Are health interventions implemented where they are most needed? District uptake of the integrated management of childhood illness strategy in Brazil, Peru and the United Republic of Tanzania.

792 Bulletin of the World Health Organization | October 2006, 84 (10) Objective To describe geographical patterns of implementation of the Integrated Management of Childhood Illness (IMCI) strategy in three countries and to assess whether the strategy was implemented in areas with the most pressing child health needs. Methods We conducted interviews with key informants at the national and district levels in Brazil, Peru and the United Republic of Tanzania, and an ecological study of factors associated with health worker training in IMCI. Explanatory factors included district population, distance from the capital, human development index, other socioeconomic indicators and baseline mortality rates in children younger than five years. Findings In line with recommendations by WHO, early implementation districts were characterized by proximity to the capital and suitable training sites, presence of motivated health managers and a functioning health system. In the expansion phase, IMCI tended to be adopted by other districts with similar characteristics. In Brazil, uptake by poor and small municipalities and those further away from the state capital was significantly lower. In Peru, there was no association with distance from Lima, and a non-significant trend for IMCI adoption by small and poor departments. In the United Republic of Tanzania, the only statistically significant finding was a lower uptake by remote districts. Implementation was not associated with baseline mortality levels in any country studied. Conclusion Whereas clear and reasonable guidelines are provided for selection of early use districts, no criteria for promoting IMCI expansion had been issued, and areas of greatest need were not prioritized. Equity analyses based on the geographical deployment of new programmes and strategies can contribute to assessing whether they are reaching those who need them most. Bulletin of the World Health Organization 2006;84:792-801. Voir page 799 le résumé en français. En la página 800 figura un resumen en español. Introduction There is ample literature on how the availability and quality of health care varies inversely in relation to an indiv vidual’s health needs, a principle that was convincingly stated by Julian Tudor Hart’s “inverse care law” in 1971.1 The sociological literature also suggests that new technologies or behaviours — including those related to health care — are initially adopted by a small group of innovators and later diffused to other social groups.2 Those with access to new health technologies are usually members of the upper social strata, who already have access to better care. Thus, it has been postulated that the health gap bev tween the rich and the poor may widen, Are health interventions implemented where they are most needed? District uptake of the Integrated Management of Childhood Illness strategy in Brazil, Peru and the United Republic of Tanzania CG Victora,a L Huicho,b JJ Amaral,c J Armstrong-Schellenberg,d F Manzi,e E Mason,f & R Scherpbier f .800 ةحفص في ةيبرعلاب صخللما لىع علاطلاا نكيم a Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, CP 464, Pelotas RS 96001 Brazil. Correspondence to this author (email: cvictora@terra.com.br). b Instituto de Salud del Niño and Universidad Nacional Mayor de San Marcos, Peru. c Universidade Federal do Ceará, Fortaleza, Brazil. d Gates Malaria Partnership, London School of Hygiene and Tropical Medicine, London, England. e Ifakara Health Research and Development Center, Ifakara, United Republic of Tanzania. f Department of Child and Adolescent Health and Development, Division of Family and Child Health, World Health Organization, Geneva, Switzerland. Ref. No. 06-030502 (Submitted: 27 January 2006 – Final revised version received: 30 May 2006 – Accepted: 11 June 2006) at least temporarily, when effective new interventions are introduced.3 In this paper we investigate a related issue at the geographical, rather than the individual level. We examined which factors were associated with the uptake, at district level, of a new strategy for improving the health of children. Our general hypothesis was that health inv terventions, programmes and strategies are often deployed without explicit atv tention to the question of which areas of the country are most likely to gain from their implementation. The Integrated Management of Childhood Illness (IMCI) strategy was developed in the midv1990s by WHO, the United Nations Children’s Fund (UNICEF) and their technical partners.4 IMCI was proposed as a strategy to unify the vertical child health programmes that were prevalent at that time, such as the Control of Diarrheal Diseases or Acute Respiratory Infections programmes. IMCI has three main components: improving the performance of health workers in firstvlevel facilities through a training course addressing leading causes of infant and child mortality; ensuring health systems support for child health (including drug and vaccine supply, supervision and health information systems); and the strengthening of famv ily practices needed to prevent disease, to stimulate appropriate utilization of health services, and to improve home 793Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. care for sick children.4 The IMCI case management guidelines were designed to address major causes of child mortalv ity — pneumonia, diarrhoea, malaria, measles and malnutrition in countries with mortality rates in children younger than 5 years (U5MRs) of 40 per 1000 live births or greater.5,6 IMCI was introduced at the country level in 1996, and since then more than 100 countries have adopted the strategy.6 In each country, IMCI was designed to evolve over three phases, namely the introduction, early implementation and expansion phases.7 In the introducv tory phase, countries held orientation meetings, trained key decisionvmakers in IMCI, defined a management strucv ture for preparing for IMCI planning and early implementation, and built government commitment to move forward with