Influenza-associated mortality in temperate and subtropical Chinese cities, 2003–2008

Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958 Research 279 Influenza-associated mortality in temperate and subtropical Chinese cities, 2003–2008 Luzhao Feng,a David K Shay,b Yong Jiang,c Hong Zhou,b Xin Chen,a Yingdong Zheng,d Lili Jiang,e Qingjun Zhang,f Hong Lin,g Shaojie Wang,h Yanyan Ying,i Yanjun Xu,j Nanda Wang,k Zijian Feng,a Cecile Viboud,l Weizhong Yanga & Hongjie Yua Introduction Influenza is one of the most prevalent vaccine-preventable diseases. Every year it causes an estimated 3 million cases of illness and from 250 000 to 500 000 deaths throughout the world.1 Influenza poses a particular risk of severe or fatal out- comes in the elderly, the very young and those with underlying chronic medical conditions.2 In temperate regions in both the northern3–13 and southern hemispheres,14–16 epidemics of seasonal influenza in winter often lead to dramatic increases in hospitalizations and mortality. Although little information is available on the burden posed by influenza in tropical and subtropical regions,17,18 the disease is thought to be responsible for substantial morbidity and mortality in the subtropical Hong Kong Special Administrative Region (SAR), and in tropical Singapore and Thailand.19–24 Only a few estimates of the burden posed by influenza-associated mortality in low- and middle-income countries have been published.14,16 As few cases of influenza undergo laboratory confirma- tion, deaths caused by influenza may go unrecognized and be attributed to co-morbidities or to secondary complications of the infection.25,26 For several decades, the mortality attributable to influenza has therefore been estimated using statistical mod- els and the elevations in mortality (i.e. the “excess” mortalities) recorded during seasonal epidemics of influenza.3–15,18–23 Such estimates can be useful in identifying high-risk groups and in guiding vaccination policy. China is a lower middle-income country whose popula- tion of 1.3 billion people is the largest in the world. The general perception that seasonal influenza does not cause substantial mortality in China may contribute to the underutilization of influenza vaccines in the country.27 In this study, we used the results of the city-wide registration of vital statistics and weekly viral surveillance to estimate the influenza-associated mortality that occurred in eight Chinese cities between 2003 and 2008. Methods Mortality data and population denominators As China has no national system for the registration of vital statistics, we focused on eight cities (Appendix A, available at: http://www.chinacdc.cn/xiazai/Feng-BullWorldHealthOrgan- 2012-AppendixA.pdf) with high-quality, population-based systems for mortality registration and low rates of underre- porting and misclassification in the study period (2003–2008). Three of the cities (Dalian, Qingdao and Zhaoyuan) lie in the temperate north of China and have a combined population Objective To estimate influenza-associated mortality in urban China. Methods Influenza-associated excess mortality for the period 2003–2008 was estimated in three cities in temperate northern China and five cities in the subtropical south of the country. The estimates were derived from models based on negative binomial regressions, vital statistics and the results of weekly influenza virus surveillance. Findings Annual influenza-associated excess mortality, for all causes, was 18.0 (range: 10.9–32.7) deaths per 100 000 population in the northern cities and 11.3 (range: 7.3–17.8) deaths per 100 000 in the southern cities. Excess mortality for respiratory and circulatory disease was 12.4 (range: 7.4–22.2) and 8.8 (range: 5.5–13.6) deaths per 100 000 people in the northern and southern cities, respectively. Most (86%) deaths occurred among people aged ≥ 65 years. Influenza-associated excess mortality was higher in B-virus-dominant seasons than in seasons when A(H3N2) or A(H1N1) predominated, and more than half of all influenza-associated mortality was associated with influenza B virus. Conclusion Between 2003 and 2008, seasonal influenza, particularly that caused by the influenza B virus, was associated with substantial mortality in three cities in the temperate north of China and five cities in the subtropical south of the country. a Chinese Centre for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, China. b National Centre for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, United States of America (USA). c National Centre for Chronic and Noncommunicable Disease Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China. d School of Public Health, Peking University, Beijing, China. e Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China. f Hubei Provincial Centre for Disease Control and Prevention, Wuhan, China. g Dalian Centre for Disease Control and Prevention, Dalian, China. h Qingdao Centre for Disease Control and Prevention, Qingdao, China. i Ningbo Centre for Disease Control and Prevention, Ningbo, China. j Guangdong Provincial Centre for Disease Control and Prevention, Guangzhou, China. k Zhaoyuan Centre for Disease Control and Prevention, Yantai, China. l Fogarty International Center, National Institutes of Health, Bethesda, USA. Correspondence to Hongjie Yu (e-mail: yuhj@chinacdc.cn). (Submitted: 2 October 2011 – Revised version received: 26 January 2012 – Accepted: 30 January 2012 ) Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958280 Research Influenza-associated mortality in China Luzhao Feng et al. of about 10 million. The other five cities (Shanghai, Wuhan, Yichang, Ningbo and Guangzhou) are in the subtropical south and have a combined population of about 21 million. Underlying cause- of-death data were manually coded and verified by locally trained coders using the 10th revision of the International Classification of Diseases (ICD-10).28 Coding practices were based on a stan- dardized protocol, and quality