmonella spp. (Kahraman and Ozmen, 2009) Unspecified/mixed spices and herbs Enterobacteriaceae (Kandhai et al., 2010) Saffron E. coli, S. aureus (Khazaei et al., 2011) Allspice, aniseed, basil, black pepper, caraway, cardamom, cayenne pepper, chervil, chili powder, Chinese five spice, cinnamon, cloves, coriander, curcuma, curry powder, dill, fennel, ginger, green pepper powder, Herbs de provence, Juniper, marjoram, mint, nutmeg, oregano, paprika, Peruvian pepper, rosemary, saffron, sage, mixed spices, sumac, tandoori, thyme, white pepper Enterobacteriaceae (Kneifel and Berger, 1994) Unspecified/mixed spices and herbs B. cereus, Salmonella spp. (Little, Omotoye and Mitchell, 2003) Red pepper B. cereus (Oh, Koo and Kim, 2012) Unspecified/mixed spices and herbs C. perfringens, E. coli (Osmar Aguilera et al., 2005) Unspecified/mixed spices and herbs E. coli (Rampersad et al., 1999) Bay leaves, black pepper powder, cumin, garlic, oregano C. perfringens (Rodriguez-Romo et al., 1998) Unspecified/mixed spices and herbs B. cereus (Rusul, 1995) Unspecified/mixed spices and herbs B. cereus, C. perfringens, S. aureus (Sheth et al., 2000) Bay leaves, black pepper powder, cayenne pepper, cumin, dill, mint, oregano, white pepper Enterobacteriaceae (Sospedra, Soriano and Mañes, 2010) Unspecified/mixed spices and herbs B. cereus (Te Giffel, 1996) ANNEX 1 233 TABLE A1.45 Articles reporting the prevalence of selected microbial hazards in batch/ shipment samples of spices Spices/teas investigated Microbial hazards investigated Sources Unspecified/mixed spices and herbs Salmonella spp. (EFSA and ECDC, 2010) Unspecified/mixed spices and herbs Salmonella spp.. (EFSA and ECDC, 2011) Unspecified/mixed spices and herbs Salmonella spp.. (EFSA and ECDC, 2012) Unspecified/mixed spices and herbs L. monocytogenes (EFSA and ECDC, 2013) Unspecified/mixed spices and herbs B. cereus, C. perfringens, Salmonella spp. (Food Safety Authority of Ireland, 2005) Black pepper powder, cinnamon, cumin, oregano Salmonella spp. (Rodriguez, Alvarez and Zayas, 1991) Unspecified/mixed spices and herbs B. cereus, C. perfringens, E. coli (Sagoo et al., 2009) Capsicum spp. Salmonella spp. (Van Doren et al., 2013) 234 Annex 2 Summary of recall data on low-moisture foods TABLE A2.1 EU-RASFF–Recall/border rejections of LMF as a result of contamination with microbiological hazards (2010 to June 2014) (EU, 2014) Product category Microbial hazard Recall-rejection frequency/year 2010 2011 2012 2013 2014 Cereal and grains Salmonella spp. - - 118 119 - L. monocytogenes - - - 120 - Bacillus cereus - 121 - - - Cronobacter sakazakii - - 122 - - Confections and snacks23 Salmonella spp. 1 - 1 1 1 Dried fruits and vegetables Salmonella spp.24 - 1 1 2 4 L. monocytogenes25 - - - 1 1 Bacillus spp. - - - 1 - B. cereus26 - - 2 2 - Dried protein products Salmonella spp.27 1 1 - 3 1 Salmonella spp. + Cronobacter sakazakii28 1 L. monocytogenes29 - - - 1 - Nut and nut products Salmonella spp.30 5 3 9 4 1 B. cereus + Enterococcus31 1 Faecal Streptococci31 - - 6 - - 18 Linked to organic bread meal mix. 19 Linked to muesli with nuts. 20 Linked to pasta tortellini so unclear if pasta or filling. 21 Linked to couscous. 22 Linked to rice cereal for children. 23 Products included mini marshmallow, maltodextrin, galacto-oligosacaride and chocolate bar with coconut. 24 Three recalls linked with dried black mushrooms, one with dried sliced mushroom, one with chlorella algae powder, one dried chlorella algae, one dehydrated red onions and one moringa powder. 25 Both recalls linked enoki mushrooms. 26 Recalls were linked to dried mushrooms, dried mulberries and dates. 27 Five recalls were linked to dry sausages, and the other two were skimmed milk powder, and soy protein product. 28 Recall was associated with dried infant formulae. 29 Recall associated with dried sausage. 30 Eleven recalls were for pine nuts, nine for coconut flour/desiccated coconut and two for hazelnuts. 31 Implicated product was coconut flour/desiccated coconut. (cont.) 235ANNEX 2 Product category Microbial hazard Recall-rejection frequency/year 2010 2011 2012 2013 2014 Spices, dried herbs and tea32 Salmonella spp. 3 14 21 14 9 Bacillus cereus - 4 2 3 3 Escherichia coli - - - 1 1 C. perfringens + B. cereus + Salmonella - 1 - - - Enterobacteriaceae - 1 - 1 - Seeds for consumption Salmonella spp.33 1 2 11 9 6 B. cereus + Salmonella + Enterobacteriaceae - 1 - - - Honey and preserves - - - - - - TABLE A2.2 USFDA Recalls (USA market) of LMF from 2009 up to June 2014 related to microbial hazards (USFDA, 2014a) Product category Microbial hazard Recall frequency/year 2009 2010 2011 2012 2013 2014 Cereal and grains Salmonella spp.34 - 2 1 2 - L. monocytogenes35 - - - 2 - - Confections and snacks Salmonella spp.36 4 12 1 17 1 Bacillus cereus37 - - 1 - - C. botulinum38 - - 2 - - S. aureus39 1 L. monocytogenes - - - 1 - Dried fruits/ vegetables Salmonella spp.40 - 1 - 1 - - Dried protein products Salmonella spp.41 5 5 2 3 - - C. botulinum42 - 2 - - - - 32 Recalls mainly linked to cumin, curry, oregano, black pepper, spice mix, ginger powder and basil. 33 Twenty-six of these recalls were for sesame seeds and Tahini. 34 Recalls were for cereal, baking mix and soybean flour. 35 Recalls were associated with popcorn and cake. 36 Recalls were linked to a range of products including snack mix, candy and bars containing peanut or peanut butter; corn chips, cookies and snack crackers. 37 Recall of cookies. 38 Recall of black bean tortilla. 39 Recall of gingerbread houses. 40 Recalls of vegetable soup mix and prune concentrate dietary supplement. 41 Recalls were of non-fat milk powder, prebiotic formula powder, kids powder dietary supplements, powdered protein products, whey protein isolate, instant beef soup mix, gravy mix and protein bistro box. 42 Recalls of dried fish and dried seafood products. (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 236 Product category Microbial hazard Recall frequency/year 2009 2010 2011 2012 2013 2014 Nut and nut products Salmonella spp.43 485 6 5 20 3 E. coli O157:H744 - - 1 - - - L. monocytogenes45 - - - - - 3 Spices, dried herbs and tea Salmonella spp. 5 20 2 5 1 7 Seeds for consumption Salmonella spp.46 - 2 - 1 2 3 Honey and preserves - - - - - - - TABLE A2.3 USFDA Import Refusals of LMF as a result of microbial contamination frequency (USA) from 2012 up to 2014. Note that product is the most routinely sampled and tested for Salmonella spp. Sampling for other microbes is determined by the product’s risk category (USFDA, 2014b) Product category Microbial hazard Refusal frequency (%)/year 2012 2013 2014 Cereal and grains47 Salmonella spp. 10 4 1 Confections and snacks Salmonella spp. 25 20 11 Dried fruits/vegetables48 Salmonella spp. 5 4 1 Dried protein products - - - - Nut and nut Products Salmonella spp. 4 14 3 Vibrio cholerae49 1 2 - Listeria +Salmonella + V. cholerae49 - 1 - Spices, dried herbs and tea Salmonella spp. 226 229 80 Seeds for consumption50 Salmonella spp. 17 13 7 Honey and preserves - - - - 43 Almost all of the recalls were due to peanuts and pistachios contaminated with Salmonella spp. Many companies recalled related products containing the suspected peanut or pistachios. 44 Hazelnuts and mixed nuts. 45 Walnuts. 46 Recalled products included chia seed powder, sesame seeds and tahini sesame paste. 47 Products recalled included products included instant noodles, barley flour, mixed cereal, soybean flour, grain, oat flakes and bread rolls. 48 Recalled products included dried tomatoes, dried spinach, dried berry, dried fungus and vegetables. 49 Linked to coconut. 50 Products recalled included sesame seeds, sesame seed paste, pumpkin seeds, melon seeds and lotus seed. 237ANNEX2 REFERENCES IN ANNEX 2 European Union (EU). 2014. Food and Feed Safety Alerts. [online]. [Cited 20 July 2021]. https://webgate.ec.europa.eu/rasff-window/screen/search USFDA. 2014a. Recalls, Market Withdrawals and Safety Alerts. [online]. [Cited 20 July 2021]. http://www.fda.gov/Safety/Recalls/ USFDA. 2014b. Import Refusals. [online]. [Cited 20 July 2021]. https://www.fda.gov/ industry/actions-enforcement/import-refusals 238 Annex 3 Technical details of the MCDA ranking approach A3.1 STEP 1: IDENTIFICATION OF FUNDAMENTAL OBJECTIVES The first step in the identification of fundamental objectives was the development of a means-end network of objectives (Keeney 1996; Montibeller and Belton, 2006). This helped the experts to consider the links between means available to mitigate risks (bottom of the diagram in Figure A3.1) and ends that policy makers are pursuing (top of the diagram in Figure A3.1), as well as the links between the former and the latter. For example, according to the diagram, knowing the pathogen of concern leads to knowledge of the root of contamination, which leads to knowledge about how to control exposure, which is a means to minimize the burden of disease and therefore increase the confidence in the health system (an ultimate objective). The objectives on the top, with only in-arrows, are the ultimate objectives to be achieved by adequate management of LMF risks, objectives which are to reduce the cost of the health systems, to increase confidence in the health system and perceived safety of food, to reduce costs to the food industry and to improve countries’ economies. As can be seen in Figure A3.1 below, four fundamental objectives in terms of achieving these have been identified. These are minimizing the burden of foodborne disease, facilitating international trade, and several descriptors relating to the production and consumption of the food. ANNEX 3 239 FIGURE A3.1 Means-end network of objectives for managing LMF risks D ec re as e pr ev al en ce a nd le ve ls o f d is ea se ca us in g or ga ni sm K no w t he pa th og en of c on ce rn K no w h ow t o co nt ro l e xp os ur e K no w t he ro ot o f co nt am in at io n M in im iz e hu m an ex po su re t o pa th og en sM ax c on su m er co nfi de nc e on fo od C on fid en ce o n th e he al th s ys te mR ed uc e co st in he al th s ys te m M ax p er ce iv ed sa fe ty o f f oo d R ed uc e co st fo r th e fo od in du st ry Im pr ov e co un tr ie s’ ec on om ic s C on fid en ce o f im po rt er c ou nt ry Im pl em en ta ti on eq ui va le nt fo od s af et y sy st em s In fo rm fo od s af et y m an ag em en t A ss es s th e fe as ib ili ty /e ffi ca cy of c on tr ol m ea su re s K no w t he di ve rs it y an d co m pl ex it y