the IMCI strategy. In the early implementation phase, countries gained experience while implementing IMCI in limited geographical areas. They developed their national strategy and plan, adapted the IMCI guidelines to their national context, developed management and training capacity in a limited number of districts and started implementing and monitoring IMCI. The end of this phase was marked by a review meeting with the objective of synthesizing the experiences gained durv ing early implementation and planning for expansion. In the expansion phase, countries were encouraged to increase both the range of IMCI interventions and IMCI coverage.8 In practice, the range of interventions was seldom exv panded. The WHO document entitled IMCI planning guide: gaining experience with the IMCI strategy in a country 8 proposed a series of possible criteria for selecting two or three districts for early implementav tion in a country. The criteria included good physical access to centralvlevel staff; committed staff at the district level; availability of a training site; availability of drugs; existence of referral care; and availability of funds to support IMCI, e.g. from a donor institution. Additional selection criteria were also proposed, including the districts having similar childvfeeding practices and a common language, the need for diversity (for example, including periurban as well as rural districts) and the advantage of selecting districts that are already being targeted by external donors. As the above list shows, selection criteria for earlyvuse districts were mainly pragmatic and managerial. The purpose was to select a couple of demonstrav tion districts with several facilitating factors (e.g. proximity, good staff, availv able funding and referral capabilities) where IMCI could be shown to work, with a view to later expansion to other districts. The final section of the IMCI planv ning guide addresses the selection of districts for the expansion phase: “factors to consider in assessing district capacity or readiness to support the IMCI strategy are: a well functioning district managev ment team, inclusion of IMCI activities in the district health plan, availability of local training faculty (for example in a training institution) and the presence of a nongovernmental organization or other donor that is ready to technically and financially support IMCI implementav tion in the district.” 8 As for the early implementation phase, these criteria priv marily represent predictors of successful implementation rather than indicators of need for IMCI, such as high mortality or prevalence of malnutrition. In 1997, the multivcountry evaluv ation of IMCI effectiveness, cost and impact (MCEvIMCI) was launched; it included invdepth studies in Bangladesh, Brazil, Peru, Uganda and the United Republic of Tanzania.9 The objectives of the evaluation incorporated an assessv ment of the potential effects of IMCI on inequalities in child health. This entailed a study of the geographical spread of IMCI within countries, to determine whether or not the programme was reaching the areas with the most pressing child health needs. Of the five countries included in the evaluation, it was possible to obtain data on IMCI uptake at the district level in Brazil, Peru and the United Republic of Tanzania. This paper presents the results of this investigation. Methods In each country, two complementary apv proaches to data collection and analyses were used. Desk reviews and interviews with key informants were used to investiv gate the introduction, early implementav tion and expansion phases of IMCI with emphasis on which administrative units (e.g. districts, states, municipalities or departments, henceforward referred to as “districts”) were prioritized, and why. The second approach included stav tistical analyses of district characteristics associated with IMCI implementation during the expansion phase. An ecologiv cal design (a type of analysis in which the study units are geographical areas) was used to compare the spatial distribution of IMCI implementation with potential explanatory variables, including sociodev mographic factors, health infrastructure and previmplementation child health and nutritional status. The outcome variable was implev mentation of the casevmanagement training component of IMCI. Because the other two components of IMCI were less strongly implemented in most countries,6 and are also more difficult to measure, training coverage indicators were used in these analyses. The actual indicators used varied from country to country depending on the nature of the data available. Table 1 summarizes the main characteristics of the design in each country. An attempt was made to collect information on the same explanatory variables in each of the three countries, but the nature of data available varied from country to country. The informav tion obtained included general charv acteristics of the district (population, distance from the capital or largest city and urbanization rate), socioeconomic variables (literacy, income and gross dov mestic product (GDP)), environmental variables (water supply) and U5MR. For each of the three countries, we also attempted to obtain information on the Human Development Index, a composv ite indicator of GDP per capita, educav tion (weighted average of adult literacy rate and gross school enrolment ratio) and life expectancy at birth.10 Whenever possible, we used baseline values for all explanatory variables, that is, prevIMCI implementation levels. Details on the methods used in each country are presented below. Brazil In Brazil, the analyses were restricted to 443 municipalities with populations between 5000 and 50 000 inhabitv ants in three states in the northveast region of the country: Ceará, Paraíba and Pernambuco.11 These were leading states in IMCI implementation. Muv nicipalities were restricted to those with this population range because the study involved fieldwork12 — which would be difficult in large cities — and because a greater impact was expected in smaller cities where IMCI coverage could be scaled up rapidly. 