control and assurance were conducted routinely by staff from the Centre for Disease Control (CDC) in each location. As the data were not adjusted for underreport- ing, the estimated mortality rates that are reported below represent minimum values.29 As in previous studies,4,19–22 we obtained separate data for deaths from all causes and for deaths attributed to pneumonia and influenza (ICD-10 codes J10–J18), respiratory and circula- tory disease (codes J00–J99 or I00– I99), ischaemic heart disease (codes I20–I25) and chronic obstructive pulmonary disease (codes J40–J47). Mortality was stratified by year, week of death occur- rence and two age groups (0–64 years and ≥ 65 years). Influenza virological surveillance National surveillance of influenza-like illness (ILI) was launched in China in 2000. During the period investigated in the present study, sentinel hospitals reported the numbers of total outpatient visits and the numbers of visits by outpa- tients with ILI, either weekly throughout the year (in the 99 sentinel hospitals in the 15 subtropical southern provinces) or once a week in the cooler months of October to March (in the 94 sentinel hospitals in the 15 temperate northern provinces). These numbers were re- corded on a centralized online system maintained by the Chinese Centre for Disease Control and Prevention in Bei- jing. In each sentinel hospital, on each day of the weeks in which surveillance data were recorded, respiratory speci- mens were collected from the first one or two ILI cases. This produced 10–15 such specimens per hospital per surveillance week. The specimens were sent to one of the 62 province- or prefecture-level CDCs and there they were tested for influenza virus using the protocols and kits released by the Chinese National Influenza Centre (a World Health Or- ganization Collaborating Centre for Reference and Research on Influenza). As only sparse virological surveillance data were available for the cities we were investigating, the surveillance data for the temperate northern provinces and subtropical southern provinces (Ap- pendix A) were aggregated to represent the influenza circulation patterns in the northern and southern study cities, re- spectively. An influenza type or subtype (A/H3N2, A/H1N1 or B) was considered dominant during an influenza season when it accounted for at least 50% of the respiratory specimens that were typed. Influenza-associated excess mortality Our main estimates are based on nega- tive binomial regression models applied to the mortality and virological surveil- lance data for the eight study cities.22 As a sensitivity analysis, we also ap- plied Serfling regression models to the mortality data for the three northern cities, each of which showed an obvious peak in influenza activity during each winter in the study period (Fig. 1). A brief description of the methodological approach is presented below but more details can be found in Appendix A. We applied negative binomial regression models, separately for each disease outcome, the two age groups and the northern and southern cities, using weekly mortality counts as the outcome and the weekly proportions of respiratory specimens testing posi- tive for influenza A(H1N1), A(H3N2) or B as the explanatory variables. The models included terms for seasonality, time trends and weekly population-size offsets, and they used an identity link. Fig. 1. Deaths attributed to respiratory and circulatory disease, all-cause deaths and specimen positivity to influenza viruses, China, 2003–2008 All-cause deaths Respiratory specimens found positive for influenza virus Deaths attributed to respiratory and circulatory disease W ee kl y m or ta lit y ( de at hs p er 1 00 0 00 ) 20 15 10 5 0 20 15 10 5 0 % o f t es te d sp ec im en s 3.0 2.5 2.0 1.5 1.0 0.5 0.0 1.0 0.8 0.6 0.4 0.2 00 Date Date Jan 2003 Jul 2003 Jan 2004 Jul 2004 Jan 2005 Jul 2005 Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008 Jan 2003 Jul 2003 Jan 2004 Jul 2004 Jan 2005 Jul 2005 Jan 2006 Jul 2006 Jan 2007 Jul 2007 Jan 2008 Jul 2008 Northern cities Southern cities Note: The upper and lower panels show the results for the three northern cities and five southern cities, respectively. Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958 281 Research Influenza-associated mortality in ChinaLuzhao Feng et al. Compared with the over-dispersion of Poisson regression models, negative binomial models provided a better goodness of fit.30 Viral surveillance data were lagged by 0 to 3 weeks; the optimum lag (3 weeks for all death outcomes) was identified by computing Pearson coefficients (r) for the correla- tions with mortality outcomes (without any filtering).19,20 Influenza-associated excess deaths were estimated separately for influenza A(H1N1), A(H3N2) and B viruses (Fig. 1). Since no surveillance for respira- tory syncytial virus was conducted, no term for this pathogen was included in the model. As influenza circulated year-round in the subtropical southern provinces (Fig. 1), we used a spectral- analysis approach to decide whether the use of one or two periods in the model for the southern cities was preferable.31 Based on the results, we used 26- and 52- week periods for that model. The num- ber of deaths attributable to influenza was calculated as the difference between the predictions from the full model and the predictions from the model with the covariates for every influenza subtype set to zero (Appendix A). A Serfling regression model was used to provide an alternative estimate of influenza-associated mortality in the northern cities.9,10 In this approach, the baseline mortality in the absence of in- fluenza virus circulation was established by fitting a seasonal linear regression model, after excluding periods with high influenza activity (i.e. weeks 44–52 and 1–8; Fig. 1). Epidemic weeks were defined as those weeks during each influenza sea- son (weeks 40–52 and 1–13) when the observed number of deaths exceeded the epidemic threshold (defined as the upper 