of th e pr od uc ti on ch ai n (f ro m fa rm to fo rk ) K no w w ha t th e co nt ro l m ea su re s ar e P ro du ce s af e fo od B ur de n of d is ea se (f re qu en cy a nd se ve ri ty ) En ds M ea ns K no w th e w ay th e fo od is p ro du ce d (d ev el op ed vs d ev el op in g co un tr ie s) K no w w ho is co ns um in g (d em og ra ph ic s) K no w th e w ay th e fo od is c on su m ed (d ev el op in g vs d ev el op ed co un tr ie s) K no w h ow m uc h is co ns um ed (v ol um e) Fa ci lit at e in te rn at io na l tr ad e RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 240 A3.2 STEP 2: DEFINITION OF EVALUATION CRITERIA The evaluation criteria associated with the fundamental objectives must observe a strict set of properties to enable a quantitative multi-criteria value model to be built up (Keeney 1996; Belton and Stewart, 2002; Franco and Montibeller, 2011), which were checked in this step of the project: • Essential and Complete. They should consider all the fundamental objectives involved in the evaluation. • Understandable. They should have a clear meaning for all the members of the expert group involved in the evaluation. • Operational. It should be possible to gather evidence about the options being assessed. • Non-redundant. They should not measure the same concern twice. • Concise. It should be the smallest number of objectives required for the analysis. • Preferentially independent. If it is possible to measure the performance of options on one criterion disregarding their performance on all other criteria, then a simple weighted sum can be used to aggregate the impacts. A3.3 STEP 3: DEFINITION OF ATTRIBUTES There were two types of attributes employed in this ranking exercise: • Natural attributes. They measure directly the concern expressed by the objective, are of general use and have a common interpretation (e.g. USD billion/year of trade for assessing the fundamental objective International Trade). • Proxy attributes. They measure indirectly the concern expressed by the fundamental objective, by assessing the degree of achievement of its associated means objective (e.g. proportion without a kill step to assess the vulnerability of a LMF category to contamination during food production). Whenever possible available natural attributes were used, as they reduce the ambiguity of the assessment and measure directly the concern expressed by the fundamental objective (Keeney and Gregory, 2005). Proxy attributes were carefully selected or developed to assess as directly as possible the impact of concern. A3.4 STEP 4: EVIDENCE GATHERING ABOUT IMPACTS Details of data and evidence collection and use are provided in Annexes 4 to 7. ANNEX 3 241 A3.5 STEP 5: EVALUATION OF NORMALIZED IMPACTS The scale for measuring the normalized impact of each LMF category on every attribute was normalized between 0 (for the lowest impact) to 100 (for the highest impact). This is therefore a linear function, with the properties associated with multi-attribute value theory (Dyer and Sarin, 1979). A3.6 STEP 6: ELICITATION OF CRITERIA WEIGHTS A3.6.1 Elicitation of the weights for subcriteria under food consumption (C3) The experts were presented with a set of hypothetical LMF categories (notice that these categories might not exist in practice) as shown in Figure A3.2, considering the lower and upper bound of each attribute. For example, the hypothetical LMF category Y1 has the highest (H) level on the Average Serving subcriteria (C3.1) and the lowest (L) level on all the other criteria. The LMF category Y0 has all impacts at the lowest level. The hypothetical LMF category with all impacts at the lowest level (Y0) receives a score of zero (swing weight SW3.0 = 0). Participants were asked to identify among the other hypothetical LMF categories (Y1, Y2, or Y3) which one had the most serious impact. Two categories were selected by them – Y1 and Y2 – and thus received a score of 100 (baseline swing weights): SW3.1 = 100; SW3.2 = 100. The baseline swing weight of the next category (Y3) was defined within these two extreme anchors by the group as SW3.3 = 30. These baseline swing weights (SW’s) are then normalized into baseline weights (w’s) so they sum up 1 as follows: w31 = SW31/∑SW3i = 100/230 = 43.5%; w32 = SW32/∑SW3i = 100/230 = 43.5%; w33 = SW33/∑SW3i = 30/230 = 13.0%. There were some differences of opinions among experts in their individual estimates, with the ranges defined as: SW3.1 = [70,100]; SW3.2 = [70,100]; SW3.3 = [30,70]. For the normalized weights the equivalent ranges were therefore: w31 = [35.0%,43.5%]; w32 = [35.0%,43.5%]; w33 = [13.0%, 25.9%]. The ranges are obtained when a certain SW is altered (e.g. SW3.1 is changed from 100 to 70) keeping the other SWs (e.g. SW3.2 and SW3.3) constant. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 242 FIGURE A3.2 Hypothetical LMF categories for the elicitation of weights for the subcriteria under C3 A3.6.2 Elicitation of the weights for subcriteria under food production (C4) The same procedure detailed above was employed for eliciting the weights for the subcriteria under the food production criterion (C4). The experts were presented with a set of hypothetical LMF categories as shown in Figure A3.3, considering the lower and upper bound of each attribute. The hypothetical LMF category Z0 received a swing weight of zero (SW4.0 = 0). The experts were asked to identify among the other hypothetical LMF categories (Z1, Z2, or Z3) which one has the most serious impact. The category Z3 was selected and thus the baseline swing weight set as SW4.3 = 100. The second most serious category was, according to the group, Z2 and the baseline swing weight was defined by the experts as SW4.2 = 70. The third most serious category was Z1 with the baseline swing weight defined by the group as SW4.1 = 40. These baseline swing weights were then normalized into baseline weights so they sum up 1 as follows: w41 = SW41/∑SW4i = 40/210 = 19.0%; w42 = SW42/∑SW4i = 70/210 = 33.3%; w43 = SW43/∑SW4i = 100/210 = 47.6%. C3.1 – Av. serving C3.2 – Vulnerability C3.3 – Cons. mishandling H (185g/d) H (33.5%v) H (25%m) Cat Y1 L (1.1g/d) L (12.7%v) L (5%m) C3.1 – Av. serving C3.2 – Vulnerability C3.3 – Cons. mishandling H (185g/d) H (33.5%v) H (25%m) Cat Y3 L (1.1g/d) L (12.7%v) L (5%m) C3.1 – Av. serving C3.2 – Vulnerability C3.3 – Cons. mishandling H (185g/d) H (33.5%v) H (25%m) Cat Y2 L (1.1g/d) L (12.7%v) L (5%m) C3.1 – Av. serving C3.2 – Vulnerability C3.3 – Cons. mishandling H (185g/d) H (33.5%v) H (25%m) Cat Y0 L (1.1g/d) L (12.7%v) L (5%m) SW3.1=? SW3.3=? SW3.2=? SW3.0=0 Normalized SW (range) value(%) (range) 100 (70, 100) 43.5 (35.0, 43.5) 100 (70, 100) 43.5 (35.0, 43.5) 30 (30-70) 13.0 (13.0, 25.9) 0 – – – ANNEX 3 243 FIGURE A3.3 Hypothetical LMF categories for the elicitation of weights for the subcriteria under C4 A3.6.3 Elicitation of the weights for the main criteria The same procedure was employed for eliciting the weights for the four main criteria of the model. The experts were presented with a set of hypothetical LMF category as shown in Figure A3.4, considering the lower and upper bound of each attribute. The hypothetical LMF category X0 received a swing weight of zero (SW0 = 0). Participants were asked to identify among the other hypothetical LMF categories (X1, X2, X3, or X4) which one had the most serious impact. Category X2 was selected by the experts, and thus the baseline swing weight set as SW2 = 100. The second most serious category according to them was X4, and the baseline swing There were some differences of opinions among experts, regarding the swings for the first and second subcriterion with the ranges defined as: SW4.1 = [30, 50]; SW4.2 = [60, 80]. For the normalized weights the equivalent ranges were therefore: w4.1 = [15.0%, 22.7%]; w4.2 = [30.0%, 36.4%]. C4.1 – Prop risk contam. C4.2 – Prop no kill step C4.3 – Prev pathogen H (40%r) H (85%k) H (11.7p) Cat Z1 L 10%r) L (10%k) L (0.8p) C4.1 – Prop risk contam. C4.2 – Prop no kill step C4.3 – Prev pathogen H (40%r) H (85%k) H (11.7p) Cat Z3 L 10%r) L (10%k) L (0.8p) C4.1 – Prop risk contam. C4.2 – Prop no kill step C4.3 – Prev pathogen H (40%r) H (85%k) H (11.7p) Cat Z2 L 10%r) L (10%k) L (0.8p) C4.1 – Prop risk contam. C4.2 – Prop no kill step C4.3 – Prev pathogen H (40%r) H (85%k) H (11.7p) Cat Z0 L 10%r) L (10%k) L (0.8p) SW4.1=? SW4.3=? SW4.2=? SW4.0=0 Normalized SW (range) value(%) (range) 40 (30, 50) 19.0 (14.0, 22.7) 70 (60, 80) 33.3 (30.0, 36.4) 100 – 47.6 – 0 – – – RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 244 weight was defined by the experts as SW4 = 75. The third most serious category was X3 with the baseline swing weight defined by them as SW3 = 50. The fourth most serious category was X1 with the baseline swing weight of SW1 = 45 by the group. These baseline swing weights were then normalized into baseline weights: w1 = SW1/∑SWi = 45/270 = 16.7%; w2 = SW2/∑SWi = 100/270 = 37.0%; w3 = SW3/∑SWi = 50/270 = 18.5%; w4 = SW4/∑SWi = 75/270 = 27.8%. There were some differences of opinions among experts, regarding the swings for the first, third and fourth criteria, with the ranges defined as: SW1 = [30, 60]; SW3 = [40, 65]; SW4 = [70, 80]. For the normalized weights the equivalent ranges were therefore: w1 = [11.8%, 21.1%]; w3 = [15.4%, 22.8%]; w4 = [26.4%, 29.1%]. FIGURE A3.4 Hypothetical LMF categories for the elicitation of weights for main criteria C4 – International Trade C2 – Burden Disease C3 – Food consumption C4 - Food Production H USD 118.6bi H 136.4 DALYs H (185g/d; 33.5%v; 25%m) H (40%r; 85%k;11.7p) Cat X1 L USD 1.5bi L 18.4 DALYs L (1.1g/d; 12.7%v,5%m) L (10%r; 10%k;0.8p) C4 – International Trade C2 – Burden Disease C3 – Food consumption C4 - Food Production H USD 118.6 bi H 136.4 DALYs H (185g/d; 33.5%v; 25%m) H (40%r; 85%k;11.7p) Cat X2 L USD 1.5 bi L 18.4 DALYs L (1.1g/d; 12.7%v,5%m) L (10%r; 10%k;0.8p) C4 – International Trade C2 – Burden Disease C3 – Food consumption C4 - Food Production H USD 118.6 bi H 136.4 DALYs H (185g/d; 33.5%v; 25%m) H (40%r; 85%k;11.7p) Cat X3 L USD 1.5 bi L 18.4 DALYs L (1.1g/d; 12.7%v,5%m) L (10%r; 10%k;0.8p) C4 – International Trade C2 – Burden Disease C3 – Food consumption C4 - Food Production H USD 118.6 bi H 136.4 DALYs H (185g/d; 33.5%v; 25%m) H (40%r; 85%k;11.7p) Cat X4 L USD 1.5 bi L 18.4 DALYs L (1.1g/d; 12.7%v,5%m) L (10%r; 10%k;0.8p) C4 – International Trade C2 – Burden Disease C3 – Food consumption C4 - Food Production