794 Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. Table 1. Summary of study characteristics in the three sites Country Brazil Peru United Republic of Tanzania Study units 443 municipalities in three states in the north-east region All 24 departments in the country 82 of 118 districts in the country, and all 21 regions of the country Population range of study units (approximate) 5 000–50 000 80 000–7 000 000 300 000–2 500 000 (regions) Outcome: Integrated Manage- ment of Childhood Illness (IMCI) implementation variable Whether or not there were any IMCI- trained health workers in the municipality Percentage of doctors and nurses working in government facilities who were trained in IMCI Ranked date of first IMCI training course in district; mean rank of all districts in each region Reference period for the outcome 1999–2002 1996–2000 1995–2005 Statistical method c² test Pearson correlation coefficient Spearman rank correlation coefficient Based on data available at state level, municipalities were classified as to whether they had “strong IMCI” (trainv ing coverage over 50% in 2000 and over 60% in 2001 and 2002), “some IMCI” (at least one trained health worker in the period 2000–02), or “no IMCI.” If statev level data were not available, municipal departments of health were contacted by telephone to provide information on IMCI training. Only 23 municipalities were classified as having strong IMCI, 216 had some, and 204 none. Owing to the small number of municipalities with strong IMCI, the first two categories were merged and the outcome variable was dichotomous (any IMCI training versus no IMCI training). Data for 2000, derived from the National Demographic Census, were available on the following indicators,13 unless otherwise stated: human development index: calculated by the United Nations Development Programme office in Brazil;14 per capita monthly income: average household per capita monthly inv come (in Brazilian reais); literacy rate: percentage of individuv als aged 15 years or more who were literate. population: number of inhabitants; distance from the state capital in kiv lometres: distance by road between the seat of the municipality and the centre of the state capital; urbanization (%): percentage of inv dividuals living in urban areas; water supply (%): percentage of households with piped water inside the house; U5MR (per thousand), based on inv direct mortality estimates made availv • • • • • • • • able by the United Nations Developv ment Programme.14 These estimates refer to the midv1990s. Peru The ecological analyses combined inforv mation from the 34 health districts with data from the 24 departments (political divisions) of Peru, covering the period from 1996 to 2000. Indicators related to coverage of IMCI training were colv lected by the research team which visited all health districts.15,16 These data were reviewed for consistency and checked against information available at the Ministry of Health and at the United Nations Children’s Fund (UNICEF) and Pan American Health Organization (PAHO) country offices.15,16 Information from the 34 health districts was aggrev gated into 24 departments to match the geographical basis of information on explanatory variables. Because all health districts had started training of health workers, it was not possible to categorize IMCI implementation as a yes/no variable, as was done in Brazil. The outcome variable therefore was the percentage of doctors and nurses employed by the Ministry of Health in each department, who were trained on the clinical IMCI course, between 1996 and 2000. The following explanatory variables were obtained from official sources and from the 1996 and 2000 Demographic and Health Surveys17,18 and are defined as for Brazil, unless otherwise stated: human development index, 2000; 7 per capita gross departmental prodv uct (US$), 1996;19 literacy rate (%); population (number of inhabitants); • • • • distance from the national capital (Lima) in kilometres; urbanization (%); water supply (%): percentage of households with piped water inside the house, 1996;17 indirect U5MR estimate, ca 1995.18 Because of the small number of departv ments, we used a nonvparametric apv proach (Kruskal–Wallis test) to assess the associations between quartiles of the explanatory variables and training coverv age. Pearson correlation coefficients were also calculated. United Republic of Tanzania The United Republic of Tanzania was a global leader in IMCI implementav tion and the first districtvlevel training course took place in November 1996; by April 2004 half of all districts had started IMCI training, and when the present data were collected in mid 2005, only 14 (17%) districts had yet to start training. The data available in the United Republic of Tanzania were more limv ited than for Brazil or Peru. There are 118 districts in the country, of which 82 (69%) had complete information on child mortality, literacy and IMCI implementation date. Other indicators were available only for the 21 regions, each including two to six districts and having populations that ranged from approximately 300 000 to 2.5 million. Because data on coverage of IMCI training by district were not available, the variable representing IMCI uptake was the date of the first training course in each district. This was obtained through a review of records, and interviews with the national IMCI team that included • • • • 795Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. staff from the Ministry of Health and the WHO country office. Districts were then ordered according to the date of the first training course. The first district to start training was given the rank of “1,” and the analyses were based on these ranks. For regionalvlevel analyses, the outcome was the median rank, in terms of the date of the first training course, of all districts belonging to each region. All analyses were repeated using mean instead of median ranks and the results were virtually unchanged. The following explanatory variables were available at district level, based on the 2002 census,20 unless otherwise stated: literacy rate: percentage of the popuv lation aged 5 years or more who can read and write in at least one lanv guage; total population; distance from