Differences between gridded population data impact measures of geographic access to healthcare in sub-Saharan Africa.

Background: Access to healthcare is imperative to health equity and well-being. Geographic access to healthcare can be modeled using spatial datasets on local context, together with the distribution of existing health facilities and populations. Several population datasets are currently available, but their impact on accessibility analyses is unknown. In this study, we model the geographic accessibility of public health facilities at 100-meter resolution in sub-Saharan Africa and evaluate six of the most popular gridded population datasets for their impact on coverage statistics at different administrative levels. Methods: Travel time to nearest health facilities was calculated by overlaying health facility coordinates on top of a friction raster accounting for roads, landcover, and physical barriers. We then intersected six different gridded population datasets with our travel time estimates to determine accessibility coverages within various travel time thresholds (i.e., 30, 60, 90, 120, 150, and 180-min). Results: Here we show that differences in accessibility coverage can exceed 70% at the sub-national level, based on a one-hour travel time threshold. The differences are most notable in large and sparsely populated administrative units and dramatically shape patterns of healthcare accessibility at national and sub-national levels. Conclusions: The results of this study show how valuable and critical a comparative analysis between population datasets is for the derivation of coverage statistics that inform local policies and monitor global targets. Large differences exist between the datasets and the results underscore an essential source of uncertainty in accessibility analyses that should be systematically assessed.

Optimising scale and deployment of community health workers in Sierra Leone: a geospatial analysis.

BACKGROUND: Little is known about strategies for optimising the scale and deployment of community health workers (CHWs) to maximise geographic accessibility of primary healthcare services. METHODS: We used data from a national georeferenced census of CHWs and other spatial datasets in Sierra Leone to undertake a geospatial analysis exploring optimisation of the scale and deployment of CHWs, with the aim of informing implementation of current CHW policy and future plans of the Ministry of Health and Sanitation. RESULTS: The per cent of the population within 30 min walking to the nearest CHW with preservice training increased from 16.1% to 80.4% between 2000 and 2015. Contrary to current national policy, most of this increase occurred in areas within 3 km of a health facility where nearly two-thirds (64.5%) of CHWs were deployed. Ministry of Health and Sanitation-defined 'easy-to-reach' and 'hard-to-reach' areas, geographic areas that should be targeted for CHW deployment, were less well covered, with 19.2% and 34.6% of the population in 2015 beyond a 30 min walk to a CHW, respectively. Optimised CHW networks in these areas were more efficiently deployed than existing networks by 22.4%-71.9%, depending on targeting metric. INTERPRETATIONS: Our analysis supports the Ministry of Health and Sanitation plan to rightsize and retarget the CHW workforce. Other countries in sub-Saharan Africa interested in optimising the scale and deployment of their CHW workforce in the context of broader human resources for health and health sector planning may look to Sierra Leone as an exemplar model from which to learn.

Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis.

Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so. We used geospatial analysis to model optimised scale-up and deployment of CHWs in Mali, to inform strategic and operational planning by the Ministry of Health and Social Development. Accessibility catchments were modelled based on travel time, accounting for barriers to movement. We compared geographic coverage of the estimated population, under-five deaths, and plasmodium falciparum (Pf) malaria cases across different hypothetical optimised CHW networks and identified surpluses and deficits of CHWs compared to the existing CHW network. A network of 15 843 CHW, if optimally deployed, would ensure that 77.3% of the population beyond 5 km of the CSCom (community health centre) and CSRef (referral health facility) network would be within a 30-minute walk of a CHW. The same network would cover an estimated 59.5% of U5 deaths and 58.5% of Pf malaria cases. As an intermediary step, an optimised network of 4 500 CHW, primarily filling deficits of CHW in the regions of Kayes, Koulikoro, Sikasso, and Ségou would ensure geographic coverage for 31.3% of the estimated population. There were no important differences in geographic coverage percentage when prioritizing CHW scale-up and deployment based on the estimated population, U5 deaths, or Pf malaria cases. Our geospatial analysis provides useful information to policymakers and planners in Mali for optimising the scale-up and deployment of CHW and, in turn, for maximizing the value-for-money of resources of investment in CHWs in the context of the country's health sector reform. Countries with similar interests in optimising the scale and deployment of their CHW workforce may look to Mali as an exemplar model from which to learn.

Optimising geographical accessibility to primary health care: a geospatial analysis of community health posts and community health workers in Niger.