H USD 118.6 bi H 136.4 DALYs H (185g/d; 33.5%v; 25%m) H (40%r; 85%k;11.7p) Cat X0 L USD 1.5 bi L 18.4 DALYs L (1.1g/d; 12.7%v,5%m) L (10%r; 10%k;0.8p) SW1=? SW3=? SW2=? SW4=? SW0=? Normalized SW (range) value(%) (range) 45 (30, 60) 16.7 (11.8, 21.1) 100 – 37.0 – 50 (40, 65) 18.5 (15.4, 22.8) 75 (70, 80) 27.8 (26.4, 29.1) 0 – – – ANNEX 3 245 FIGURE A3.5 Sensitivity analysis for the weight of criterion C3.1 (average serving) Figure A3.6 presents a sensitivity analysis of the overall normalized impact of every LMF category as the weight of subcriterion C3.2 (vulnerability of consumers) is ranged from 0 to 100 percent. The baseline weight of this criterion in the model is w3.2 = 43.5 percent and is indicated by the vertical line. If the weight of this criterion A3.7 STEP 7: ROBUSTNESS ANALYSIS A3.7.1 Sensitivity to criteria weights – subcriteria of the model We first analyse the three subcriteria that decompose criterion C3 (food consumption), followed by the three subcriteria that decompose criterion C4 (food production). We start with the former subcriteria. Figure A3.5 presents a sensitivity analysis of the overall normalized impact of every LMF category as the weight of criterion C3.1 (average serving) is ranged from 0 to 100 percent. The baseline weight of this criterion in the model is w3.1 = 43.5 percent as indicated by the vertical line. If the weight of this criterion were further increased, to the right of the vertical line, Cat 1’s overall normalized impact would further increase. However, if the weight of this criterion were decreased, there would be a point where Cat 1 would intersect with Cat 4 (point ➄: w’3.1 = 31.0 percent). Any further reduction of weight beyond this point ➄ should lead to the selection of Cat 4. Notice that the range of weights provided by the experts for this criterion (w31 = [35.0 percent, 43.5 percent]) is above point ➄, thus maintaining Cat 1 as the highest scored category. O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W3.1 = 43.5% Normalized weight W3.1(Average Serving) 5 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 246 were increased, to the right of the vertical line, there would be a point where Cat 1 would intersect with Cat 4 (point ➅: w’3.2 = 55.8 percent). If the weight of this criterion were further increased beyond this point ➅, Cat 4 should be selected. For any level below point ➅, Cat 1 remains the highest in the rank. Notice that the range of weights provided by the experts for this criterion (w32 = [35.0 percent, 43.5 percent]) is below point ➅, thus maintaining Cat 1 as the highest scored category. FIGURE A3.6 Sensitivity analysis for the weight of criterion C3.2 (vulnerability of consumers) Figure A3.7 presents a sensitivity analysis of the overall normalized impact of every LMF category as the weight of subcriterion C3.3 (consumer mishandling) is ranged from 0 to 100 percent. The baseline weight of this criterion in the model is w3.3 = 13.0 percent and is indicated by the vertical line. If the weight of this criterion were increased, to the right of the vertical line, there would be point where Cat 1 intersects with Cat 4 (point ➆: w’3.3 = 69.2 percent). If the weight of this criterion were further increased beyond this point ➆, Cat 4 should be selected. For any level below point ➆, Cat 1 remains the highest in the rank. Notice that the range of weights provided by the experts for this criterion (w33 = [13.0 percent, 25.9 percent]) is below point ➆, thus maintaining Cat 1 as the highest scored category. O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W3.2 = 43.5% Normalized weight W3.2 (Vulnerability Consumers) 6 ANNEX 3 247 We will now analyse the three subcriteria that decompose criterion C4 (food production). Figure A3.8 presents a sensitivity analysis of the overall normalized impact of every LMF category as the weight of subcriterion C4.1 (risk of contamination) is ranged from 0 to 100 percent. The baseline weight of this criterion in the model is w4.1 = 19.0 percent and is indicated by the vertical line. If the weight of this criterion were increased, to the right of the vertical line, there would be a point where Cat 1 would intersect with Cat 4 (point ➇: w’4.1 = 42.3 percent). If the weight of this criterion were further increased beyond this point ➇, Cat 4 should be selected. For any level below point ➇, Cat 1 remains the highest in the rank. Notice that the range of weights provided by the experts for this criterion (w41 = [15.0 percent, 22.7 percent] is below point ➇, thus maintaining Cat 1 as the highest scored category. FIGURE A3.7 Sensitivity analysis for the weight of criterion C3.3 (consumer mishandling) O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W3.3 = 13.0% Normalized weight W3.3 (Consumer Mishandling) 7 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 248 FIGURE A3.8 Sensitivity analysis for the weight of criterion C4.1 (risk of contamination) Figure A3.9 presents a sensitivity analysis of the overall normalized impact of every LMF category as the weight of criterion C4.2 (proportion without kill step) is ranged from 0 to 100 percent. The baseline weight of this criterion in the model is w4.2 = 33.3 percent as indicated by the vertical line. If the weight of this criterion were further increased, to the right of the vertical line, Cat 1’s overall normalized impact would further increase. However, if the weight of this criterion were decreased, there would be a point where Cat 1 intersects with Cat 4 (point ➈: w’4.2 = 19.2 percent). Any further reduction of weight beyond this point ➈ should lead to the selection of Cat 4. Notice that the range of weights provided by the experts for this criterion (w42 = [30.0 percent, 36.4 percent]) is above point ➈, thus maintaining Cat 1 as the highest scored category. O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W4.1 = 19.0% Normalized weight W4.1 (Risk of Contamination) 8 O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W4.2 = 33.3% Normalized weight W4.2 (Proportion without kill step) 9 FIGURE A3.9 Sensitivity analysis for the weight of criterion C4.2 (proportion without kill step) ANNEX 3 249 FIGURE A3.10 Sensitivity analysis for the weight of criterion C4.3 (prevalence of pathogen) These analyses of sensitivity on weights show that the ranking is quite robust to changes of priorities, with either Cat 1 or Cat 4 always being on the top position. There are no intersection points very near the baseline weights and, in all cases except for criterion 1 (Figure 3.3 of the main report), there was not a range of weights provided by the experts that reached any intersection point. (For criterion 1, the lower bound of the range provided by experts was only slightly below the intersection point ➀.) In addition to this analysis, the four graphs for the main criteria (from Figure 3.3 to Figure 3.6 of the main report) can help the policy makers in identifying the category to be selected if their priorities increase/decrease from the baseline weights suggested by the expert group during the project. Finally, Figure A3.10 presents a sensitivity analysis of the overall normalized impact of every LMF category as the weight of subcriterion C4.3 (presence of pathogen) is ranged from 0 to 100 percent. The baseline weight of this criterion in the model is w4.3 = 47.6 percent and is indicated by the vertical line. If the weight of this criterion were increased, to the right of the vertical line, there would be point where Cat 1 would intersect with Cat 4 (point ➉: w’4.3 = 76.9 percent). If the weight of this criterion were further increased beyond this point ➉, Cat 4 should be selected. For any level below point ➉, Cat 1 remains the highest in the rank. Notice that experts did not contemplate a further increase on this parameter during the elicitation of weights. O ve ra ll im pa ct (d is -v al ue ) 100 90 80 70 60 50 40 30 20 10 0 Cat 1 Cat 2 Cat 3 Cat 4 Cat 5 Cat 6 Cat 7 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% W4.3 = 47.6% -Normalized weight W4.3 (Prevalence of pathogen) 10 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 250 A3.7.2 Sensitivity to the estimation of impacts An analysis of robustness considering the uncertainties about the evidence available (impacts), which was used to calculate the normalized impacts of each LMF category, was also considered. (As a simplifying assumption, we are considering throughout this analysis that the criteria weights remain fixed, as the baseline weights, despite the changes in the ranges of the attributes.) Three criteria were expert-derived estimates given the lack of available data and the extensive expertise of the group. We have considered the consequence of different estimates of Most Likely (ML) values across the expert group. For criterion C3.3 (consumer mishandling), we considered the experts’ baseline estimates used in the results (Table 3.4 of the main report), as well as their lower ML and upper ML estimates (Table A7.1 of Annex 7) and calculated the overall normalized impact with these three sets of inputs, as shown in Figure A3.11. The ranking for the three sets of estimates remains the same in the three set of inputs, with Cat 1 followed by Cat 4 in each case. 70 60 50 40 30 20 10 0 58 54 32 21 10 45 59 33 21 54 42 10 46 57 32 21 54 42 10 45 42 Base-line Lower ML estimates Expert estimates Cat 1 Cereals and grains Cat 2 Confections and snacks Cat 3 Dried fruits and vegetables Cat 4 Dried protein products Cat 5 Nuts and nut products Cat 6 Seeds for consumption Cat 7 Spices, dried herbs and tea O ve ra ll im pa ct (d is -v al ue ) Upper ML estimates FIGURE A3.11 Sensitivity analysis for the input estimates – criterion C3.3 ANNEX 3 251 FIGURE A3.12 Sensitivity analysis for the input estimates – criterion C4.1 For criterion C4.2 (proportion without a kill step) the experts’ baseline estimates used in the results (Table 3.5 of the main report) as well as their lower ML and upper ML estimates were considered (Table A7.3 of Annex 7) and calculated the overall normalized impact with these three sets of inputs, as shown in Figure A3.13. The ranking for the three sets of estimates remains the same for the baseline and upper estimates, with Cat 1 followed by Cat 4. However, the overall normalized impact of Cat 4 is the same as Cat 1 when using the lower estimates. For criterion C4.1 (risk of contamination), the experts’ baseline estimates used in the results (Table 3.5 of the main report) as well as their lower ML and upper ML estimates were considered (Table A7.2 of Annex 7), and the overall normalized impact with these three sets of inputs was calculated, as shown in Table A3.12. The ranking for the three sets of estimates remains the same for the baseline and upper estimates, with Cat 1 followed by Cat 4. However, the overall normalized impact of Cat 4 is slightly higher than Cat 1 when using the lower estimates. 