the largest city (Dar es Salaam) in kilometres, estimated usv ing a geographical information datav base (MapInfo Professional version 7.8); U5MR: deaths in children younger than 5 years per 1000 live births, esv timated from the 2002 census using indirect methods; the estimate is for the 5vyear period from 1995–99. All variables available at the district level were also available at the regional level. In addition, the following variables were available only at the regional level: human development index; 21 average annual contribution to the national GDP, expressed as a percentv age of the regional over the national GDP. 22 As regions varied in populav tion size, the ratio of this percentage to the percentage of the national population living in the region was calculated, and this variable is referred to as the “GDP/population ratio”; per capita income in Tanzanian shillings; 22 urbanization: percentage urban popuv lation; 22 water supply: percentage of the popuv lation with safe water. 21 Because the outcome was a ranked variv able, we used Spearman rank correlation coefficients in the analyses. Analyses were repeated using Pearson correlation and the results were virtually unchanged. Results For each country, we provide a brief history of IMCI implementation, folv • • • • • • • • • lowed by the statistical analyses of factors associated with its uptake. Brazil The IMCI introduction phase started with a meeting held in Brasília in March 1996. There was a broad consultative process involving staff from the Minv istry of Health, representatives from governmental and nongovernmental institutions, the Brazilian Society of Paev diatrics, public universities, and state and municipal health departments. Generic IMCI materials were adapted and trainv ing materials were prepared. The first training course took place in June 1997. At that time, the estiv mated infant mortality rate (IMR) in Table 2. Brazil: percentage of municipalities with Integrated Management of Childhood Illness (IMCI) according to quartiles of geographical, socio- economic and environmental variables, and to baseline mortality levels Variables (quartiles) Number Municipalities with IMCI (%) P-level Human development index 0.01a > 0.64 106 59.4 0.61–0.64 114 57.9 0.58–0.60 110 56.4 < 0.58 113 42.5 Per capita income (Brazilian reais) 0.02b > 91 111 66.7 78–91 111 52.2 67–77 111 46.8 < 67 110 50.0 Literacy rate (%) 0.59 b > 64 112 52.7 61–64 110 59.5 56–60 111 50.9 < 56 110 52.7 Population (inhabitants) < 0.001a 25 001–50 000 106 70.7 15 001–25 000 111 62.2 10 001–15 000 111 52.2 5 000–10 000 109 31.2 Distance from the state capital (km) < 0.001 b > 318 110 33.6 195–318 111 52.2 95–194 111 69.4 < 95 111 60.4 Urbanization (%) 0.46 b > 62 111 58.6 48–62 110 60.4 38–47 111 50.9 < 38 111 45.9 Water supply (%) 0.14 b > 46 110 58.2 36–46 112 58.0 26–35 110 44.5 < 26 111 54.9 U5MR c (per 1 000) 0.17 b > 93 112 49.1 77–93 105 49.5 64–76 116 62.1 < 64 110 54.5 a c² test for linear trend in proportions. b c² test for heterogeneity. c U5MR, mortality rate in children younger than 5 years. 796 Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. Table 3. Peru: mean Integrated Management of Childhood Illness (IMCI) training coverage by departments, according to quartiles of geographical, socioeconomic and environmental variables, and to baseline mortality Variables (quartiles) Number of departments Mean training coverage P-level a Human development index 0.19 > 0.66 6 8.3 0.59–0.66 6 26.7 0.51–0.58 6 24.2 < 0.51 6 20.6 Per capita gross departmental product (US dollars) 0.16 > 1 759 6 20.4 1 102–1759 6 9.0 707–1101 6 23.4 < 706 6 26.9 Literacy rate (%) 0.96 > 95 6 20.7 92–95 6 21.4 82–91 6 16.7 < 82 6 21.0 Population (inhabitants) 0.06 > 1 148 000 6 8.0 696 000–1 148 000 6 22.1 384 000–695 000 6 29.6 < 384 000 6 20.0 Distance from the state capital (km) 0.67 > 1 109 6 9.8 850–1109 6 13.5 422–849 6 14.7 < 422 6 12.0 Urbanization (%) 0.74 > 81 6 13.8 60–81 6 27.8 41–59 6 18.3 < 41 6 19.8 Water supply (%) 0.29 > 63 5 13.1 56–63 7 23.2 42–55 6 12.4 < 42 6 29.5 U5MRb (per 1 000) 0.69 > 93 6 25.6 81–93 6 20.7 59–80 6 15.8 < 59 6 17.7 a Kruskal–Wallis test. b U5MR, mortality rate in children younger than 5 years. Brazil was 34 per 1000. IMCI trainv ing was initially targeted at four of the country’s 27 states: Ceará, Pernambuco and Sergipe, in the northveast region (estimated IMRs in 1997 of 45, 54 and 49, respectively), and Pará state in the Amazon region (IMR, 32). Therefore, three of the four states where IMCI was initially implemented had a higher IMR than the national rate. These states were known for having strong vertical child health programmes, including Control of Diarrheal Diseases and Acute Respiv ratory Infections. Interviews with key informants confirmed that the presence of a strong health team at the state level was a prerequisite for inclusion in the early implementation phase. Training courses were rapidly exv panded to other states in the country, inv cluding those in the south and southveast where IMRs were below 20 per 1000. Nevertheless, training coverage in most states has remained very low. A detailed discussion of IMCI implementation is available elsewhere.23 The analysis presented in Table 2 covers 443 municipalities in three states leading in IMCI implementation in the northveast region (Ceará, Paraíba and Pernambuco). IMCI was less likely to be implemented in municipalities with low scores on the Human Development Index, low per capita income, small populations, and that were far from the state’s capital. Indicators of literacy, urbanization, water supply and baseline U5MR were not associated with IMCI implementation. Peru Peru was one of the first countries in the Americas to introduce IMCI, starting in 1996. Six districts were identified for the early implementation phase. Junin, Pasco and Huanuco were chosen because of high IMRs and high rates of acute rev spiratory infections, diarrhoeal diseases, malaria and malnutrition in children younger than 5 years.17 An additional criterion was that they were not being covered by other major health projects in progress at that time, such as the Proyecto Salud y Nutricion Basica and Proyecto 