95% confidence limit on the baseline) for two or more consecutive weeks. Rates of weekly excess mortality were calculated as the observed mortal- ity minus the baseline for all epidemic weeks (Appendix A). Seasonal excess mortality was then estimated as the sum of the weekly excess mortalities. Although all model terms representing linear and nonlinear time trends yielded statistical significance (P < 0.05), the terms representing seasonal fluctuations did not (P > 0.05). Overall, the Serfling regression models for the three northern cities fitted the mortality data for people aged ≥ 65 years moderately well when the deaths analysed were those coded as respiratory and circulatory disease (R2 = 0.57; fit excluding winter weeks), ischaemic heart disease (R2 = 0.61), chronic obstructive pulmonary disease (r = 0.36) or any cause (R2 = 0.51), but they only gave a poor fit with deaths attributed to pneumonia and influenza (R2 = 0.04). For people aged < 65 years, the R2 values for each death category were generally lower, having ranged from 0.16 to 0.27, and the fit with the data on deaths coded as pneumonia and influenza was too poor to yield statistical significance. Wilcoxon signed-rank tests were used to compare the annual mean death rates for the three northern cities that were estimated using the negative bino- mial model with: (i) the corresponding estimates from the Serfling model, and (ii) the rates in the five southern cities that were also estimated using the nega- tive binomial model. Version 9.1 of the SAS software package (SAS Institute, Cary, USA) was used for all the statistical analyses. A P- value of < 0.05 was considered indicative of a statistically significant difference. Results Mortality Between 2003 and 2008, the mean annu- al mortality rates, in deaths per 100 000 population, were 618 (range: 581–659) in the three northern cities and 692 (range: 673–708) in the five southern cities. Most of the deaths (69.6% in the northern cities and 77.8% in the south- ern) occurred among individuals aged ≥ 65 years. The coded cause of almost half of all deaths (49.0% in the northern cities and 46.2% in the southern cities) was respiratory and circulatory disease (Table 1, available at: http://www.who. int/bulletin/volumes/90/4/11-096958). Death rates for the other disease out- comes varied between the southern and northern cities, with the northern cities recording relatively high numbers of deaths attributed to ischaemic heart disease or pneumonia and influenza and relatively low numbers of deaths attributed to chronic obstructive pul- monary disease. In all the study cities, the underlying cause of death was rarely coded as influenza. During the 6-year study period, all categories of death peaked in the winter months in each city that was investigated. A second peak in mortality was observed in the southern cities in June and July (Fig. 1 and Appendix A). In general, annual death rates were relatively constant throughout the study period. However, the annual mortality attributed to ischaemic heart disease in the northern cities increased over the study period (the linear regression of death rate against week gave a P-value of < 0.01), while that attributed to chronic obstructive pulmonary disease in south- ern cities showed a significant decrease (P < 0.01). Influenza virus activity in the three temperate northern cities showed marked seasonality matching mortality patterns, whereas influenza apparently circulated year-round in the five sub- tropical southern cities, with no clear seasonality (Fig. 1). Influenza-associated excess deaths Negative binomial models The negative binomial models indicated that, for the period 2003–2008, the mean annual numbers of influenza-associated all-cause excess deaths in the northern cities and southern study cities were 1825 (range: 1103–3397) and 2446 (range: 1551–3844), respectively. The corresponding annual mortality in the northern cities was higher than that in the southern cities (18.0 versus 11.3 influenza-associated excess deaths per 100 000 persons), but the difference did not quite reach statistical significance in a Wilcoxon signed-rank test (P = 0.063; Table 2). Most influenza-associated excess deaths (93.7% and 86.3% of those in the northern and southern cities, respectively) occurred among people aged ≥ 65 years, and the rates of influenza-associated excess mortality in this age group were much higher than among younger individuals, in both the northern study cities (150.8 versus 1.3 deaths per 100 000) and the southern cities (75.4 versus 1.8 per 100 000). The rates of influenza-associated mortality attributed to respiratory and circulatory disease were higher in northern than in southern cities (12.4 versus 8.8 deaths per 100 000) but, again, the difference did not reach statistical significance in a Wilcoxon signed- rank test (P = 0.091). Almost all of the influenza-associated deaths attributed to respiratory and circulatory disease oc- curred among people aged ≥ 65 years in both the northern (95.7%) and southern (94.0%) cities, and the corresponding mortality rates were higher in people aged ≥ 65 years than in younger individ- Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958282 Research Influenza-associated mortality in China Luzhao Feng et al. (c on tin ue s . ..) Ta bl e 2. In flu en za -a ss oc ia te d ex ce ss d ea th s i n ei gh t c iti es , b y a ge a nd co de da ca us e of d ea th , C hi na , 2 00 3– 20 08 Se as on No . o f ep id em ic w ee ks Th re e no rt he rn ci tie sb (S er fli ng m od el ) Th re e no rt he rn ci tie sb (n eg at iv e bi no m ia l m od el ) Fi ve so ut he rn ci tie sc ( ne ga tiv e bi no m ia l m od el ) To ta ld Αg e ≥ 65 ye ar s To ta ld Αg e ≥ 65 ye ar s To ta ld Αg e ≥ 65 ye ar s No . ( CI ) Ra te e ( CI ) No . ( CI ) % o f t ot al No . ( CI ) Ra te e ( CI ) No . ( CI ) % o f t ot al No . ( CI ) Ra te e ( CI ) No . ( CI ) % o f t ot al R& C 20 02 –0 3f 7 11 54 23 .6 10 30 89 .2 48 0 9. 8 46 1 96 .0 56 2 5. 