70 60 50 40 30 20 10 0 Base-line Lower ML estimates Expert estimates Cat 1 Cereals and grains Cat 2 Confections and snacks Cat 3 Dried fruits and vegetables Cat 4 Dried protein products Cat 5 Nuts and nut products Cat 6 Seeds for consumption Cat 7 Spices, dried herbs and tea O ve ra ll im pa ct (d is -v al ue ) Upper ML estimates 58 32 21 54 42 10 45 57 32 21 58 43 10 45 59 32 21 58 43 10 46 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 252 FIGURE A3.13 Sensitivity analysis for the input estimates – criterion C4.2 Finally, the three set of estimates together, for the subcriteria C3.3, C4.1 and C4.2, were considered. The experts’ baseline estimates for these three subcriteria as well as their lower ML and upper ML estimates were employed, and the overall normalized impact with these three sets of inputs calculated, as shown in Figure A3.14. Cat 4 is higher than Cat 1 for the lower estimates, and the former is also slightly higher than the latter for the upper estimates. This is mainly due to a wider range of estimates among experts for Cat 4 when compared with Cat 1. Another sensitivity analysis that we conducted was on the estimates for criterion C3.1 (average serving). The baseline estimates employed the mean values to calculate overall normalized impact, which we now compared with the overall results for high volume consumers (P95) (Table 3.4 of the main report). As Table A3.15 shows, there is no change of ranking if the latter estimates were used. The much wider range of normalized impacts if these estimates (high volume 70 60 50 40 30 20 10 0 Base-line Lower ML estimates Expert estimates Cat 1 Cereals and grains Cat 2 Confections and snacks Cat 3 Dried fruits and vegetables Cat 4 Dried protein products Cat 5 Nuts and nut products Cat 6 Seeds for consumption Cat 7 Spices, dried herbs and tea O ve ra ll im pa ct (d is -v al ue ) Upper ML estimates 58 55 58 32 31 31 21 20 23 54 55 55 42 38 43 10 8 11 45 46 45 ANNEX 3 253 consumers) were employed would tend to further increase the weight of this criterion, above its baseline value (w3.1 = 43.5 percent). However, as analysed in Figure A3.5, an increase of its weight would not change the ranking – with Cat 1 remaining the one with the highest score. The ranking is therefore very robust to the two sets of estimates available for C3.1. FIGURE A3.14 Sensitivity analysis for the input estimates – criteria C3.3, C4.1 and C4.2 70 60 50 40 30 20 10 0 Base-line Lower ML estimates Expert estimates Cat 1 Cereals and grains Cat 2 Confections and snacks Cat 3 Dried fruits and vegetables Cat 4 Dried protein products Cat 5 Nuts and nut products Cat 6 Seeds for consumption Cat 7 Spices, dried herbs and tea O ve ra ll im pa ct (d is -v al ue ) Upper ML estimates 58 55 58 32 32 31 21 20 23 54 59 59 42 39 44 10 8 12 45 47 47 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 254 A3.8 REFERENCES IN ANNEX 3 Belton, V. & Stewart, T.J. 2002. Multiple Criteria Decision Analysis: An Integrated Approach. Norwell, MA, Springer. Dyer, J.S. & Sarin, R.K. 1979. Measurable Multiattribute Value Functions. Operations Research, 27(4): 810–822. Franco, L.A. & Montibeller, G. 2011. Problem Structuring for Multicriteria Decision Analysis Interventions. Wiley Encyclopedia of Operations Research and Management Science, Hoboken, NJ, USA, John Wiley & Sons, Inc. Keeney, R.L. 1996. Value-Focused Thinking: A Path to Creative Decision making. Cambridge, MA, Harvard University Press. Keeney, R.L. & Gregory, R.S. 2005. Selecting attributes to measure the achievement of objectives. Operations Research, 53(1): 1–11. Montibeller, G. & Belton, V. 2006. Causal maps and the evaluation of decision options—a review. Journal of the Operational Research Society, 57(7): 779–791. FIGURE A3.15 Sensitivity analysis for the input estimates – criterion C3.1 70 60 50 40 30 20 10 0 Base-line estimates (Mean) High consumers level estimates (P95) Cat 1 Cereals and grains Cat 2 Confections and snacks Cat 3 Dried fruits and vegetables Cat 4 Dried protein products Cat 5 Nuts and nut products Cat 6 Seeds for consumption Cat 7 Spices, dried herbs and tea O ve ra ll im pa ct (d is -v al ue ) 58 32 21 54 42 10 45 58 37 24 54 43 12 45 255 Annex 4 Trade data TABLE A4.1 Export value in US dollars of each of the categories of LMF based on the data available for 2011 in FAOSTAT. Category Export value in US dollars in 2011 (x1000) Comments/Limitations Cereals and grains 118 594 636 Amount adjusted to account for proportion of grains going for human consumption Subcategories Unprocessed cereals 42 678 253 Partly processed cereals 34 317 536 Cereal-based products 41 598 847 Confections and snacks 58 124 835 Very limited data available; may be partly included in other categories (cereals and grains, dried vegetables but not possible to segregate out) Subcategories Chocolate and cocoa 42 465 315 Non-chocolate confectionary 9 677 740 Snacks 5 981 780 Dried fruits and vegetables 15 211 735   Subcategories   Dried fruits 5 033 350   Dried Vegetables 10 178 385 Includes vegetable flours Dried protein products 22 800 655   Subcategories   Dried meat products n/a Data aggregated with all preserved meats and not possible to disaggregate. Proportion meeting definition for this work considered minimal Dried dairy products 21 729 252   Dried egg products 305 936   Dried vegetable protein products 765 467 Based on an assumption that 2% of total soybean production is consumed by humans in foods (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 256 Category Export value in US dollars in 2011 (x1000) Comments/Limitations Dried fish products n/a Data aggregated with all preserved fish and not possible to disaggregate. Proportion meeting definition of this work considered minimal Nut and nut products 20 338 654   Subcategories   Tree nuts 17 964 125   Ground nuts 2 374 529 Includes peanut butter Seeds for consumption 1 150 471 As many were used for oil production figure adjusted to account for this – based on available data; 10% assumed to be for direct human consumption Spices, Dried herbs and teas 14 938 847   Subcategories   Spices and dried herbs 7 150 458   Teas 7 788 389   REFERENCE IN ANNEX 4 FAO. 2017. FAOSTAT [online]. Rome. [Cited 15 February 2017]. www.fao.org/faostat/ en/#home 257 Annex 5 Calculation of DALYS TABLE A5.1 Calculation of the DALY for each of the microorganisms under consideration based on DALY per 1 000 cases of illness in the Netherlands (Havelaar et al., 2012) and cases of illness per organism and per LMF category identified in the structured scoping review (Annex 1) Cereals and grains Confections and snacks Dried Fruit and Vegetables Dried protein products DALY for each pathogen Pathogens Cases Total DALY Cases Total DALY Cases Total DALY Cases Total DALY 0.143 E. coli 313 44.759 11 1.573 0 0 0.049 Salmonella 257 12.593 1 448 70.952 669 32.781 1 589 77.861 1.45 Clostridium botulinum   0 0 0 16 23.2 0.0023 Bacillus cereus 577 1.3271 4 0.0092 0 0 0.0032 Clostridium perfringens 369 1.1808 0 0 0 0.0026 Staphylococcus aureus 152 0.3952 0 0 13 606 35.3756 TOTAL 1 668.0 60.3 1 463.0 72.5 669.0 32.8 15 211.0 136.4 Nuts and nut products Seeds for consumption Spices, dried herbs and teas DALY for each pathogen Pathogens Cases Total DALY Cases Total DALY Cases Total DALY 0.143 E. coli 30 4.29 0 4 0.572 0.049 Salmonella 2 183 106.967 376 18.424 1 582 77.518 1.45 Clostridium botulinum 5 7.25 0 1 1.45 0.0023 Bacillus cereus 0 0 421 0.9683 0.0032 Clostridium perfringens 0 0 63 0.2016 0.0026 Staphylococcus aureus 0 0 0 TOTAL 2 218.0 118.5 376.0 18.4 2 071.0 80.7 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 258 TABLE A5.2 Total DALY for each of the categories of LMF taking into consideration all the microorganisms under consideration SUMMARY Average DALY Total cases Total DALY Cereals and grains 0.0361 1 668 60.3 Confections and snacks 0.0496 1 463 72.5 Dried Fruit and Vegetables 0.0490 669 32.8 Dried protein products 0.0090 15 211 136.4 Nuts and Nut Products 0.0534 2 218 118.5 Seeds 0.0490 376 18.4 Spices, dried herbs and tea 0.0390 2 071 80.7 References in Annex 5 Havelaar, A.H., Haagsma, J.A., Mangen, M.J., Kemmeren, J.M., Verhoef, L.P., Vijgen, S.M., Wilson, M., Friesema, I.H., Kortbeek, L.M., van Duynhoven, Y.T. & van Pelt, W. 2012. Disease burden of foodborne pathogens in the Netherlands, 2009. International Journal of Food Microbiology, 156: 231–238. 259 Annex 6 Consumption data The FAO/WHO Chronic Individual Food Consumption Database Summary Statistics (CIFOCOSS) is a preliminary concise global food consumption database, which will soon be published on FAO/WHO websites and contains summary daily intake statistics (i.e. 5th, 50th, 75th, 95th and 97.5th…) for different populations groups (i.e. toddlers, children, adolescents, adults, elderly and general population) based upon 34 food consumption surveys from at least two days of consumption conducted in 23 countries from the last ten years (Australia, Belgium, Brazil, Bulgaria, China, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Latvia, the Netherlands, Republic of Korea, Spain, Sweden, Thailand and the United Kingdom of Great Britain and Northern Ireland). This database provides summary statistics parameters of daily food consumed by population expressed at the lowest food classification level, i.e. food item level 3 (example of wheat flour classified in the broad food categories cereals and grains at level 1, annex 1). Considering the need for the ranking exercise, it was agreed to express the consumption data at the broad food category level 1 with at least the following statistics parameters (mean whole population, median whole population, standard deviation, the 95th percentile of consumers, the number of subjects and the percent of consumers). As the raw data at the individual level was not available internally within FAO/WHO due to the format of CIFOCOSS, it was agreed that the estimates of the 95th percentile of consumers be calculated using the same guidelines as