2000. The first of these projects was run by the Ministry of Health in collaboration with the World Bank, to modernize the health sector with the aim of improving quality of care and coverv age of primaryvlevel health services with a focus on maternal and child health and nutrition.24 The second project — Proyecto 2000 — was implemented by the Ministry of Health and USAID with the objective of improving the health and nutritional status of prevschool children and women of reproductive age through the promotion of utilization of maternal and perinatal health services, home care and healthy community practices.25 The other three earlyvimplementav tion districts — Ferreñafe in Lambayeque Department, Caylloma in Arequipa Department and Callao — were proposed by the staff in charge of the Programa de Salud Basica para Todos (PSBT).26 This Ministry of Health programme, which aimed at improving access to 797Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. health services and quality of health care, provided, at least initially, most of the funding for IMCI implementation. The PSBT officers chose Ferreñafe and Cailv loma because these were the poorest areas in their respective departments. Callao, one of the most advanced departments in terms of integrated health care and located just outside Lima, was chosen because it provided the opportunity for close followvup of IMCI implementav tion. By midv1997, a highvlevel decision at the Ministry of Health led to the incorporation of six additional districts (Andahuaylas, Ayacucho, Ica, Puno, Tacna and Ucayali), chosen because they were priority areas for Proyecto 2000. Of the 12 areas chosen for initial IMCI implementation, five (Apurimac, Ayacucho, Pasco, Puno and Ucayali) had IMRs above the national average of 58.3 per 1000 live births, whereas seven had mortality rates below the national average. By late 1996, 53 national facilitators had been trained in IMCI. As early as 1997, the Ministry of Health declared its commitment to expanding the strategy to all 34 health districts, but the rate of training of health workers fell well short of achieving this target.15,16 The rate of training peaked in 1999, and fell therev after. Details of IMCI implementation at district level in this period have been published elsewhere.15,16 Table 3 and Table 4 show the rev sults of the quantitative analyses. There were no significant associations between coverage of training and any of the inv dicators under study. Coverage tended to be somewhat lower in departments with higher values of the Human Develv opment Index, larger populations and poorer water supply. United Republic of Tanzania A detailed account of IMCI implev mentation in the United Republic of Tanzania is available elsewhere.27 The introductory phase started with a planning meeting in November 1995, at which the first IMCI national plan of action was prepared and seven “early use” districts were identified. These districts were intended to start IMCI implementation and provide lessons that could be used in expansion to the rest of the country. These districts were selected on the basis of four criteria: being easily accessible to the central level; the leadership skills of the District Medical Officer; existence of a functioning Control of Diarrhoeal Diseases Programme; and availability of a donor willing to support implementav tion. These districts, and the respective donors, were Morogoro and Rufiji (International Development Research Centre (IDRC)/United Republic of Tanzania Essential Health Interventions Project (TEHIP)), Muheza and Korogwe (Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ)), Igunga (World Bank), Mpwapwa (WHO) and Magu (UNICEF). The early implementation phase started in October 1996 and involved activities at the central level, including training of trainers who were then dev ployed in the seven earlyvuse districts. In June 1998, there was a desk review of initial implementation, and the expansion phase was launched. This involved the appointment of a fullv time National IMCI Coordinator and stepwise expansion of IMCI training to all facilities within the initial districts, to new districts within the same region and to new districts in other regions. The expansion phase also incorporated implementation of the other two IMCI components: strengthening of health systems and improving family and comv munity practices. Interviews with key informants at the national level suggest that implev mentation depended largely on the attitude of the individual district health management team, and rather less on the availability of a donor, and was unlikely to be associated with the level of sociov economic development. This view is supported by the data shown in Table 5. Owing to lack of Table 4. Pearson correlation coefficients (r) between the cumulative percentage of doctors and nurses trained in Integrated Management of Childhood Illness (IMCI) between 1996 and 2000 and explanatory variables (ca 1995), for the 24 departments of Perua Explanatory variable Pearson correlation coefficient (r) P-level Human development index –0.278 0.19 Per capita gross departmental product (US$) –0.140 0.51 Literacy rate (%) –0.096 0.66 Population (inhabitants) –0.294 0.16 Distance from the capital (km) –0.060 0.78 Urbanization (%) –0.024 0.91 Water supply (%) –0.309 0.14 U5MRb (per thousand) 0.169 0.43 a Positive coefficients indicate that IMCI was more strongly implemented in areas with high values of the explanatory variable. b U5MR, mortality rate in children younger than 5 years. data, fewer variables are available at the district than at the regional level. The only significant correlation was the earlier introduction of IMCI in districts that were close to Dar es Salaam. None of the other correlations, including that with baseline U5MR, were statistically significant. Discussion The strong inverse association between the geographical availability of health resources and measures of population need for health care is well recognized.28 Much less is known, however, about how new health programmes are spread out on a geographical basis, or about the factors associated with their uptake at district level. The present