BACKGROUND: Little is known about the contribution of community health posts and community health workers (CHWs) to geographical accessibility of primary healthcare (PHC) services at community level and strategies for optimising geographical accessibility to these services. METHODS: Using a complete georeferenced census of community health posts and CHWs in Niger and other high-resolution spatial datasets, we modelled travel times to community health posts and CHWs between 2000 and 2013, accounting for training, commodities and maximum population capacity. We estimated additional CHWs needed to optimise geographical accessibility of the population beyond the reach of the existing community health post network. We assessed the efficiency of geographical targeting of the existing community health post network compared with networks designed to optimise geographical targeting of the estimated population, under-5 deaths and Plasmodium falciparum malaria cases. RESULTS: The per cent of the population within 60-minute walking to the nearest community health post with a CHW increased from 0.0% to 17.5% between 2000 and 2013. An estimated 10.4 million people (58.5%) remained beyond a 60-minute catchment of community health posts. Optimal deployment of 7741 additional CHWs could increase geographical coverage from 41.5% to 82.9%. Geographical targeting of the existing community health post network was inefficient but optimised networks could improve efficiency by 32.3%-47.1%, depending on targeting metric. INTERPRETATIONS: We provide the first estimates of geographical accessibility to community health posts and CHWs at national scale in Niger, highlighting improvements between 2000 and 2013, geographies where gaps remained and approaches for optimising geographical accessibility to PHC services at community level.

Integrated community case management of childhood illness in low- and middle-income countries.

BACKGROUND: The leading causes of mortality globally in children younger than five years of age (under-fives), and particularly in the regions of sub-Saharan Africa (SSA) and Southern Asia, in 2018 were infectious diseases, including pneumonia (15%), diarrhoea (8%), malaria (5%) and newborn sepsis (7%) (UNICEF 2019). Nutrition-related factors contributed to 45% of under-five deaths (UNICEF 2019). World Health Organization (WHO) and United Nations Children's Fund (UNICEF), in collaboration with other development partners, have developed an approach - now known as integrated community case management (iCCM) - to bring treatment services for children 'closer to home'. The iCCM approach provides integrated case management services for two or more illnesses - including diarrhoea, pneumonia, malaria, severe acute malnutrition or neonatal sepsis - among under-fives at community level (i.e. outside of healthcare facilities) by lay health workers where there is limited access to health facility-based case management services (WHO/UNICEF 2012). OBJECTIVES: To assess the effects of the integrated community case management (iCCM) strategy on coverage of appropriate treatment for childhood illness by an appropriate provider, quality of care, case load or severity of illness at health facilities, mortality, adverse events and coverage of careseeking for children younger than five years of age in low- and middle-income countries. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase and CINAHL on 7 November 2019, Virtual Health Library on 8 November 2019, and Popline on 5 December 2018, three other databases on 22 March 2019 and two trial registers on 8 November 2019. We performed reference checking, and citation searching, and contacted study authors to identify additional studies. SELECTION CRITERIA: Randomized controlled trials (RCTs), cluster-RCTs, controlled before-after studies (CBAs), interrupted time series (ITS) studies and repeated measures studies comparing generic WHO/UNICEF iCCM (or local adaptation thereof) for at least two iCCM diseases with usual facility services (facility treatment services) with or without single disease community case management (CCM). We included studies reporting on coverage of appropriate treatment for childhood illness by an appropriate provider, quality of care, case load or severity of illness at health facilities, mortality, adverse events and coverage of careseeking for under-fives in low- and middle-income countries. DATA COLLECTION AND ANALYSIS: At least two review authors independently screened abstracts, screened full texts and extracted data using a standardised data collection form adapted from the EPOC Good Practice Data Collection Form. We resolved any disagreements through discussion or, if required, we consulted a third review author not involved in the original screening. We contacted study authors for clarification or additional details when necessary. We reported risk ratios (RR) for dichotomous outcomes and hazard ratios (HR) for time to event outcomes, with 95% confidence intervals (CI), adjusted for clustering, where possible. We used estimates of effect from the primary analysis reported by the investigators, where possible. We analysed the effects of randomized trials and other study types separately. We used the GRADE approach to assess the certainty of evidence. MAIN RESULTS: We included seven studies, of which three were cluster RCTs and four were CBAs. Six of the seven studies were in SSA and one study was in Southern Asia. The iCCM components and inputs were fairly consistent across the seven studies with notable variation for the training and deployment component (e.g. on payment of iCCM providers) and the system component (e.g. on improving information systems). When compared to usual facility services, we are uncertain of the effect of iCCM on coverage of appropriate treatment from an appropriate provider for any iCCM illness (RR 0.96, 95% CI 0.77 to 1.19; 2 CBA studies, 5898 children; very low-certainty evidence). iCCM may have little to no effect on neonatal mortality (HR 1.01, 95% 0.73 to 1.28; 2 trials, 65,209 children; low-certainty evidence). We are uncertain of the effect of iCCM on infant mortality (HR 1.02, 95% CI 0.83 to 1.26; 2 trials, 60,480 children; very low-certainty evidence) and under-five mortality (HR 1.18, 95% CI 1.01 to 1.37; 1 trial, 4729 children; very low-certainty evidence). iCCM probably increases coverage of careseeking to an appropriate provider for any iCCM illness by 68% (RR 1.68, 95% CI 1.24 to 2.27; 2 trials, 9853 children; moderate-certainty evidence). None of the studies reported quality of care, severity of illness or adverse events for this comparison. When compared to usual facility services plus CCM for malaria, we are uncertain of the effect of iCCM on coverage of appropriate treatment from an appropriate provider for any iCCM illness (very low-certainty evidence) and iCCM may have little or no effect on careseeking to an appropriate provider for any iCCM illness (RR 1.06, 95% CI 0.97 to 1.17; 1 trial, 811 children; low-certainty evidence). None of the studies reported quality of care, case load or severity of illness at health facilities, mortality or adverse events for this comparison. AUTHORS' CONCLUSIONS: iCCM probably increases coverage of careseeking to an appropriate provider for any iCCM illness. However, the evidence presented here underscores the importance of moving beyond training and deployment to valuing iCCM providers, strengthening health systems and engaging community systems.