those used by JECFA (FAO and WHO, 2009). The approach used for estimating high percentiles of exposure from all contribution food sources is based on the assumption that an individual might be a high level consumer of one food category only and would be an average consumer of all the remaining food groups. The method consists simply of adding the highest level of exposure from one food category (calculated for high consumers only at the P95) to the mean exposure values for the remaining categories (calculated for the whole population with consumers and non-consumers). Moreover, in order to provide the best description of the intake distributions for the seven categories, the standard deviation (SD) was estimated assuming a log-normal distribution. First, the error factor is calculated. For a log-normal RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 260 distribution, SD is defined as the ratio of the 95th percentile to the median. Then mathematical relationships between the mean, the error factor and the standard deviation of the underlying normal distribution (sigma) defined by the following equations are used: • error factor = P95/median • sigma = LOG (error factor)/1.645 • SD = mean * SQR(EXP(sigma ^ 2) - 1) It was noted that it was not possible to provide reliable estimates for the median and therefore, neither for the standard deviation for some low-moisture broad food categories (i.e dried fruits and vegetables and dried protein products) due to the low number of consumers reported in the surveys. The mean serving in grams per day for the average population as well as the amount consumed by those considered to be high consumers are based on the tables provided below. A6.1 Average serving Table A6.1 gives a description of different population groups considered for the description of the consumption from the low-moisture broad food category as the groups have been reported by data providers to WHO/FAO and as the groups have been used by the expert consultation group to report the description of the consumption from the low-moisture broad food category. TABLE A6.1 Food consumption surveys considered for the calculation of consumption data of LMF Population Age range Countries with food consumption surveys covering more than one day Toddlers From 12 up to and including 35 months of age Belgium, Bulgaria, China*, Finland, Germany, Italy, Japan*, the Netherlands, Republic of Korea* and Spain Children From 36 months up to and including 9 years of age Australia, Belgium, Bulgaria, Czech Republic, Denmark, Finland, France, Germany, Greece, Italy, Latvia, Netherlands, Spain and Sweden Adolescents From 10 up to and including 17 years of age Australia, Belgium, Cyprus, Czech Republic, Denmark, France, Germany, Italy, Latvia, Netherlands, Spain and Sweden Adults From 18 up to and including 64 years of age Belgium, Czech Republic, Denmark, Finland, France, Germany, Hungary, Ireland, Italy, Latvia, the Netherlands, Spain, Sweden and United Kingdom of Great Britain and Northern Ireland (cont.) ANNEX 6 261 Population Age range Countries with food consumption surveys covering more than one day The elderly From 65 years of age and older Belgium, Denmark, Finland, France, Germany, Hungary and Italy General population From 24 months up to over 65 years of age Australia, Belgium, Brazil, Bulgaria, China, Czech Republic, Denmark, Finland, France, Germany, Greece, Italy, Japan, Latvia, the Netherlands, Republic of Korea, Spain, Sweden and Thailand *Age range for those countries was up to 72 months. Table A6.2 summarizes the range estimates of daily consumption of low-moisture broad food categories at global level per population groups considered by the expert working group (in g/person). RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 262 TABLE A6.2 Daily consumption of LMF per population groups Toddlers (1–3 years)* Children (3–9 years) Adolescents (10–17 years) Adults (18–64 years) Elderly (>65 years) General population (all population groups, 2 ->65 years) $ Cereals and grains Number of subjects 4 432 8 405 9 870 29 807 4 056 184 417 % of consumers 90 95 93 93 95 93 Mean whole population (g/day) 123 147 196 193 182 185 Median whole population (g/day) 66 96 128 121 111 116 SD 166,7 92,8 130,5 140,1 112,4 217,8 High consumers Level (P95) (g/day) 353.1 249.4 345.8 353.1 284.0 537.5 High consumers Level (P95) – % of population (approximate) 4.5% 4.8% 4.65% 4.65% 4.75% 4.7% Confections and snacks Number of subjects 4 432 8 405 9 870 29 807 4 056 184 417 % of consumers 66 89 82 69 57 72 Mean whole population (g/day) 27.4 63 79 57 35 52.0 Median whole population(g/day) 16 41 34 32 12 30 SD 63.4 184.1 273.6 272.9 467.6 224.7 High consumers Level (P95) (g/day) 147 486 476 592 502 513 High consumers Level (P95) – % of population (approximate) 3.3 4.5 4.1 3.5 2.9 3.6 Dried fruits and vegetables Number of subjects 4 432 8 405 9 870 29 807 4 056 184 417 % of consumers 33 30 33 33 37 36 Mean whole population (g/day) 15.6 12.9 14.2 16.9 19.7 21.1 Median whole population(g/day) 0.0 0.0 0.0 0.0 0.0 0.0 SD - - - - - - High consumers Level (P95) (g/day) 171.8 221.6 190.3 294.3 283.8 295.5 High consumers Level (P95) – % of population (approximate) 1.65 1.5 1.65 1.65 1.85 1.8 (cont.) ANNEX 6 263 Toddlers (1–3 years)* Children (3–9 years) Adolescents (10–17 years) Adults (18–64 years) Elderly (>65 years) General population (all population groups, 2 ->65 years) $ Dried protein products Number of subjects 3 283 3 579 2 753 28 187 3 766 160 024 % of consumers 35 13 14 8 11 15 Mean whole population (g/day) 2.9 0.1 0.1 0.3 0.2 1.1 Median whole population (g/day) 0.0 0.0 0.0 0.0 0.0 0.0 SD - - - - - - High consumers Level (P95) (g/day) 20.6 2.9 5.2 29.9 26.7 40.0 High consumers Level (P95) – % of population (approximate) 1.75 0.65 0.7 0.4 0.55 0.75 Honey and preserves Number of subjects 4 432 8 405 9 870 29 807 4 056 184 417 % of consumers 52 70 66 73 77 66 Mean whole population (g/day) 8.2 15.4 20.4 17.6 16.5 15.5 Median whole population(g/day) 0.1 5.5 4.4 5.1 12.2 5.0 SD - 64.1 - - 32.7 - High consumers Level (P95) (g/day) 49.8 90.6 152.4 123.0 97.5 141.3 High consumers Level (P95) – % of population (approximate) 2.6 3.5 3.3 3.65 3.85 3.3 Nuts and nut products Number of subjects 3 778 8 405 9 870 29 807 4 056 183 763 % of consumers 19 10 11 11 14 14 Mean whole population (g/day) 1.3 1.4 2.2 2.8 1.7 2.1 Median whole population(g/day) 0.0 0.0 0.0 0.0 0.0 0.0 SD - - - - - - High consumers Level (P95) (g/day) 24.2 74.4 139.2 143.0 88.4 131.7 High consumers Level (P95) – % of population (approximate) 0.95 0.5 0.55 0.55 0.7 0.7 (cont.) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 264 Toddlers (1–3 years)* Children (3–9 years) Adolescents (10–17 years) Adults (18–64 years) Elderly (>65 years) General population (all population groups, 2 ->65 years) $ Seeds for consumption Number of subjects 4 361 8 405 9 567 29 807 4 056 18 1332 % of consumers 17 25 30 35 37 30 Mean whole population (g/day) 2.3 4.0 6.0 6.7 9.7 5.5 Median whole population (g/day) 0.0 0.0 0.0 0.0 0.0 0.0 SD - - - - - - High consumers Level (P95) (g/day) 79.4 85.0 161.2 151.6 188.0 179.0 High consumers Level (P95) – % of population (approximate) 0.85 1.25 1.5 1.75 1.85 1.5 Spices, dried herbs and tea Number of subjects 4 379 8 405 9 870 29 807 4 056 184 364 % of consumers 59 61 69 81 80 69 Mean whole population (g/day) 1.5 2.0 3.6 7.0 6.8 4.4 Median whole population (g/day) 0.02 0.1 0.1 0.7 2.4 0.1 SD - - - - 19.9 - High consumers Level (P95) (g/day) 7.6 20.1 42.0 45.9 28.9 49.1 High consumers Level (P95) – % of population (approximate) 2.95 3.05 3.45 4.05 4 3.45 High consumers Level (P95): Estimates based on the added highest P95 consumers food group + the mean consumption value for the remaining food group from whole population. *China, Japan and the Republic of Korea are included, with age up to 72 months. $: Consumption figures also includes intakes from Asian countries which were reported only at the general population group. (-) Could not be estimated due to the low number of consumers. (0.0) Means that there is <50% of consumers. ANNEX 6 265 A6.2 VULNERABLE CONSUMERS The proportion of vulnerable consumers was calculated, for each category, by considering the percent of total consumers that were consuming a given LMF category in the surveys against the percent of vulnerable consumers (toddlers and elderly) as shown in Table A6.3. (cont.) TABLE A6.3 Proportion of vulnerable consumers (toddlers and elderly)   Toddlers Children Adolescents Adults Elderly Proportion Vulnerable (1–3 years)* (3–9 years) (10–17 years) (18–64 years) (>65 years) (Toddlers + Elderly) Cereals and grains Number of subjects 4 432 8 405 9 870 29 807 4 056   % of consumers 90 95 93 93 95   Consumers 3 988.8 7 984.75 9 179.1 27 720.51 3 853.2   Proportion 7.60% 15.10% 17.40% 52.60% 7.30% 14.90% Confections and snacks  Number of subjects 4 432 8 405 9 870 29 807 4 056   % of consumers 66 89 82 69 57   Consumers 2 925.12 7 480.45 8 093.4 20 566.83 2 311.92   Proportion 7.10% 18.10% 19.60% 49.70% 5.60% 12.70% Dried fruits and vegetables Number of subjects 4 432 8 405 9 870 29 807 4 056   % of consumers 33 30 33 33 37   Consumers 1 462.56 2 521.5 3 257.1 9 836.31 1 500.72   Proportion 7.90% 13.60% 17.50% 52.90% 8.10% 16.00% Dried protein products  Number of subjects 3 283 3 579 2 753 28 187 3 766   % of consumers 35 13 14 8 11   Consumers 1 149.05 465.27 385.42 2 254.96 414.26   Proportion 24.60% 10.00% 8.30% 48.30% 8.90% 33.50% Nuts and nut products Number of subjects 3 778 8 405 9 870 29 807 4 056   % of consumers 19 10 11 11 14   Consumers 717.82 840.5 1 085.7 3 278.77 567.84   Proportion 11.10% 12.90% 16.70% 50.50% 8.70% 19.80% RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 266   Toddlers Children Adolescents Adults Elderly Proportion Vulnerable (1–3 years)* (3–9 years) (10–17 years) (18–64 years) (>65 years) (Toddlers + Elderly) Seeds for consumption             Number of subjects 4 361 8 405 9 567 29 807 4 056   % of consumers 17 25 30 35 37   Consumers 741.37 2 101.25 2 870.1 10 432.45 1 500.72   Proportion 4.20% 11.90% 16.30% 59.10% 8.50% 12.70% Spices, dried herbs and tea Number of subjects 4 379 8 405 9 870 29 807 4 056   % of consumers 59 61 69 81 80   Consumers 2 583.61 5 127.05 6 810.3 24 143.67 3 244.8   Proportion 6.20% 12.20% 16.30% 57.60% 7.70% 13.90% * Data of three countries (China, Japan and the Republic of Korea) are included with age up to 72 months. ANNEX 6 267 TA B LE A 6. 