analyses have certain limitations. Detailed information on IMCI implementation, and particularly on coverage of training for health workv ers, was very difficult to obtain. In Brazil and Peru, this required repeated contacts with, and sometimes visits to, numerous administrative units, because there was no upvtovdate central registry of trainv ing coverage. In the United Republic of Tanzania, it was only possible to obtain information on the date of the first trainv ing course in each district — admittedly a poor proxy for training coverage. The countries for these analyses were selected from the five (Bangladesh, Brazil, Peru, Uganda and the United Republic of Tanzania) included in a multivcountry evaluation.6 However, in Bangladesh, IMCI was being implev mented only in one pilot district and in Uganda, data on IMCI introduction or 798 Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. Table 5. Spearman correlation coefficients (rho) between ranked dates of Integrated Management of Childhood Illness (IMCI) introduction and explanatory variables (ca 2000)a Explanatory variables Regional level analyses (n = 21)c District level analysesb (n = 82)d rho P rho P Human development index –0.021 0.93 – – GDP/population ratio 0.120 0.61 – – Per capita income 0.249 0.29 – – Urbanization (%) –0.114 0.63 – – Water supply (%) –0.168 0.48 – – Literacy rate (%) 0.011 0.97 –0.034 0.77 Population (inhabitants) –0.261 0.25 –0.149 0.20 Distance from Dar es Salaam (km) 0.271 0.25 0.244 0.03 U5MRe (per thousand) –0.007 .975 –0.112 0.32 a Data for 82 districts and 21 regions of the United Republic of Tanzania. Positive coefficients indicate that IMCI tended to be introduced later in areas with higher values of the explanatory variable. b Data not available. c Data were missing for up to six districts for one or more variables. d Data were missing for up to one region for one or more variables. e U5MR, mortality rate in children younger than 5 years. implementation in most districts were unavailable. Ideally a larger number of countries would have been included in this study. However, as noted above, few if any countries have information systems that routinely report on IMCI introduction or coverage, and obtaining the information used in these analyses was a timevconsuming effort. The need to develop a strong inforv mation system sidevbyvside with rolling out training activities is a priority for effective scaling up. Information on exv planatory variables, such as the Human Development Index, was also imposv sible to obtain in the United Republic of Tanzania, even at the regional level. Another drawback was that, except for in Brazil, the number of study units available for analyses was limited, resultv ing in relatively low statistical power for detecting significant associations. Also, several likely determinants of implemenv tation are hard to measure. For example, key informants in all countries menv tioned that motivation of the district health team was a major determinant of IMCI uptake. This important variable is difficult if not impossible to measure in largevscale studies. Use of the WHOvrecommended criteria for selecting districts for early implementation, as described in the first section of this paper, resulted in the selection of earlyvuse districts that were close to the national capital or main city, with a good track record in previous verv tical child health programmes, managed by motivated teams and with funding available. While this makes sense for the selection of earlyvuse districts, these characteristics are likely to be found in districts where the U5MRs are lower than the national average. The WHO guidelines did not identify mortality levels or population size as criteria for the selection of districts at this stage. These observations are being made with the benefit of hindsight. In practice, IMCI training materials were developed first,4 and implementation guidelines a few years later.7,8 The thinking of the global team in charge of IMCI development and implementation has evolved over time; there was a substantial time lag bev tween the development of new concepts and guidelines and their application at country level and below. IMCI should not be singled out as the only strategy without explicit provequity implementation guidelines. Antenatal and delivery care, immuniv zations and many other child survival interventions are inequitably distributed within lowv and middlevincome counv tries.28–30 Vaccination initiatives have recently incorporated the “reach every district” approach to achieve universal coverage and thereby reduce inequities;31 countries are being encouraged to focus first on lowvcoverage districts, which will often be the poorest. The need to match delivery of child survival interventions with population health needs in a geov graphical area is also reflected in the programme management guidelines for child survival, which WHO is currently developing.32 In spite of the lack of specific recomv mendations regarding equity, in both Brazil and Peru — but not in the United Republic of Tanzania — nationalvlevel IMCI planners partially addressed equity concerns when selecting earlyvuse districts. In Brazil, three of the four states initially selected were in the area of the country with the highest mortality rate; however, the two states with the highest mortality rates, Alagoas and Maranhão, were not included. In Peru, as described above, there was also an attempt at targeting health districts with high death rates. The statistical analyses presented in Tables 2–5 go beyond the earlyvuse districts, to reveal which administrative units were most likely to take up IMCI during the expansion phase. In Brazil, these are not the same types of geov graphical units (states) as were included in the early phase, but represent the spread to municipalities within three states. Because decentralization is an ongoing process in the three countries under study, districts or municipalities were reasonably independent in their adoption of new strategies such as IMCI, and the influence of the nationalv (or in Brazil, statev) level administration was relatively limited. Unfortunately, it was not possible