3 53 4 95 .0 (4 32 –1 96 0) (8 .8 –4 0. 1) (4 30 –1 63 0) (1 56 –2 09 8) (3 .2 –4 2. 9) (1 56 –1 72 3) (0 –3 53 9) (0 –3 3. 2) (0 –3 21 9) 20 03 –0 4 7 12 49 12 .7 11 36 90 .9 94 5 9. 6 91 8 97 .1 11 86 5. 5 11 46 96 .6 (5 39 –2 05 6) (5 .5 –2 0. 9) (5 36 –1 73 6) (5 15 –4 36 0) (5 .2 –4 4. 2) (5 15 –3 57 4) (2 06 –6 84 4) (1 .0 –3 2. 0) (2 06 –6 13 5) 20 04 –0 5 9 16 64 16 .6 15 88 95 .4 14 93 14 .9 14 32 95 .9 30 18 14 .0 28 47 94 .3 (8 07 –2 68 8) (8 .1 –2 6. 9) (8 07 –2 36 8) (7 32 –4 60 6) (7 .3 –4 6. 0) (7 32 –3 86 8) (7 90 –8 88 7) (3 .7 –4 1. 3) (7 67 –7 98 4) 20 05 –0 6 4 73 6 7. 2 52 9 71 .9 75 1 7. 4 70 4 93 .7 20 20 9. 3 18 73 92 .7 (2 56 –1 22 3) (2 .5 –1 2. 1) (1 62 –8 96 ) (9 0– 41 38 ) (0 .9 –4 0. 8) (9 0– 32 70 ) (5 88 –7 44 1) (2 .7 –3 4. 3) (5 65 –6 55 6) 20 06 –0 7 6 10 31 10 .0 99 3 96 .3 14 50 14 .1 13 84 95 .4 13 79 6. 3 13 05 94 .6 (4 30 –1 76 2) (4 .2 –1 7. 2) (4 30 –1 55 7) (4 90 –4 80 6) (4 .8 –4 6. 8) (4 90 –4 01 0) (6 7– 67 47 ) (0 .3 –3 0. 9) (6 7– 60 21 ) 20 07 –0 8 9 22 96 22 .1 20 79 90 .5 23 09 22 .2 22 10 95 .7 30 18 13 .6 28 03 92 .9 (1 2 78 –3 43 9) (1 2. 3– 33 .1 ) (1 2 11 – 29 46 ) (1 1 98 –6 16 4) (1 1. 5– 59 .4 ) (1 1 98 – 52 38 ) (7 60 –9 09 3) (3 .4 –4 1. 1) (7 38 –8 17 6) 20 08 –0 9f 0 0 0 0 0 11 1 2. 1 10 4 93 .7 31 0 2. 8 29 2 94 .2 (0 –0 ) (0 –0 ) (0 –0 ) (0 –2 15 7) (0 –4 1. 4) (0 –1 72 8) (0 –3 16 5) (0 –2 8. 3) (0 –2 84 5) M ea n 7 13 55 13 .4 12 26 90 .5 12 57 12 .4 12 02 95 .7 19 16 8. 8 18 00 94 .0 (6 24 –2 18 8) (6 .2 –2 1. 6) (5 96 –1 85 5) (5 30 –4 72 2) (5 .2 –4 6. 6) (5 30 –3 90 2) (4 02 –7 61 9) (1 .8 –3 5. 1) (3 91 –6 82 3) A ll- ca us e 20 02 –0 3f 7 18 23 37 .3 15 27 83 .7 74 8 15 .3 69 5 92 .9 70 0 6. 6 59 8 85 .4 (6 59 –3 16 4) (1 3. 5– 64 .7 ) (6 33 –2 42 1) (2 48 –3 49 6) (5 .1 –7 1. 5) (2 48 –2 64 5) (1 5– 45 03 ) (0 .1 –4 2. 3) (1 5– 36 30 ) 20 03 –0 4 6 15 62 15 .8 12 97 83 .0 13 46 13 .7 12 19 90 .6 15 51 7. 3 12 85 82 .8 (5 38 –2 70 7) (5 .5 –2 7. 5) (5 30 –2 06 3) (6 42 –6 94 1) (6 .5 –7 0. 4) (6 42 –5 19 1) (6 4– 10 2 48 ) (0 .3 –4 7. 9) (6 4– 82 26 ) 20 04 –0 5 9 23 22 23 .2 21 77 93 .7 21 54 21 .5 20 11 93 .4 38 29 17 .8 32 91 85 .9 (1 0 12 –3 95 5) (1 0. 1– 39 .5 ) (1 0 12 – 33 41 ) (1 0 26 –7 14 6) (1 0. 2– 71 .4 ) (1 0 26 – 55 87 ) (5 68 –1 3 07 7) (2 .6 –6 0. 8) (5 64 –1 0 61 1) 20 05 –0 6 2 41 7 4. 1 30 8 73 .9 11 03 10 .9 10 75 97 .5 26 04 12 .0 22 80 87 .6 (4 3– 82 1) (0 .4 –8 .1 ) (3 4– 58 2) (1 94 –6 29 7) (1 .9 –6 2. 1) (1 94 –4 79 5) (5 51 –1 0 96 8) (2 .5 –5 0. 6) (5 44 –8 66 0) 20 06 –0 7 2 51 5 5. 0 45 8 89 .0 20 26 19 .7 18 88 93 .2 17 53 8. 0 15 11 86 .2 (1 79 –9 25 ) (1 .7 –9 .0 ) (1 79 –7 38 ) (6 18 –7 24 1) (6 .0 –7 0. 5) (6 18 –5 65 5) (1 4– 98 64 ) (0 .1 –4 5. 2) (1 4– 78 43 ) 20 07 –0 8 10 37 21 35 .8 31 70 85 .2 33 97 32 .7 31 98 94 .1 38 44 17 .4 33 55 87 .3 (1 8 57 –5 80 2) (1 7. 9– 55 .9 ) (1 7 33 – 46 06 ) (1 7 78 –9 56 3) (1 7. 1– 92 .1 ) (1 7 78 – 76 14 ) (6 46 –1 3 10 1) (2 .9 –5 9. 2) (6 41 –1 0 74 6) Research 283Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958 (.. . c on tin ue d) uals. In general, the influenza-associated mortality attributed to other causes linked to influenza (i.e. ischaemic heart disease, chronic obstructive pulmonary disease and pneumonia and influenza) showed similar age- and region-specific patterns, although the mortality attrib- uted to chronic obstructive pulmonary disease was higher in the southern cities than in the northern ones (Appendix A). The influenza-associated excess all- cause mortality and the corresponding excess mortality attributed to respiratory and circulatory disease showed season- to-season variability. Most influenza- associated excess deaths were associated with the B or A(H3N2) viruses; only 11% of such deaths in the northern cit- ies investigated and no such deaths in the southern cities were associated with A(H1N1) (Table 3). Of the influenza- associated excess deaths, a greater pro- portion was associated with the B virus than with A(H3N2), both in the northern cities (49.6% versus 39.7% for respiratory and circulatory disease; 50.9% versus 38.2% for all-cause) and in the southern ones (66.1% versus 33.9% for respiratory and circulatory disease; 64.8% versus 35.2% for all-cause). However, the cor- responding P-values from Wilcoxon signed-rank tests (0.735, 0.735, 0.128 and 0.176, respectively) were all too high to indicate statistical significance. The rate of influenza B-associated excess mortality in the B-predominant season (2007–2008) was about double that of the A(H3N2)-associated mortality in the A(H3N2)-predominant seasons (i.e. the 2003–2004 and 2006–2007 seasons in the northern cities and the 2003–2004 and 2004–2005 seasons in the southern cities) and much higher than the A(H1N1)-asso- ciated mortality in the A(H1N1)-predom- inant season (2005–2006; Table 3). This pattern was observed in both age groups that we considered and in both the north- ern and southern cities (Appendix A). In both the northern and the southern cities, the excess rates of all-cause mortality and of mortality attributed to respiratory and circulatory disease were positively cor- related with the percentages of specimens testing positive for influenza B (Fig. 2). Serfling models The age-specific rates of influenza- associated excess mortality that were estimated using Serfling models were similar to those derived using negative binomial models (Wilcoxon signed-rank tests, P > 0.05; Table 2 and Appendix A). Most of the excess deaths estimated using Serfling models (86.3% of the all-cause deaths and 90.5% of those at- tributed to respiratory and circulatory disease) occurred among people aged ≥ 65 years. Discussion Our findings demonstrate that influenza activity is associated with excess deaths in China – a lower middle-income country with the world’s largest popula- tion and diverse climate patterns. Our estimates of the annual rates for total influenza-associated all-cause mortality and for influenza-associated mortality attributed to respiratory and circula- tory disease in