4 T he t yp es o f l ow -m oi st ur e fo od s in cl ud ed in e ac h m aj or fo od c at eg or y fo r th e pu rp os es o f c om pi lin g th e da ta o n co ns um pt io n Ce re al s an d gr ai ns Co nf ec ti on a nd sn ac ks D ri ed fr ui ts a nd ve ge ta bl es D ri ed p ro te in pr od uc ts N ut s an d nu t p ro du ct s Se ed s fo r co ns um pt io n Sp ic es , d ri ed h er bs an d te a # B an an a ca ke B ul le ts o r lo lli po p A pp le , d ri ed C ur ed (i nc lu di ng sa lt ed ) a nd d ri ed no n- he at -t re at ed pr oc es se d m ea t, po ul tr y, a nd g am e pr od uc ts in w ho le pi ec es o r cu ts A lm on ds A ni se s ee d A ng el ic a (l ea ve s) B ar le y C ak es , c oo ki es an d pi es (e .g . fr ui t- fil le d or cu st ar d ty pe s) A pr ic ot , d ri ed E gg p ro du ct s an d pr oc es se d eg gs B ra zi l n ut B or ag e se ed B as il B ar le y br an , pr oc es se d C ak es , c oo ki es an d pi es (e .g . fr ui t- fil le d or cu st ar d ty pe s) , ne s B an an a, d ri ed M ilk p ow de r an d cr ea m p ow de r (p la in ) C as he w n ut C ar aw ay s ee d B as il, d ry B ar le y br an , un pr oc es se d C ho co la te c ak e B ea ns , e xc ep t br oa d be an a nd so ya b ea n Sm ok ed , d ri ed , fe rm en te d, a nd / or s al te d fis h an d fis h pr od uc ts , in cl ud in g m ol lu sc s, cr us ta ce an s an d ec hi no de rm s C he st nu ts C or ia nd er s ee d B ay le av es , d ry B ar le y flo ur a nd gr it s C oc oa b ev er ag e (w at er -b as ed ) B la ck be rr ie s, d ri ed Sm ok ed , d ri ed , fe rm en te d, a nd / or s al te d fis h an d fis h pr od uc ts , in cl ud in g m ol lu sc s, cr us ta ce an s, a nd ec hi no de rm s, n es C oc on ut C um in s ee d C am om ile o r C ha m om ile (H er b te a) B re ad cr um bs C oc oa b ut te r B lu eb er ri es , d ri ed H az el nu ts Fe nn el s ee d C ar da m om (c on t. ) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 268 Ce re al s an d gr ai ns Co nf ec ti on a nd sn ac ks D ri ed fr ui ts a nd ve ge ta bl es D ri ed p ro te in pr od uc ts N ut s an d nu t p ro du ct s Se ed s fo r co ns um pt io n Sp ic es , d ri ed h er bs an d te a # B re ak fa st ce re al s, in cl ud in g ro lle d oa ts C oc oa m as s B ro ad b ea n M ac ad am ia n ut s G re en b ea n (g re en po ds a nd im m at ur e se ed s) C el er y le av es B uc kw he at C oc oa p ow de r C hi ck -p ea P ea nu t Li ns ee d C hi ve s, d ry B uc kw he at fl ou r G um C ra nb er ry , d ri ed P ea nu t oi l a nd b ut te r M el on s ee d C ila nt ro , l ea ve s, d ry B ul gu r w he at H on ey C ur ra nt s, d ri ed P ec an M us ta rd s ee d C ila nt ro /c or ia nd er le av es C ak e co rn O th er c oc oa pr od uc ts (i nc l. ch oc ol at e) , n es D at e, d ri ed P in e nu ts P ea s, S he lle d (s uc cu le nt s ee ds ) C in na m on b ar k (i nc l. ci nn am on , ch in es e ba rk ) C ak e m an io c P op co rn D at es , d ri ed o r dr ie d an d ca nd ie d P is ta ch io n ut s P er ill a se ed s C lo ve s, b ud s C an jiq ui nh a P ot at o cr is ps D ri ed fr ui t P ro ce ss ed n ut s, in cl ud in g co at ed n ut s an d nu t m ix tu re s (w it h e. g. d ri ed fr ui t) P op py s ee d D ill w ee d ra w C ar ro t ca ke Sn ac ks – p ot at o, ce re al , fl ou r or st ar ch b as ed (f ro m ro ot s an d tu be rs , p ul se s an d le gu m es ) D ri ed g ra pe Sw ee t pe an ut P um pk in s ee d D ri ed h er bs fo r he rb al t ea , n es C as sa va fl ou r Sn ac ks - p ot at o, ce re al , fl ou r or st ar ch b as ed (f ro m ro ot s an d tu be rs , p ul se s an d le gu m es ), ne s D ri ed t om at o Tr ee n ut s pr oc es se d, n es Se sa m e se ed E di bl e flo w er s, n es C el lo ph an e no od le s Sn ac ks , n es Fi g, d ri ed Tr ee n ut s, n es So ya b ea n (i m m at ur e se ed s) G al an ga l, rh iz om e (c on t. ) ANNEX 6 269 Ce re al s an d gr ai ns Co nf ec ti on a nd sn ac ks D ri ed fr ui ts a nd ve ge ta bl es D ri ed p ro te in pr od uc ts N ut s an d nu t p ro du ct s Se ed s fo r co ns um pt io n Sp ic es , d ri ed h er bs an d te a # C er ea l- ba se d co m po si te fo od Su ga r be et G oj i B er ry , D ri ed W al nu ts Su nfl ow er s ee d G in ge r, r hi zo m es C er ea l- ba se d co m po si te fo od , ne s Su ga r ca ne G re en b ea n (g re en p od s an d im m at ur e se ed s) G in se ng C er ea ls g ra in s, ne s Su ga r ca ne m ol as se H ar ic ot b ea n (d ry ) (N av y be an [d ry ]) G re en t ea C ho co la te c ak e Su ga r ca ne , n es K id ne y be an (d ry ) H er bs , n es C or n br ea d Su ga r pr od uc ts a nd co nf ec ti on ar ie s, ne s Le nt il H op s, d ry C or nm ea l c ak e Su ga r, n es Li m a be an (d ry ) (B ut te r be an , Si ev a be an ) Le m on v er be na (d ry le av es ) Fl ou rs , n es Sw ee t co rn , dr ie d Li m a be an ( yo un g po ds a nd /o r im m at ur e be an s) Le m on gr as s G in ge rb re ad Sw ee t P ot at o C ak e M an go , d ri ed Li qu or ic e, ro ot s H om in y/ m ug un zá Ye as t on ly M an go es , d ri ed M ac e In st an t no od le s M ix ed d ri ed fr ui ts , dr ie d M ar jo ra m , d ry Jo b’ s te ar s M us hr oo m s an d fu ng i M at é (d ry le av es ) (H er b te a) M ai ze M us hr oo m s pr es er ve d M at e be ve ra ge M ai ze fl ou r M us hr oo m s, d ri ed M in ts M ai ze m ea l O kr a M in ts , d ry (c on t. ) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 270 Ce re al s an d gr ai ns Co nf ec ti on a nd sn ac ks D ri ed fr ui ts a nd ve ge ta bl es D ri ed p ro te in pr od uc ts N ut s an d nu t p ro du ct s Se ed s fo r co ns um pt io n Sp ic es , d ri ed h er bs an d te a # M ill et P ap ay a, d ri ed N at iv e m in t M ill et fl ou r P ea r, d ri ed N ut m eg O at b ra n, un pr oc es se d P ea s P ar sl ey O at m ea l P ea s, S he lle d (s uc cu le nt s ee ds ) P ar sl ey , d ri ed O at s P ig eo n pe a P ep pe r (b la ck , w hi te ) O ra ng e ca ke P od de d pe a (y ou ng p od s) (M an ge to ut , Su ga r pe a) P im en to , f ru it O th er p ro ce ss ed pr od uc ts (e xc l. fo r in fa nt ), n es P ru ne s, d ri ed R oo ib os le av es d ry P op co rn P ul se s pr oc es se d, ne s R os em ar y P or ri dg e P ul se s, n es R os em ar y, d ry Q ui no a P ul se s, o ils ee d an d Tr ee n ut s- ba se d co m po si te fo od Sa ff ro n R ic e (e xc l. W ild ) R ai si ns , d ri ed Sa ge a nd re la te d sa lv ia s pe ci es R ic e (e xc l. W ild ), ne s R as pb er ri es , R ed , B la ck , d ri ed Sa ge , d ry R ic e br an , un pr oc es se d Se aw ee d, n es Sa lt R ic e ca ke So ya b ea n Ta rr ag on R ic e flo ur So ya b ea n (i m m at ur e se ed s) Te a an d m at e be ve ra ge s, n es (c on t. ) ANNEX 6 271 Ce re al s an d gr ai ns Co nf ec ti on a nd sn ac ks D ri ed fr ui ts a nd ve ge ta bl es D ri ed p ro te in pr od uc ts N ut s an d nu t p ro du ct s Se ed s fo r co ns um pt io n Sp ic es , d ri ed h er bs an d te a # R ic e pa st as a nd no od le s an d lik e pr od uc ts St ra w be rr y, d ri ed Te a in fu se d, be ve ra ge R ic e pa st as a nd no od le s an d lik e pr od uc ts , n es Su lt an as , d ri ed Te a, d ri ed le av es R ye To m at o, d ri ed Th ym e R ye b re ad V in e fr ui ts (c ur ra nt s, r ai si ns an d su lt an as ), dr ie d Th ym e, d ry R ye fl ou r Tu rm er ic , r oo t So rg hu m V an ill a be an s So y Fl ou r V ie tn am es e m in t Sw ee t co rn , dr ie d Sw ee t P ot at o C ak e Ta pi oc a ca ke Ta pi oc a flo ur Tr it ic al e W he at W he at b ra n, pr oc es se d (c on t. ) RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 272 Ce re al s an d gr ai ns Co nf ec ti on a nd sn ac ks D ri ed fr ui ts a nd ve ge ta bl es D ri ed p ro te in pr od uc ts N ut s an d nu t p ro du ct s Se ed s fo r co ns um pt io n Sp ic es , d ri ed h er bs an d te a # W he at fl ou r W he at g er m W he at p as ta s an d no od le s an d lik e pr od uc ts W he at p as ta s an d no od le s an d lik e, n es pr od uc ts W he at w hi te br ea d W he at w ho le m ea l b re ad W ild r ic e Ya m c ak e # A d ilu ti on f ac to r of 2 0 w as a pp lie d to b ev er ag e re po rt ed a s co ns um ed in o rd er t o ob ta in t he c on su m pt io n of h er bs o r te a ex pr es se d as d ry m at te r (i .e t ea in fu se d) . N es =N ot s pe ci fie d el se w he re . ANNEX 6 273 A6.3 REFERENCES IN ANNEX 6 FAO & WHO. 2009. Principles and methods for the risk assessment of chemicals in food. Environmental Health Criteria (EHC) 240. Geneva, World Health Organization. 274 Annex 7 Elicitation survey and results A7.1 OBJECTIVES The purpose of this survey is to elicit information on three parameters relevant to the ranking of LMF. Questions 1 and 2 below are relevant to the definition of the criterion on production. The production criterion has been characterized by three variables: a) the prevalence of pathogens in the specific categories of LMF, b) the proportion of foods in a category subject to a kill step, and c) the proportion of foods in the categories to which ingredients are added after the kill step. Inputs for b and c are dependent on expert judgement, and questions 1 and 2 below relate to these. Question 3 is relevant to the definition of the criterion on consumption and aims to capture the impact of mishandling by the food handler or consumer after the retail stage. Questions and guidance to the experts in the elicitation process i. Proportion (in terms of amount of product produced51) of low-moisture food products in a given category subject to a kill step (see definition below) prior to retail and distribution For the purposes of characterizing this parameter, a kill step is defined as follows: a process applied to a food or food ingredient with the aim of minimizing public health hazards from pathogenic microorganisms. The process step would likely not inactivate all microorganisms present, but it should reduce the number of harmful ones to a level at which they do not constitute a significant health hazard. Although not originally intended as a kill step, processes such as roasting or extrusion cooking of LMF may also contribute to reducing numbers of harmful microorganisms which might be present. Regardless of the origin of the process step, all the processes which are used as a kill step must be validated to ensure that they are delivering the intended effect. In the absence of validation, such processes should not be considered as a specific kill step. Examples of a kill step could include validated processes of the following: applying heat or other means of inactivation when the food or ingredient has a high water activity (e.g. cooking meat, pasteurizing liquids, etc. before drying); increasing the water activity and 51 Produced for human consumption. 