to obtain comparable data on all exv planatory factors under study. In Brazil, IMCI was less likely to be implemented by poor and small municipalities, and by those that were distant from the state capital. The association with population size in Brazil may be, at least in part, artefactual: larger cities have more health workers and there is thus a greater chance that at least one of them would have been trained in IMCI. Key informants mentioned that small and remote municipalities were less likely to have qualified workers because most training took place in the capital, and because these municipalities were not willing to release one of their few health workers (sometimes the only one) for the extended period necessary for the training. Other informants also mentioned that IMCIvtrained health workers were more likely to get jobs in larger and wealthier municipalities; it was even mentioned that some mayors were unwilling to allow their workers to be trained because this would lead to their eventual departure. 799Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. Résumé Les interventions sanitaires sont-elles mises en œuvre là où elles sont le plus nécessaires ? Application à l’échelle du district de la Prise en charge intégrée des maladies de l’enfant au Brésil, au Pérou et en République unie de Tanzanie Objectif Décrire comment se répartit géographiquement l’application de la Prise en charge intégrée des maladies de l’enfant (IMCI) dans trois pays et déterminer si cette stratégie est mise en œuvre dans les zones où les besoins des enfants sont les plus pressants. Méthodes Nous avons mené des entretiens avec des informateurs clés aux niveaux du pays et du district, au Brésil, au Pérou et en République unie de Tanzanie, ainsi qu’une étude écologique des facteurs intervenant dans la formation à l’IMCI des agents de santé. Parmi ces facteurs, figuraient la population du district, la distance par rapport à la capitale, l’indice de développement humain et d’autres indicateurs socioéconomiques, ainsi que les taux de mortalité de référence chez les enfants de moins de cinq ans. Résultats Conformément aux recommandations de l’OMS, les districts ayant bénéficié précocement de la mise en œuvre de l’IMCI présentaient les caractéristiques suivantes : proximité avec la capitale, disponibilité de sites de formation appropriés, présence de cadres sanitaires motivés et d’un système de santé opérationnel. Dans la phase d’expansion, l’IMCI a été préférentiellement adoptée par des districts présentant des caractéristiques similaires. Au Brésil, sa mise en œuvre par les municipalités pauvres ou de faible importance et par celles situées à plus grande distance de la capitale de l’État était nettement plus limitée. Au Pérou, aucune association entre la distance à Lima et le taux de mise en œuvre n’a été constatée et une tendance non significative à l’adoption de l’IMCI par des services de faible importance et disposant de ressources limitées a été relevée. Pour la République unie de Tanzanie, le seul résultat statistiquement significatif était une moindre mise en œuvre dans les districts isolés. On n’a relevé d’association entre la mise en œuvre de cette stratégie et les taux de mortalité de référence dans aucun des pays étudiés. Conclusion Si des directives claires et raisonnables ont été fournies pour la sélection des districts devant bénéficier parmi les premiers de l’IMCI, aucun critère pour guider l’élargissement de cette stratégie n’a été publié et aucun classement par priorité des zones où s’expriment les plus grands besoins n’a été établi. Des analyses sur le plan de l’équité du déploiement géographique des stratégies et programmes récents pourraient aider à déterminer si ces interventions atteignent ceux qui en ont le plus besoin. In Peru, coverage of IMCI training was not significantly associated with any of the indicators under study, but tended to be somewhat higher in poorer and smaller departments, and in those with lower coverage of safe water supply. This may reflect the tendency, mentioned by the key informants, to target IMCI at the poorest districts. Finally, in the United Republic of Tanzania the only significant finding at the district level was the delayed introduction of IMCI in remote disv tricts. A similar but nonvsignificant association was found in the regionalv level analyses. In a perfect world, IMCI would be more strongly implemented in districts with high U5MRs and lower standards of living, and among these, priority would be given to districts with a large populav tion of children younger than five years old. This was not the case in any of the three countries studied. In Brazil, there was a weak, nonvsignificant inverse assov ciation — in fact, IMCI implementation at municipal level tended to be provrich rather than provpoor. In Peru, implev mentation was slightly provpoor, but no significant associations were present. In the United Republic of Tanzania, there were no clear patterns but, as in Brazil, distance from the main city was inversely associated with implementation. When data from the interviews with key informants are compared, the need to prioritize poor districts with higher mortality was mentioned quite often in Peru, to a certain extent in Brazil, and less so in the United Republic of Tanzania. When 124 countries with available data were ranked in ascending order of income inequality in 2005, the United Republic of Tanzania was considerably more equitable (ranked 64th) than Peru (ranked 100th) or Brazil (ranked 117th).33 The existence of wider inequalities in South America is supported by additional results from the present analyses. The correlation coefficients for the literacy and U5MR indicators were –0.710 (P < 0.001) in Peru; –0.454 (P < 0.001) in Brazil; and –0.280 (P = 0.23) in the United Republic of Tanzania, all suggesting inverse asv sociations, although less strong in the United Republic of Tanzania. This may explain why greater attention — at least at the discourse level — is given to inequalities in the two South American countries. For example, Peru introduced Haemophilus influenzae type b vaccine in 1998 in the high mortality departments, whereas the vaccine was