eight Chinese cities are similar to estimates from other countr ies.3–5,10–12,15,16,19,21,22 The impact of sea- sonal influenza on mortality in China disproportionately affects people aged ≥ 65 years (e.g. between 2003 and 2008, > 85% of the influenza-associated deaths in the study cities occurred in this age group). This finding is consistent with observations made in Hong Kong SAR,19 Singapore22 and the United States of America,4 where about 90% of influen- za-associated deaths have been found to occur among the elderly. In the temperate study areas of northern China, where influenza cir- culation is strongly seasonal, we used both Serfling and negative binominal models to estimate the excess mortality associated with influenza. The fact that these two approaches produced similar estimates for all-cause mortality and for mortality associated with respiratory and circulatory disease demonstrates the robustness of our results. The coding of very few deaths as having been caused by pneumonia and influenza in China may explain why the fit of the Serfling models to the data on such deaths was particularly poor. The rate of influenza-associated mortality in the temperate study areas was higher than that in the subtropical study areas farther south, particularly among the elderly. Among the possible explanations for this difference are re- gional variation in socioeconomic and demographic factors; the reporting of vital statistics, and influenza seasonal- ity. The estimates of excess influenza- associated mortality made in the present study are similar to the corresponding estimates published for temperate Aus- tralia,15 Italy,11,12 Mexico16 and the United S ea so n No . o f ep id em ic w ee ks Th re e no rt he rn ci tie sb (S er fli ng m od el ) Th re e no rt he rn ci tie sb (n eg at iv e bi no m ia l m od el ) Fi ve so ut he rn ci tie sc ( ne ga tiv e bi no m ia l m od el ) To ta ld Αg e ≥ 65 ye ar s To ta ld Αg e ≥ 65 ye ar s To ta ld Αg e ≥ 65 ye ar s No . ( CI ) Ra te e ( CI ) No . ( CI ) % o f t ot al No . ( CI ) Ra te e ( CI ) No . ( CI ) % o f t ot al No . ( CI ) Ra te e ( CI ) No . ( CI ) % o f t ot al M ea n 6 17 27 17 .0 14 89 86 .3 18 25 18 .0 17 11 93 .7 24 46 11 .3 21 11 86 .3 (7 15 –2 89 6) (7 .1 –2 8. 6) (6 87 –2 29 2) (7 51 –7 38 3) (7 .4 –7 2. 9) (7 51 –5 70 1) (3 10 –1 0 94 0) (1 .4 –5 0. 4) (3 07 –8 78 1) CI : 9 5% c on fid en ce in te rv al ; R &C ; r es pi ra to ry a nd c irc ul at or y di se as e. a I nt er na tio na l s ta tis tic al cl as sifi ca tio n of d ise as es a nd re la te d he al th p ro bl em s, te nt h re vi sio n. 28 b D al ia n, Q in gd ao a nd Z ha oy ua n. c G ua ng zh ou , N in gb o, S ha ng ha i, W uh an a nd Y ic ha ng . d T he su m o f t he e st im at es o f e xc es s i nfl ue nz a- as so ci at ed d ea th s f or th e pe op le a ge d < 65 y ea rs a nd th e pe op le ≥ 65 y ea rs . e I n de at hs p er 1 00 00 0. f B ec au se th e st ud y w as b as ed o n da ta c ol le ct ed b et w ee n th e st ar t o f 2 00 3 an d th e en d of 2 00 8, o nl y th e re su lts fo r t he la st h al f o f t he 2 00 2– 03 se as on (i .e . J an ua ry 2 00 3 to Ju ne 2 00 3) a nd th e fir st h al f o f t he 2 00 8– 09 se as on (i .e . J ul y 20 08 to D ec em be r 2 00 8) a re in cl ud ed . Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958284 Research Influenza-associated mortality in China Luzhao Feng et al. Ta bl e 3. In flu en za -a ss oc ia te d ex ce ss m or ta lit y i n ei gh t c iti es , b y i nfl ue nz a vi ru s t yp e an d su bt yp e, Ch in a, 2 00 3– 20 08 Se as on Po sit iv e re sp ira to ry sp ec im en s ( % ) No . ( % ) o f e xc es s d ea th s p er 1 00 00 0 pe op le w ith d ea th co de d as : A( H1 N1 ) A( H3 N2 ) B Re sp ira to ry a nd ci rc ul at or y d ise as e Al l-c au se Al l A( H1 N1 ) A( H3 N2 ) B Al l A( H1 N1 ) A( H3 N2 ) B Th re e no rt he rn ci ti es a 20 02 –0 3b 4. 3 54 .3 41 .4 9. 8 0. 1 (1 .3 ) 3. 8 (3 9. 2) 5. 8 (5 9. 6) 15 .3 0. 2 (1 .2 ) 5. 8 (3 8. 0) 9. 3 (6 0. 8) 20 03 –0 4 3. 4 94 .7 1. 8 9. 6 0. 2 (1 .6 ) 9. 1 (9 5. 3) 0. 3 (3 .1 ) 13 .7 0. 2 (1 .6 ) 13 .0 (9 4. 9) 0. 5 (3 .4 ) 20 04 –0 5 2. 2 49 .1 48 .7 14 .9 0. 1 (0 .7 ) 5. 2 (3 5. 1) 9. 6 (6 4. 2) 21 .5 0. 2 (0 .8 ) 7. 2 (3 3. 6) 14 .1 (6 5. 6) 20 05 –0 6 81 .3 7. 7 11 .1 7. 4 4. 3 (5 8. 1) 0. 8 (1 1. 3) 2. 3 (3 0. 6) 10 .9 6. 2 (5 7. 5) 1. 2 (1 1. 2) 3. 4 (3 1. 4) 20 06 –0 7 31 .7 53 .2 15 .0 14 .1 2. 2 (1 5. 9) 7. 8 (5 5. 5) 4. 0 (2 8. 6) 19 .7 3. 2 (1 6. 2) 10 .6 (5 3. 9) 5. 9 (2 9. 9) 20 07 –0 8 1. 2 32 .3 66 .5 22 .2 0. 0 (0 .2 ) 4. 7 (2 1. 1) 17 .5 (7 8. 7) 32 .7 0. 1 (0 .3 ) 6. 6 (2 0. 0) 26 .1 (7 9. 7) 20 08 –0 9b 97 .2 2. 3 0. 5 2. 1 2. 0 (9 3. 7) 0. 1 (3 .6 ) 0. 1 (2 .7 ) 3. 4 3. 2 (9 5. 5) 0. 1 (2 .8 ) 0. 1 (1 .7 ) M ea n 38 .5 33 .9 27 .6 12 .4 1. 3 (1 0. 7) 4. 9 (3 9. 7) 6. 2 (4 9. 6) 18 .0 2. 0 (1 0. 9) 6. 9 (3 8. 2) 9. 2 (5 0. 9) Fi ve s ou th er n ci ti es c 20 02 –0 3b 4. 0 74 .0 22 .0 5. 3 0 (0 ) 2. 3 (4 4. 0) 3. 0 (5 6. 0) 6. 6 0 (0 ) 3. 1 (4 6. 7) 3. 5 (5 3. 3) 20 03 –0 4 0. 0 93 .2 6. 8 5. 5 0 (0 ) 4. 5 (8 2. 0) 1. 0 (1 8. 0) 7. 3 0 (0 ) 6. 0 (8 2. 3) 1. 3 (1 7. 7) 20 04 –0 5 8. 7 66 .3 24 .9 14 .0 0 (0 ) 5. 8 (4 1. 7) 8. 2 (5 8. 3) 17 .8 0 (0 ) 7. 8 (4 3. 7) 10 .0 (5 6. 3) 20 05 –0 6 53 .2 11 .1 35 .7 9. 3 0 (0 ) 1. 0 (1 0. 6) 8. 3 (8 9. 4) 12 .0 0 (0 ) 1. 4 (1 2. 1) 10 .6 (8 7. 9) 20 06 –0 7 35 .0 44 .7 20 .3 6. 3 0 (0 ) 2. 9 (4 5. 3) 3. 5 (5 4. 7) 8. 0 0 (0 ) 3. 6 (4 4. 8) 4. 4 (5 5. 2) 20 07 –0 8 5. 7 35 .2 59 .1 13 .6 0 (0 ) 2. 3 (1 6. 9) 11 .3 (8 3. 1) 17 .4 0 (0 ) 3. 1 (1 7. 8) 14 .3 (8 2. 2) 20 08 –0 9b 71 .3 12 .9 15 .8 2. 8 0 (0 ) 0. 6 (2 3. 2) 2. 1 (7 6. 8) 3. 5 0 (0 ) 0. 9 (2 5. 7) 2. 6 (7 4. 3) M ea n 29 .7 38 .9 31 .4 8. 8 0 (0 ) 3. 0 (3 3. 9) 5. 8 (6 6. 1) 11 .3 0 (0 ) 4. 0 (3 5. 2) 7. 3 (6 4. 8) a D al ia n, Q in gd ao a nd Z ha oy ua n. b B ec au se th e st ud y w as b as ed o n da ta c ol le ct ed b et w ee n th e st ar t o f 2 00 3 an d th e en d of 2 00 8, o nl y th e re su lts fo r t he la st h al f o f t he 2 00 2– 03 se as on (i .e . J an ua ry 2 00 3 to Ju ne 2 00 3) a nd th e fir st h al f o f t he 2 00 8– 09 se as on (i .e . J ul y 20 08 to D ec em be r 2 00 8) a re in cl ud ed . c G ua ng zh ou , N in gb o, S ha ng ha i, W uh an a nd Y ic ha ng . Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958 285 Research Influenza-associated mortality in ChinaLuzhao Feng et al. States,3–5,10 the subtropical city of Guang- zhou in China,21 subtropical Hong Kong SAR19 and tropical Singapore22 (Table 4, available at: http://www.who. int/bulletin/volumes/90/4/11-096958). However, at least three issues must be considered when comparing our results with those of other studies: the presence or absence of other variables, such as indicators of respiratory syncytial virus activity, in the model used4,22; differ- ences in the study periods, each with distinct influenza activities and domi- nant strains; and potential differences in the quality of the viral surveillance and mortality data used. Our most interesting findings were that influenza-associated death rates were highest during periods when in- fluenza B virus was circulating, rather than during periods when A(H3N2) was dominant, and that very few or no deaths were associated with the A(H1N1) virus. These results differ substantially from the mortality patterns seen in Hong Kong SAR and the United States,4,9,10,19 where the highest death rates were associated with A(H3N2) activity. However, our results should be treated with caution since they are based on data collected over only five influenza seasons. The prevalence of influenza B during the study period may have been unusually high, and the patterns of influenza seasonality and circulation in China appear to be complex. Additional studies exploring the association be- tween influenza B and mortality are war- ranted in China and other parts of the world. Limited information is available on the clinical severity of influenza B infections in China, and, unfortunately, too few young children were included in our study to give a reasonable estimate of influenza B-associated mortality in this age group. Further studies in subtropical southern China would be very interest- ing in this respect, as influenza viruses there circulate year-round, with peaks in both summer and winter months and a complex cycling of subtypes. Ad- ditionally, surveillance data for other respiratory viral and bacterial infections, including respiratory syncytial virus, are crucial if the patterns of influenza- related mortality in China are to be fully elucidated. Our study has several potential limitations. Even in the large urban cities that we investigated, some deaths dur- ing the study period were probably not registered and the recorded underlying causes of some of the registered deaths were probably not specific enough to be coded accurately.29,32,33 Such under- reporting and misclassification of deaths could lead to the underestimation of influenza-associated excess mortality in China. Our estimates of the influenza- associated excess mortalities attributed to pneumonia and influenza are much lower than those reported from more developed countries, probably owing to between-country differences in cod- ing practices for diseases of the lower respiratory tract.4,5,10,12,19,22 In addition, as influenza virus surveillance in China gradually expanded between 2000 and 2005, year-to-year variations in surveil- lance coverage and/or laboratory meth- ods may have influenced our estimates, despite our attempts to adjust for the annual number of specimens tested for influenza. Finally, given the substantial regional differences in climate, access to medical care and socioeconomic deter- minants of health, as well as the dispari- ties between urban and rural areas, our estimates based on mortality data from eight relatively wealthy cities in eastern China may not be generalizable to the rest of the country. This study highlights the substantial mortality associated with influenza in both temperate and subtropical areas of China. The findings have important implications for China’s strategies to prevent and control influenza. First, our results contrast with the general percep- tion that influenza is not an important contributor to mortality in China. Sec- ond, they support the recommendation issued by the Chinese Centre for Disease Control and Prevention to practice an- nual influenza vaccination of the elderly (as the target population at the greatest Fig. 2. Estimates of influenza-associated mortality plotted against specimen positivity for influenza B virus, China, 2003–2008 r = 0.90, P = 0.035 for all-cause deaths r = 0.71, P = 0.181 for all-cause deaths r = 0.89, P = 0.043 for deaths attributed to respiratory and circulatory disease r = 0.71, P = 0.182 for deaths attributed to respiratory and circulatory disease Es tim at ed an nu al m or ta lit y ( de at hs p er 1 00 0 00 ) 35 30 25 20 15 10 5 0 25 20 15 10 5 0 % of typed respiratory specimens found positive for influenza B virus % of typed respiratory specimens found positive for influenza B virus 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Northern cities Southern cities Deaths attributed to respiratory and circulatory disease All-cause deaths Note: The upper and lower panels show the results for the three northern cities (Dalian, Qingdao and Zhaoyuan) and the five southern cities (Guangzhou, Ningbo, Shanghai, Wuhan and Yichang), respectively. Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958286 Research Influenza-associated mortality in China Luzhao Feng et al. 摘要 2003 年至 2008 年在中国温带及亚热带城市中流感引起的死亡率 目的 估算中国城市流感引起的死亡率 方法 根据负二项回归模式、人口动态统计及每周流感病 毒监控结果, 对 2003 年至 2008 年间中国北方三个温带 城市及南方五个亚热带城市流感引起的非自然性死亡率 进行估算。 结果 每年因各种原因由流感引起的非自然性死亡率在北 方城市为每 10 万人口中 18（范围：10.9 - 32.7）例死亡 患者，在南方城市为每 10万个人口中 11.3（范围：7.3 - 17.8）例死亡患者。由流感引起呼吸系统及循环系统疾病 而导致的非自然性死亡率在北方城市为每10万人口中12.4 (范围: 7.4–22.2) 例死亡患者， 在南方城市为每10万人口 中8.8 (范围: 5.5–13.6) 例死亡患者。大多数（86%）死亡 患者的年龄大于等于 6 5岁。在 B 类病毒高发期季节里引 起的非自然性死亡率高于在A(H3N2) 或 A(H1N1) 病毒高 发期的季节引起的非自然性死亡率。超过一半的流感引起 的死亡病例均缘于 B 类流感病毒。 