275ANNEX 7 applying heat (steam pasteurization of nuts and spices, etc. sometimes combined with roasting); applying dry heat (to lower water activity foods or food ingredients) (validated roasting, baking and toasting, etc.); and applying other inactivation methods such as UV, infrared, pulsed light, chemicals and irradiation, etc. ii. Proportion (in terms of amount of product produced51) of low-moisture food products in a given category with an increased risk of contamination post kill step This is defined as those low-moisture food products to which there is addition or combining of ingredients after the kill step which would present an opportunity for contamination of the product. iii. Proportion (of the product which is sold for human consumption52) of low-moisture food products in a given category with an increased risk as a result of mishandling/poor practices at any time between final retail and consumption For the purposes of characterizing this parameter, please note the following: • The increased risk is only related to an increase in the intrinsic microbial population. • The potential for cross-contamination or contamination from extrinsic sources is not considered. Important notes: • Values are requested for the most likely (median) proportion of food in a given category that may be subject to a kill step, post kill step contamination or poor practices during food preparation that would lead to an increased risk. • The proportion can be expressed as percent, i.e. a number between 1 and 100. • The minimum proportion and the maximum proportion of food within each of these categories should also be provided. • The three values provided do not have to add up to 100. • Values should be provided at the category level taking into account the range of products within each category. • Data on global production of each of the categories is limited and only available at the raw commodity level, so this could not be provided. However, the values of the different categories and where feasible subcategories within those categories are provided in a separate spreadsheet for use as appropriate. 52 For ease of completion, this can also be considered in terms of the amount of product produced for human consumption. RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 276 FIGURE A7.1 Elicitation survey spreadsheet Ca te go ry 1. P ro po rt io n (0 –1 0 0 % ) o f lo w -m oi st ur e fo od p ro du ct s in a gi ve n ca te go ry s ub je ct to k ill s te p (s ee d efi ni ti on b el ow ) p ri or to r et ai l an d di st ri bu ti on 2. P ro po rt io n (0 –1 0 0 % ) o f lo w -m oi st ur e fo od p ro du ct s in a gi ve n ca te go ry w it h an in cr ea se d ri sk of c on ta m in at io n po st k ill s te p 3. P ro po rt io n (0 –1 0 0 % ) o f lo w -m oi st ur e fo od p ro du ct s in a gi ve n ca te go ry w it h an in cr ea se d ri sk a s a re su lt o f m is ha nd lin g /p oo r pr ac ti ce s at a ny ti m e be tw ee n fi na l re ta il an d co ns um pt io n M os t lik el y M ed iu m M ax im im M os t lik el y M ed iu m M ax im im M os t lik el y M ed iu m M ax im im C er ea ls a n d g ra in C on fe ct io ns a n d sn ac ks D ri ed fr ui ts a n d ve g et ab le s D ri ed p ro te in p ro d uc ts N ut s an d nu t p ro d uc ts S ee ds fo r co ns um pt io n S p ic es , d ri ed h er bs a n d te as Ce re al s an d gr ai n. T hi s ca te go ry in cl ud es w he at , b ar le y, m ai ze /c or n, o at s, ry e, m ill et , s or gh um , b uc kw he at a nd ri ce , a s w el l a s th ei r m ill ed p ro du ct s (e .g . fl ou rs , s ta rc he s) a nd fu rt he r p ro ce ss ed fo od s ba se d on c er ea ls a nd gr ai ns (e .g . d ry b ak in g m ix es , b re ak fa st c er ea ls , p as ta , n oo dl es ). Co nf ec ti on s an d sn ac ks . T hi s ca te go ry in cl ud es s ug ar a nd s ug ar -b as ed s w ee ts s uc h as f on da nt s/ cr ea m s, m ar sh m al lo w s, c ar am el s/ to ff ee s, c he w in g gu n an d ch oc ol at e an d ot he r co co a- ba se d pr od uc ts ( e. g. c oc oa a nd ch oc ol at e po w de rs a nd m ix es ), s av ou ry a nd re ad y- to -e at lo w -m oi st ur e fo od s su ch a s ch ip s an d dr ie d bi sc ui ts /c ra ck er s. Y ea st is a ls o in cl ud ed a s a fla vo ur in g or a dd it iv e to lo w -m oi st ur e fo od s. D ri ed fr ui ts a nd v eg et ab le s. T hi s ca te go ry in cl ud ed d ri ed a nd d eh yd ra te d fr ui ts a nd v eg et ab le s, a s w el l a s dr ie d se aw ee d an d m us hr oo m s. E xa m pl es o f dr ie d fr ui ts in cl ud ed r ai si ns , p ru ne s, d at es , d ri ed m an go s, d ri ed ap ri co ts , d es ic ca te d co co nu t a nd fr ui t p ow de rs . E xa m pl es o f d ri ed v eg et ab le s in cl ud ed s un -d ri ed v eg et ab le s (e .g . t om at oe s, o kr a) , v eg et ab le p ow de rs a nd m ix es (e .g . d ry s ou p m ix es ), d eh yd ra te d ve ge ta bl es (e .g . p ot at o fla ke s, c ar ro t sl ic es ), a nd v eg et ab le fl ou rs ( e. g. p ot at o st ar ch , y am fl ou r) . W e al so in cl ud ed d ri ed le gu m es a nd le gu m e flo ur s in t he d ri ed v eg et ab le c at eg or y. F or t he p ur po se o f s um m ar iz in g pr ev al en ce a nd in te rv en ti on in fo rm at io n, d at a w er e co lla ps ed a cr os s fo ur c at eg or ie s: 1) d ri ed /d eh yd ra te d fr ui ts , 2 ) d ri ed /d eh yd ra te d ve ge ta bl es , 3 ) d ri ed /d eh yd ra te d m us hr oo m s, a nd 4 ) d ri ed s ea w ee d. D ri ed p ro te in p ro du ct s. T hi s ca te go ry in cl ud es 1) d ri ed d ai ry p ro du ct s (e .g . m ilk , w he y an d m ilk -p ro du ct p ow de rs ), 2 ) d ri ed e gg p ro du ct s (e .g . e gg p ow de rs ), 3 ) d ri ed fi sh /s ea fo od p ro du ct s (e .g . d ri ed fi sh , fi sh m ea l/ flo ur ), 4 ) d ri ed m ea t pr od uc ts o th er t ha n sa us ag es , s al am is a nd je rk y’ s (e .g . g el at in , m ea t po w de rs ), a nd 5 ) d ri ed p ro te in s of p la nt o ri gi n (e .g . s oy p ow de r) . N ut s an d nu t p ro du ct s. T hi s ca te go ry in cl ud es e di bl e nu ts a nd n ut s pr od uc ts , w hi ch a re d efi ne d as t he d ri ed , h ar d- sh el le d fr ui ts , k er na ls o r se ed s of t re es , s hr ub s or o th er p la nt s (F A O , 1 99 5) . I t in cl ud ed t w o ca te go ri es : 1 ) tr ee n ut s (e .g . a lm on ds , B ra zi l n ut s, c as he w s, p ec an s, p is ta ch io s, p in e nu ts , w al nu ts ), a nd 2 ) g ro un d nu ts o r pe an ut s. Se ed s fo r co ns um pt io n. T hi s ca te go ry in cl ud es d ri ed s un flo w er s ee ds , p um pk in s ee ds , m el on s ee ds , p op py s ee ds , fl ax s ee ds , s es am e se ed s an d se sa m e pr od uc ts , a nd o th er e di bl e se ed s. S pe ci fic s ee p ro du ct s ar e al so in cl ud ed h er e – ta hi ni (s es am e pa st e) , w hi ch is p ro du ce d fr om ro as te d an d m ill ed s es am e se ed s, a nd h al va /h el va , w hi ch is a c on fe ct io ne ry p ro du ce d fr om m ix in g ta hi ni , s ug ar , g lu co se s yr up a nd o th er in gr ed ie nt s. Sp ic es , d ri ed h er bs a nd t ea s. S pi ce s ar e dr ie d pa rt s of f ru it s, s ee ds , b ar k, r oo ts , l ea ve s or fl ow er s of p la nt s an d he rb s w hi ch a re o ft en g ro un d, c ru sh ed o r ot he rw is e pr oc es se d an d us ed f or s ea so ni ng , fl av ou ri ng a nd /o r pr es er vi ng fo od s. 277ANNEX 7 A7.2 RESULTS OF THE ELICITATION PROCESS The most likely values provided by each of the experts for each of the three questions are provided below. The median values of these were used in the ranking exercise. i. Proportion (in terms of amount of product produced53) of low-moisture food products in a given category subject to a kill step (see definition below) prior to retail and distribution TABLE A7.1 Expert estimates for criterion 4.2 proportion without a kill step (most likely values) Food Category Expert 1 Expert 2 Expert 3 Expert 4 Expert 5 Lower Estimate Upper Estimate Median Average SD Confections and snacks 5 35 20 20 3 3 35 20 16.6 13 Dried fruits and vegetables 90 70 70 80 50 50 90 70 72 14.8 Dried protein roducts 15 40 10 10 8 8 40 10 16.6 13.3 Nuts and nut products 10 70 50 60 30 10 70 50 44 24.1 Seeds for consumption 50 75 70 75 90 50 90 75 72 14.4 Spices, dried herbs and teas 75 80 75 75 85 75 85 75 78 4.5 ii. Proportion (in terms of amount of product produced53) of low-moisture food products in a given category with an increased risk of contamination post kill step 53 Produced for human consumption RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 278 TABLE A7.2 Expert estimates for criterion 4.1 increased risk of contamination (most likely values) Food Category Expert 1 Expert 2 Expert 3 Expert 4 Expert 5 Lower Estimate Upper Estimate Median Average SD Confections and snacks 40 15 10 40 70 10 70 40 35 24 Dried fruits and vegetables 1 20 10 10 1.5 1 20 10 8.5 7.8 Dried protein products 10 25 20 10 73.6 10 73.6 20 27.72 26.5 Nuts and nut products 3 30 25 10 10.5 3 30 10.5 15.7 11.3 Seeds for consumption 1 20 25 10 9 1 25 10 13 9.5 Spices, dried herbs and teas 10 30 15 5 1.5 1.5 30 10 12.3 11.1 iii. Proportion (of the product which is sold for human consumption54) of low-moisture food products in a given category with an increased risk as a result of mishandling/poor practices at any time between final retail and consumption TABLE A7.3 Expert estimates for criterion 3.3 consumer mishandling (most likely values) Food Category Expert 1 Expert 2 Expert 3 Expert 4 Expert 5 Lower Estimate Upper Estimate Median Average SD Cereals and Grain 10 30 20 5 30 5 30 20 19 11.4 Confections and snacks 1 8 10 5 2 1 10 5 5.2 3.8 Dried fruits and vegetables 1 15 15 5 5 1 15 5 8.2 6.4 Dried protein products 70 25 20 5 70 5 70 25 38 30.1 Nuts and nut products 0 15 10 5 1 0 15 5 6.2 6.3 Seeds for consumption 1 10 10 5 1 1 10 5 5.4 4.5 Spices, dried herbs and teas 60 15 20 5 10 5 60 15 22 22 54 For ease of completion, this can also be considered in terms of the amount of product produced for human consumption. 