only introduced in the more developed areas in 2004 when high coverage had already been reached in the initial implementation departments.34 Until recently, equity considerations were seldom addressed in international child health initiatives aimed at lowv and middlevincome countries.29 Results from the present analyses show that criteria for selecting districts for the early implev mentation phase of IMCI — which are somewhat provrich — need to be counv terbalanced by provpoor criteria for the expansion phase. WHO should work tov gether with countries to guide selection of the districts in which programmes and strategies are deployed, to ensure that highvrisk geographical areas are not left behind. Admittedly, this is easier said than done, but unless provactive efforts are made to deploy interventions where they are most needed, inequalities in child health may widen as a result of new programmes. O Acknowledgements This work is part of the MultivCountry Evaluation of IMCI Effectiveness, Cost and Impact, coordinated by the Departv ment of Child and Adolescent Health and Development of the World Health Organization, and supported by the Bill and Melinda Gates Foundation. We are particularly thankful to our colleagues from the United Republic of Tanzania (Conrad Mbuya, Leslie Mgalula, Don de Savigny, Nemes Iriya and Neema Rusibamayila), Brazil (Ana Goretti Maranhão, Antonio Cunha and Alvaro Leite) and Peru (Miguel Davila) for their contributions to data collection. Competing interests: none declared. 800 Bulletin of the World Health Organization | October 2006, 84 (10) Research Uptake of IMCI in three countries CG Victora et al. Resumen ¿Se implementan las intervenciones sanitarias donde más se necesitan? Implantación distrital de la estrategia de Atención Integrada a las Enfermedades Prevalentes de la Infancia en el Brasil, el Perú y la República Unida de Tanzanía Objetivo Describir la distribución geográfica de la implementación de la estrategia de Atención Integrada a las Enfermedades Prevalentes de la Infancia (AIEPI) en tres países y evaluar si dicha estrategia se aplicaba en las zonas donde más acuciantes eran las necesidades de salud infantil. Métodos Realizamos entrevistas con informantes clave a nivel nacional y distrital en el Brasil, el Perú y la República Unida de Tanzanía, así como un estudio ecológico de los factores asociados a la formación de los trabajadores sanitarios en materia de AIEPI. Entre los factores explicativos figuraban la población del distrito, la distancia hasta la capital, el índice de desarrollo humano, otros indicadores socioeconómicos y las tasas de mortalidad basales de los menores de cinco años. Resultados En consonancia con las recomendaciones de la OMS, los distritos de implementación temprana se caracterizaban por que estaban cerca de la capital y disponían de centros de formación idóneos, de administradores sanitarios motivados y de un sistema de salud operativo. En la fase de expansión, la AIEPI solía ser adoptada por otros distritos de características similares. En el Brasil, la implantación en los municipios más pobres y pequeños y en los más alejados de la capital del Estado fue significativamente menor. En el Perú no se observó ninguna relación con la distancia a Lima, y la tendencia de adopción de la AIEPI por los departamentos pequeños y pobres no era significativa. En la República Unida de Tanzanía, el único dato estadísticamente relevante fue la menor implantación en los distritos alejados. La implementación no se asoció a niveles de mortalidad basal en ninguno de los países estudiados. Conclusión Si bien se facilitan directrices claras y razonables para la selección de los distritos de implementación temprana, no se suministraron criterios para promover la expansión de la AIEPI, y no se priorizaron las áreas más necesitadas. Los análisis de la equidad basados en el despliegue geográfico de nuevos programas y estrategias pueden ser una ayuda para evaluar si se está llegando o no a quienes más los necesitan. صخلم ؟اهل ًاجايتحا ثركلأا عقاولما في ةيحصلا تلا ُّخدتلا تذ ِّفُن له ةدحتلما اينازنت ةيروهمجو ويربلاو ليزابرلا في ةلوفطلا ضارملأ لماكتلما يربدتلا ةيجيتارـتسا ذ ِّفنت قطانلما ضارملأ لماكتلما يربدتلا ةيجيتارـتسا ذيفنت طانملأ ٌفيارغج فصو :فدهلا في تذ ِّفُن دق ةيجيتارـتسلاا هذه تناك اذإ ام ميـيقت عم ،نادلب ةثلاث في ةلوفطلا .لافطلأا ةحصل ًاجايتحا عقاولما ثركأ لىعو ينطولا ىوتسلما لىع ينـِّيسيئرلا ينـِّينعلما عم تلاباقم انيرجأ :ةقيرطلا ،ةدحتلما اينازنت ةيروهمجو ويربلاو ليزابرلا نم ٍّلك في تاعطاقلما ىوتسم لىع ينـِّيحصلا ينلماعلا بيردت تقفار يتلا لماوعلل ةيئيب ةسارد بناج لىإ ةييرسفتلا لماوعلا تلمتشا دقو .ةلوفطلا ضارملأ لماكتلما يربدتلا ةيجيتارـتسا ةيشربلا ةيمنتلا بَسْنَمو ،ةمصاعلا نع اهِدْعُبو ،ةعطاقلما ناكس ددع لىع لافطلأا ىدل تايفولل ةيساسلأا تلادعلماو ىرخأ ةيداصتقاو ةيعماتجا تا ِّشؤمو .تاونس سمخ نود رمعب ةذ ِّفنلما تاعطاقلما تناك ،ةيجيتارـتسلاا ذيفنتل ةركابلا ةلحرلما في :تادوجولما نيريدبم عَّتمتـتو ،ةئملام ةيبيردت عقاوبم عَّتمتـت يتلاو ،ةمصاعلل برقلأا يه اهل شىماتـت صئاصخلا هذهو ،لا َّعف يحص ماظنب عَّتمتـتو ،زفاوحلاب نومعني ينـِّيحص تاعطاقلما تلام ،ذيفنتلاب ع ُّسوتلا ةلحرم فيو .ةيلماعلا ةحصلا ةمظنم تايصوت عم .ةلوفطلا ضارملأ لماكتلما يربدتلا ةيجيتارـتسا يِّنبتل ةهباشم صئاصخ اهيدل يتلا ةيرقفلاو ةيرغصلا تايدلبلا ىدل يرثكب لقأ ةيجيتارـتسلاا ذيفنت ناك ليزابرلا فيو تاعطاقلما دعُب ينب ةقلاع ةيأ كانه نكي لم ويربلا فيو .ةمصاعلا نع ةديعبلاو ةيرغصلا وأ ةيرقفلا تايريدلما ِدْبُت لمو ،ةيجيتارـتسلاا ذيفنت ينبو مايل ةمصاعلا نع ةيروهمج في امأ .ةلوفطلا ضارملأ لماكتلما يربدتلا ةيجيتارـتساب ًاظوحلم ًامماتها ةيئاصحلإا ةيمهلأا تاذ تادوجولما ينب نم طقف ةدحاو نإف ةدحتلما اينازنت قفاتري لمو .ةديعبلا تاعطاقلما في ةيجيتارـتسلاا ذيفنت ىوتسم ضافخنا تناك نم يأ في تايفولا تلادعلم ةيساسلأا تايوتسملل قيثوتب ةيجيتارـتسلاا ذيفنت .ةسوردلما ثلاثلا نادلبلا ذ ِّفنت يتلا تاعطاقلما رايتخلا ةحضاوو ةلوقعم ةيداشرإ لئلاد رفاوت مغر :جاتنتسلاا ،ةيجيتارـتسلاا هذه عيسوت زيزعتل تايطعم ةيأ كانه سيل هنإف ،ًاركاب ةيجيتارـتسلاا ةلادعلاو ةاواسلما ليلحتل نكيمو .ًاجايتحا ثركلأا ةيولولأا تاذ قطانلما ح َّضوت لمو تناك اذإ ام ميـيقت في مهاسي نأ ةديدجلا جمابرلل فيارغجلا راشتنلاا لىع زِكَْترُمـلا .اهيلإ ةجاح ثركلأا مه نلم حاتُت تايجيتارـتسلااو جمابرلا هذه References 1. 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