结论 2003 年至 2008 年间，在被调查的中国北方三个温 带城市及南方五个亚热带城市，大多数死亡病例缘于季节 性流感（特别是 B 型病毒引起的流感）。 صخلم 2008 - 2003 ،ةيئاوتسلاا هبشو ةلدتعلما ةينيصلا ندلما في ازنولفنلأاب ةطبترلما تايفولا في ةيضرلحا قطانلما في ازنولفنلأاب ةطبترلما تايفولا ريدقت ضرغلا .ينصلا في ازنولفنلأاب ةطبترلما تايفولل طرفلما لدعلما ريدقت مت ةقيرطلا ةيلماشلا ةقطنلما في ندم ثلاث في 2008 - 2003 ينب ام ةترفلا ةيئاوتسلاا هبش ةيبونلجا ةقطنلما في ندم سخمو ينصلا في ةلدتعلما لىع ةدمتعم جذمان نم تاريدقتلا هذه ءاقتسا متو .دلبلا نم جئاتنو ةيويلحا تاءاصحلإاو دودلحا ةيئانث ةيبلسلا تادادترلاا .ازنولفنلأا سويرفل ةيعوبسلأا ةبقارلما ،ازنولفنلأاب ةطبترلما تايفولل طرفلما يونسلا لدعلما غلب جئاتنلا لكل )32.7-10.9 :قاطنلا( ةافو ةلاح 18.0 ،بابسلأا عيملج :قاطنلا( ةافو ةلاح 11.3و ةيلماشلا ندلما في ةمسن 100000 ىزعُي .ةيبونلجا ندلما في ةمسن 100000 لكل )17.8-7.3 )22.2-7.4 :قاطنلا( 12.4 – تايفولل طرفلما لدعلما مظعم ةمسن 100000 لكل )13.6-5.5 :قاطنلا( ةافو ةلاح 8.8و ضارمأب ةباصلإا لىإ – لياوتلا لىع ،ةيبونلجاو ةيلماشلا ندلما في تلااح مظعم تثدحو .يرودلا زاهلجا وأ/و سيفنتلا زاهلجا طرفلما لدعلما ناكو .اًماع 65 ≥ صاخشلأا ينب )% 86( ةافولا اهيف شرتني نوكي يتلا لوصفلا في لىعأ ازنولفنلأاب ةطبترلما تايفولل )H3N2(سويرفلا اهيف شرتني يتلا لوصفلا في نع B سويرفلا ةطبترلما تايفولا لدعم فصن نم رثكأ طبتراو A)H1N1( وأ A .B ازنولفنلأا سويرفب ازنولفنلأاب ازنولفنلأا تطبترا ،2008و 2003 يماع ينب مايف جاتنتسلاا يربك ددعب B ازنولفنلأا سويرف اهببسي يتلا صخلأابو ،ةيمسولما ينصلا في ةلدتعلما ةيلماشلا ةقطنلما في ندم ثلاث في تايفولا نم .دلبلا تاذ نم ةيئاوتسلاا هبش ةيبونلجا ةقطنلما في ندم سخمو risk of developing severe complications from influenza infections).34 Third, the finding that seasons in which influ- enza B virus dominates are associated with relatively high mortality deserves special attention and scrutiny, and it suggests the need to improve seasonal surveillance and characterization of influenza B virus variants. Our strategy of using the mortality data available for a period of about 5 years from large cit- ies to model influenza-associated deaths may be applicable in other countries that lack national mortality registration. The present estimates of seasonal influenza-associated deaths in selected urban cities represent only the first step in quantifying the burden posed by in- fluenza in China. The next steps include describing the impact on mortality of infection with A(H1N1)pdm09 and a more comprehensive assessment of seasonal influenza-associated mortality using a nationally-representative system of death registration. In addition, fur- ther studies are needed to evaluate the impact of underlying host susceptibility, access to medical care, socioeconomic status and co-circulating bacterial and viral pathogens on the influenza bur- den in different areas of China. Such studies can help strengthen evidence- based decision-making and guide the introduction of national programmes of influenza immunization to mitigate the global impact of inter-pandemic influenza. ■ Acknowledgements We thank the local Centres for Disease Control and Prevention in the study areas for their valuable assistance during the course of our research. Funding: This study was supported by the China–US Collaborative Program on Emerging and Re-emerging Infectious Diseases. Competing interests: None declared. Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958 287 Research Influenza-associated mortality in ChinaLuzhao Feng et al. Résumé Mortalité associée à la grippe dans les villes des zones tempérées et subtropicales de Chine, 2003–2008 Objectif Estimer la mortalité associée à la grippe en Chine urbaine. Méthodes La mortalité excessive associée à la grippe pour la période 2003–2008 a été évaluée dans trois villes de la zone tempérée du nord de la Chine et dans cinq villes de la zone subtropicale du pays. Les estimations ont été établies sur des modèles basés sur des régressions binomiales négatives, des statistiques vitales et les résultats de la surveillance hebdomadaire de la grippe. Résultats La mortalité annuelle excessive associée à la grippe, dans tous les cas, a été de 18 (plage: 10,9–32,7) décès pour une population de 100 000 personnes dans les villes du nord et de 11,3 (plage: 7,3–17,8) décès pour une population de 100 000 personnes dans les villes du sud. La plus grande partie de cette mortalité excessive – respectivement 12,4 (plage: 7,4–22,2) et 8,8 (plage: 5,5–13,6) décès pour une population de 100 000 personnes dans les villes du nord et du sud – a été attribuée à des maladies respiratoires et/ou circulatoires. La plupart des décès (86%) sont survenus chez des personnes de ≥65 ans. La mortalité excessive associée à la grippe a été plus élevée lors des saisons où prédominait le virus B plutôt que lors de celles où prédominaient les virus A(H3N2) ou A(H1N1) et plus de la moitié de l’ensemble de la mortalité associée à la grippe a été associée au virus B de la grippe. Conclusion De 2003 à 2008, la grippe saisonnière, surtout celle provoquée par le virus B, a été associée à une mortalité substantielle dans trois villes du nord tempéré de Chine et dans cinq villes du sud subtropical du pays. Резюме Влияние эпидемий гриппа на смертность в в городах умеренного и субтропического пояса Китая в 2003–2008 годах Цель Произвести оценку влияния эпидемий гриппа на смертность среди городского населения Китая. Методы В 2003-2008 гг. среди жителей трех городов северного Китая с умеренным климатом и пяти городов субтропического юга страны была произведена оценка роста смертности, связанного с заболеванием гриппом. Оценивание осуществлялось с помощью моделей, основанных на отрицательной биномиальной регрессии, а также на основании демографической статистики и результатов еженедельных наблюдений за распространением вируса гриппа. Результаты Годовой рост смертности, связанный с заболеванием гриппом, независимо от причины смерти составил 18,0 (диапазон: 10,9 – 32,7) смертей на 100 000 жителей в северных городах и 11,3 (диапазон: 7,3–17,8) смертей на 100 000 жителей в южных городах. Большая часть данного роста – 12,4 (диапазон: 7,4 – 22,2) и 8,8 (диапазон: 5,5 – 13,6) количества смертей на 100 000 жителей в северных и южных городах, соответственно, вызвана респираторными заболеваниям и/или заболеваниями, протекающими с расстройством кровообращения. Большая часть (86%) смертей произошла в возрастной группе ≥ 65 лет. Рост смертности, связанной с заболеванием гриппом, был выше в периоды доминирования вируса B по сравнению с периодами, когда преобладали вирусы A(H3N2) либо A(H1N1); более половины всех связанных с заболеванием гриппом случаев смерти относится к вирусу гриппа B. Вывод В период между 2003 и 2008 гг. существенное повышение уровня смертности в трех городах севера Китая с умеренным климатом и пяти городах субтропического юга страны было связано с сезонной заболеваемостью гриппом, вызванной, главным образом, вирусом гриппа B. Resumen La mortalidad asociada a la gripe en ciudades chinas con clima templado y subtropical, 2003–2008 Objetivo Calcular la mortalidad asociada a la gripe en la China urbana. Métodos Se calculó el exceso de mortalidad asociado a la gripe durante el periodo comprendido entre 2003 y 2008 en tres ciudades del norte de China con clima templado y en cinco ciudades del sur del país con clima subtropical. Los cálculos se obtuvieron de modelos basados en regresiones binomiales negativas, estadísticas vitales y de los resultados de la vigilancia semanal del virus de la gripe. Resultados El exceso de mortalidad anual asociado a la gripe, por todas las causas, fue de 18,0 (rango: 10,9–32,7) muertes por cada 100 000 habitantes en las ciudades del norte y de 11,3 (rango: 7,3–17,8) muertes por cada 100 000 habitantes en las ciudades del sur. La mayor parte de este exceso de mortalidad – 12,4 (rango: 7,4–22,2) y 8,8 (rango: 5,5–13,6) muertes por cada 100 000 habitantes en las ciudades del norte y del sur, respectivamente – se atribuyeron a una enfermedad respiratoria y/o circulatoria. La mayoría de las muertes (el 86%) ocurrió en personas con una edad ≥ 65 años. El exceso de mortalidad asociado a la gripe fue superior en épocas con un virus B dominante que en épocas en las que predominaron los virus A(H3N2) o A(H1N1). 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All-cause (AC) deaths and codeda causes of death in eight cities, China, 2003–2008 City and year Population (millions) Deaths per 100 000 people (% of AC) AC R&C IHD COPD P&I In Three northern citiesb 2003 9.8 580.5 272.7 (47.0) 64.2 (11.1) 23.1 (4.0) 9.2 (1.6) 0.4 (0.1) 2004 9.9 613.1 294.0 (48.0) 72.0 (11.8) 25.4 (4.1) 8.9 (1.5) 0.3 (0.1) 2005 10.1 614.2 306.7 (49.9) 80.2 (13.1) 23.6 (3.8) 8.3 (1.4) 0.2 (0.0) 2006 10.2 612.9 308.3 (50.3) 87.8 (14.3) 26.6 (4.3) 8.3 (1.4) 0.3 (0.0) 2007 10.3 623.6 312.7 (50.1) 89.8 (14.4) 30.4 (4.9) 8.5 (1.4) 0.1 (0.0) 2008 10.4 659.1 319.0 (48.4) 94.7 (14.4) 28.9 (4.4) 8.2 (1.2) 0.1 (0.0) Mean 10.1 617.7 302.5 (49.0) 81.7 (13.2) 26.4 (4.3) 8.6 (1.4) 0.2 (0.0) Five southern citiesc 2003 21.3 690.4 322.4 (46.7) 56.6 (8.2) 93.8 (13.6) 6.1 (0.9) 0.2 (0.0) 2004 21.4 673.3 306.1 (45.5) 56.4 (8.4) 77.4 (11.5) 6.5 (1.0) 0.1 (0.0) 2005 21.6 707.6 330.0 (46.6) 62.8 (8.9) 81.6 (11.5) 6.9 (1.0) 0.2 (0.0) 2006 21.7 668.4 300.7 (45.0) 61.6 (9.2) 69.4 (10.4) 6.1 (0.9) 0.1 (0.0) 2007 21.9 708.0 325.6 (46.0) 68.3 (9.6) 74.9 (10.6) 6.5 (0.9) 0.1 (0.0) 2008 22.4 702.1 330.8 (47.1) 71.4 (10.2) 75.2 (10.7) 8.5 (1.2) 0.1 (0.0) Mean 21.7 691.7 319.3 (46.2) 62.9 (9.1) 78.7 (11.4) 6.8 (1.0) 0.1 (0.0) R&C, respiratory and circulatory disease; IHD, ischaemic heart disease; COPD, chronic obstructive pulmonary disease; P&I, pneumonia and influenza; In, influenza. a International statistical classification of diseases and related health problems, tenth revision.28 b Dalian, Qingdao and Zhaoyuan. c Guangzhou, Ningbo, Shanghai, Wuhan and Yichang. Bull World Health Organ 2012;90:279–288B | doi:10.2471/BLT.11.096958288B Research Influenza-associated mortality in China Luzhao Feng et al. Ta bl e 4. Co m pa ris on o f e st im at es o f a nn ua l i nfl ue nz a- as so cia te d ex ce ss m or ta lit y i n Ch in a an d ot he r s el ec te d lo ca tio ns , b y a ge a nd ca us e of d ea th a s c od ed a o r r ec or de d St ud y a re a M od el St ud y p er io d Pr op or tio n of in flu en za se as on s b y: Ex ce ss d ea th s ( pe r 1 00 00 0 pe op le ) A( H3 N2 ) B Al l a ge s Ag e ≥ 65 ye ar s P& I R& C AC P& I R& C AC Au st ra lia 15 Po iss on 19 97 –2 00 4 N A N A N A N A N A 15 .2 80 .4 10 1. 2 Ch in a (G ua ng zh ou )21 Po iss on 20 04 –2 00 6 2/ 3 0/ 3 1. 0 9. 9 10 .6 N A 10 4. 1 11 1. 3 Ch in a (n or th er n ci tie s) b N eg at iv e bi no m ia l 20 03 –2 00 8 2. 5/ 6 1/ 6 0. 4 12 .4 18 .0 3. 1 10 6. 0 15 0. 8 Ch in a (n or th er n ci tie s) b Se rfl in g 20 03 –2 00 8 2. 5/ 6 1/ 6 0. 4 13 .4 17 .0 2. 6 10 8. 1 13 1. 3 Ch in a (s ou th er n ci tie s) b N eg at iv e bi no m ia l 20 03 –2 00 8 2. 5/ 6 1/ 6 0. 5 8. 8 11 .3 3. 6 64 .3 75 .4 Ch in a (H on g Ko ng S AR )19 Po iss on 19 96 –1 99 9 4/ 4 0/ 4 4. 1 12 .4 16 .4 39 .3 10 2. 0 13 6. 1 Ita ly 11 ,1 2 Se rfl in g 19 70 –2 00 1 21 /3 1 5/ 31 1. 9– 2. 2 N A 11 .6 –1 8. 6 12 .7 –1 4. 2 N A 71 .2 –1 15 .7 M ex ic o1 6 Se rfl in g 20 00 –2 00 8 6/ 9 1/ 9 1. 5 12 .7 15 .7 10 .4 c 11 5. 6c 14 7. 4c Si ng ap or e2 2 N eg at iv e bi no m ia l 19 96 –2 00 3 8/ 8 0/ 8 2. 9 11 .9 14 .8 46 .9 15 5. 4 16 7. 8 U ni te d St at es 4 Po iss on 19 90 –1 99 9 6/ 9 2/ 9 3. 1 13 .8 19 .6 22 .1 98 .3 13 2. 5 U ni te d St at es 3 Po iss on 19 76 –2 00 2 14 /2 7 9/ 27 N A 9. 9 N A N A 72 .4 N A U ni te d St at es 5 Po iss on 19 76 –2 00 7 17 /3 1 9/ 31 2. 4 9. 0 N A 17 .0 66 .1 N A U ni te d St at es 10 Se rfl in g 19 80 –2 00 1 12 /2 1 6/ 21 2. 9 N A 15 .0 22 .0 N A 10 0. 0 AC , a ll- ca us e; N A, n ot a va ila bl e; P &I , p ne um on ia a nd in flu en za ; R &C , r es pi ra to ry a nd c irc ul at or y di se as e; S AR , S pe ci al A dm in ist ra tiv e Re gi on . a I nt er na tio na l s ta tis tic al cl as sifi ca tio n of d ise as es a nd re la te d he al th p ro bl em s, te nt h re vi sio n. 28 b D at a fro m p re se nt st ud y. c D at a fo r a ge ≥ 60 y ea rs .