279 Calculation of prevalence There was a strong desire during the consultation process to base the inputs to the ranking on available evidence where possible. In this context, there was much discussion on how the data on prevalence collected during the knowledge synthesis could be used. There were some concerns about the representativeness of the data and in some cases the limited number of studies that had been undertaken. As a result, it was decided to consider the data for a selected number of pathogens only where there were the greatest number of studies so there could be more confidence in the data. Details of the organisms considered, the reported prevalence data and the corrected prevalence data are provided in Table A8.1. The correction factors and their basis applied to toxin producers within each of the categories are presented in Table A8.2. TABLE A8.1 Overview of prevalence data from knowledge synthesis and after application of correction factors to account for levels above a certain threshold of toxin producers before a risk of illness exists   Expert Judgement Prevalence from knowledge synthesis Prevalence of pathogen contamination above specified thresholds (Prevalence [%] from KS * correction factors in the table below [Table A8.2]) Cereals and grains       B. cereus   38.5 3.47 C. Perfringens   4.5 0.05 S. aureus   4.0 0.21 Salmonella spp.   0.7 0.70 Overall–middle 5.5 9.5 3.94 min   3.47 max   4.42 Confections and snacks     B. cereus   19 1.90 C. Perfringens   0 0.00 (cont.) Annex 8 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 280   Expert Judgement Prevalence from knowledge synthesis Prevalence of pathogen contamination above specified thresholds (Prevalence [%] from KS * correction factors in the table below [Table A8.2]) S. aureus   0.5 0.03 Salmonella spp.   0.6 0.60 Overall–middle 0.2 4.02 2.21 min   1.90 max   2.53 Dried fruits and vegetables     B. cereus   76.3 3.82 C. Perfringens   0 0.00 S. aureus   1.7 0.05 Salmonella spp.   2.0 2.00 Overall–middle 4.8 20.0 4.84 min   3.82 max   5.86 Dried protein products     B. cereus   31.5 2.52 Salmonella spp.   0.03 0.03 Overall–middle 0.1 0.6 2.54 min   2.52 max   2.55 Nuts and nut products     B. cereus   7.3 0.37 C. Perfringens   0 0.00 S. aureus   0 0.00 Salmonella spp.   0.6 0.60 Overall–middle 1.2 1.6 0.78 min   0.60 max   0.97 (cont.) 281ANNEX 8   Expert Judgement Prevalence from knowledge synthesis Prevalence of pathogen contamination above specified thresholds (Prevalence [%] from KS * correction factors in the table below [Table A8.2]) Seeds for consumption All data relates to sesame seed and sesame seed products.   B. cereus   6.7 0.34 C. Perfringens   0 0.00 S. aureus   0 0.00 Salmonella spp.   1.9 1.90 Overall–middle 2 1.7 2.07 min   1.90 max   2.24 Spices, dried herbs and tea     B. cereus   24.5 9.56 C. Perfringens   11.4 0.11 S. aureus   4.9 1.12 Salmonella spp.   3 3.00 Overall–middle 7 8.76 11.67 min   9.56 max   13.79 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 282 TABLE A8.2 Overview of correction factors applied to toxin producers in each of the categories to account for the need to reach a threshold before the possibility to cause illness was considered exists * 3 log CFU/g was considered by the experts, and the literature on this topic to be a conservative cut-off for contamination with toxin producing bacteria above a safe threshold Toxin producers correction factors Proportion of positive samples in prevalence surveys that are likely to exceed a 3 log CFU/g threshold*. Prevalence in the tables above have been adjusted by these values in right most column.   B. cereus1 S. aureus2 C. perfringens3 Cereals and grains 9.0% 5.3% 1.0% Confections and snacks 10.0% 5.8% 1.0% Dried fruits and veg 5.0% 2.9% 1.0% Dried protein 8.0% 4.7% 1.0% Nuts 5.0% 2.9% 1.0% Seed 5.0% 2.9% 1.0% Spices 39.0% 22.8% 1.0% 1 B. cereus literature was used to support variable correction factors for different categories. Nuts and seeds lacked direct evidence, and so the correction for dried fruits and vegetables was used as the most appropriate category. 2 S. aureus literature only supported a correction factor for spices and herbs. Thus, the relative corrections for B. cereus (other categories compared to spices) were used to estimate variable corrections for S. aureus as the experts agreed that this was the most logical behaviour for S. aureus. 3 C. perfringens literature indicated that these toxin levels were rarely detected above the threshold, and this was consistent across several food categories, so the experts agreed that a single, low correction was to be used across all categories of C. perfringens. CHAPTER 1 - BACKGROUND 283 FAO/WHO Microbiological Risk Assessment Series 1 Risk assessments of Salmonella in eggs and broiler chickens: Interpretative Summary, 2002 2 Risk assessments of Salmonella in eggs and broiler chickens, 2002 3 Hazard characterization for pathogens in food and water: Guidelines, 2003 4 Risk assessment of Listeria monocytogenes in ready-to-eat foods: Interpretative Summary, 2004 5 Risk assessment of Listeria monocytogenes in ready-to-eat foods: Technical Report, 2004 6 Enterobacter sakazakii and microorganisms in powdered infant formula: Meeting Report, 2004 7 Exposure assessment of microbiological hazards in food: Guidelines, 2008 8 Risk assessment of Vibrio vulnificus in raw oysters: Interpretative Summary and Technical Report, 2005 9 Risk assessment of choleragenic Vibrio cholerae 01 and 0139 in warm-water shrimp in international trade: Interpretative Summary and Technical Report, 2005 10 Enterobacter sakazakii and Salmonella in powdered infant formula: Meeting Report, 2006 11 Risk assessment of Campylobacter spp. in broiler chickens: Interpretative Summary, 2008 12 Risk assessment of Campylobacter spp. in broiler chickens: Technical Report, 2008 13 Viruses in food: Scientific Advice to Support Risk Management Activities: Meeting Report, 2008 14 Microbiological hazards in fresh leafy vegetables and herbs: Meeting Report, 2008 15 Enterobacter sakazakii (Cronobacter spp.) in powdered follow-up formula: Meeting Report, 2008 16 Risk assessment of Vibrio parahaemolyticus in seafood: Interpretative Summary and Technical Report, 2011 17 Risk characterization of microbiological hazards in food: Guidelines, 2009. 18 Enterohaemorrhagic Escherichia coli in raw beef and beef products: approaches for the provision of scientific advice: Meeting Report, 2010 19 Salmonella and Campylobacter in chicken meat: Meeting Report, 2009 284 RANKING OF LOW-MOISTURE FOODS IN SUPPORT OF MICROBIOLOGICAL RISK MANAGEMENT: MEETING REPORT AND SYSTEMATIC REVIEW 20 Risk assessment tools for Vibrio parahaemolyticus and Vibrio vulnificus associated with seafood: Meeting Report, 2020 21 Salmonella spp. in bivalve molluscs: Risk Assessment and Meeting Report, In press 22 Selection and application of methods for the detection and enumeration of human pathogenic halophilic Vibrio spp. in seafood: Guidance, 2016 23 Multicriteria-based ranking for risk management of food-borne parasites, 2014 24 Statistical aspects of microbiological criteria related to foods: A risk managers guide, 2016 25 Risk-based examples and approach for control of Trichinella spp. and Taenia saginata in meat: Meeting Report, 2020 26 Ranking of low-moisture foods in support of microbiological risk management: Meeting Report and Systematic Review, 2022 27 Microbiological hazards in spices and dried aromatic herbs: Meeting Report, 2022 28 Microbial safety of lipid based ready-to-use foods for management of moderate acute malnutrition and severe acute malnutrition: First meeting report, 2016 29 Microbial safety of lipid based ready-to-use foods for management of moderate acute malnutrition and severe acute malnutrition: Second meeting report, 2021 30 Interventions for the control of non-typhoidal Salmonella spp. in Beef and Pork: Meeting Report and Systematic Review, 2016 31 Shiga toxin-producing Escherichia coli (STEC) and food: attribution, characterization, and monitoring, 2018 32 Attributing illness caused by Shiga toxin-producing Escherichia coli (STEC) to specific foods, 2019 33 Safety and quality of water used in food production and processing, 2019 34 Foodborne antimicrobial resistance: Role of the environment, crops and biocides, 2019. 35 Advance in science and risk assessment tools for Vibrio parahaemolyticus and V. vulnificus associated with seafood: Meeting report, 2021. 36 Microbiological risk assessment guidance for food: Guidance, 2021 37 Safety and quality of water used with fresh fruits and vegetables, 2021 285 286 26 Low-moisture foods (LMF) are foods that are naturally low in moisture or are produced from higher moisture foods through drying or dehydration processes. These foods typically have a long shelf life and have been perceived for many years to not represent microbiological food safety risk hazards. However, in recent years, a number of outbreaks of foodborne illnesses linked to LMF has illustrated that despite the fact that microorganisms cannot grow in these products, bacteria do have the possibility to persist for long periods of time in these matrices. Responding to a request from the Codex Committee on Food Hygiene (CCFH), the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) implemented a series of activities aimed at collating and analysing the available information on microbiological hazards related to LMF and ranking the foods of greatest concern from a microbiological food safety perspective. Seven categories of LMF which were ultimately included in the ranking process, and the output of the risk ranking, in descending order was as follows: cereals and grains; dried protein products; spices and dried herbs; nuts and nut products; confections and snacks; dried fruits and vegetables; and seeds for consumption. ISSN 1726-5274 Ranking of low-moisture foods in support of microbiological risk management MICROBIOLOGICAL RISK ASSESSMENT SERIES 26 MEETING REPORT AND SYSTEMATIC REVIEW Attributing illness caused by Shiga toxin-producing Escherichia coli (ST C) to specific foods MICROBIOLOGICAL RISK ASSESSMENT SERIES 32 REPORT R a n k in g o f lo w -m o is tu re fo o d s in s u p p o rt o f m ic ro b io lo g ic a l ris k m a n a g e m e n t: M E E T IN G R E P O R T A N D S Y S T E M A T IC R E V IE W F A O /W H O Food Systems and Food Safety - Economic and Social Development jemra@fao.org http://www.fao.org/food-safety Food and Agriculture Organization of the United Nations Viale delle Terme di Caracalla 00153 Rome, Italy Department of Nutrition and Food Safety jemra@who.int https://www.who.int/health-topics/food-safety/ World Health Organization 20 Avenue Appia 1211 Geneva 27, Switzerland CC0763EN/1/07.22 ISBN 978-92-5-136559-5 ISSN 1726-5274 9 7 8 9 2 5 1 3 6 5 5 9 5