Are monitoring and evaluation systems adequate to report the programmatic coverage of HIV services among key populations in countries?

There was no global guidance or agreement regarding when a country has an adequate system to report on the service packages among human immunodeficiency virus (HIV) key populations. This article describes an approach to categorizing the system in a country for reporting the service package among HIV key populations. The approach consists of four dimensions, namely the epidemiological significance, comprehensiveness of the service packages, geographic coverage of services, and adequacy of the monitoring system. The proposed categorization approach utilizes available information and can inform the improvement of the service delivery and monitoring systems among HIV key populations.

Global implementation survey of Integrated Management of Childhood Illness (IMCI): 20 years on.

OBJECTIVE: To assess the extent to which Integrated Management of Childhood Illness (IMCI) has been adopted and scaled up in countries. SETTING: The 95 countries that participated in the survey are home to 82% of the global under-five population and account for 95% of the 5.9 million deaths that occurred among children less than 5 years of age in 2015; 93 of them are low-income and middle-income countries (LMICs). METHODS: We conducted a cross-sectional self-administered survey. Questionnaires and data analysis focused on (1) giving a general overview of current organisation and financing of IMCI at country level, (2) describing implementation of IMCI's three original components and (3) reporting on innovations, barriers and opportunities for expanding access to care for children. A single data file was created using all information collected. Analysis was performed using STATA V.11. PARTICIPANTS: In-country teams consisting of representatives of the ministry of health and country offices of WHO and Unicef. RESULTS: Eighty-one per cent of countries reported that IMCI implementation encompassed all three components. Almost half (46%; 44 countries) reported implementation in 90% or more districts as well as all three components in place (full implementation). These full-implementer countries were 3.6 (95% CI 1.5 to 8.9) times more likely to achieve Millennium Development Goal 4 than other (not full implementer) countries. Despite these high reported implementation rates, the strategy is not reaching the children who need it most, as implementation is lowest in high mortality countries (39%; 7/18). CONCLUSION: This survey provides a unique opportunity to better understand how implementation of IMCI has evolved in the 20 years since its inception. Results can be used to assist in formulating strategies, policies and activities to support improvements in the health and survival of children and to help achieve the health-related, post-2015 Sustainable Development Goals.

Correction: Evaluation of a community-based intervention to improve maternal and neonatal health service coverage in the most rural and remote districts of Zambia.

[This corrects the article DOI: 10.1371/journal.pone.0190145.].

Evaluation of a community-based intervention to improve maternal and neonatal health service coverage in the most rural and remote districts of Zambia.

BACKGROUND: A community-based intervention comprising both men and women, known as Safe Motherhood Action Groups (SMAGs), was implemented in four of Zambia's poorest and most remote districts to improve coverage of selected maternal and neonatal health interventions. This paper reports on outcomes in the coverage of maternal and neonatal care interventions, including antenatal care (ANC), skilled birth attendance (SBA) and postnatal care (PNC) in the study areas. METHODOLOGY: Three serial cross-sectional surveys were conducted between 2012 and 2015 among 1,652 mothers of children 0-5 months of age using a 'before-and-after' evaluation design with multi-stage sampling, combining probability proportional to size and simple random sampling. Logistic regression and chi-square test for trend were used to assess effect size and changes in measures of coverage for ANC, SBA and PNC during the intervention. RESULTS: Mothers' mean age and educational status were non-differentially comparable at all the three-time points. The odds of attending ANC at least four times (aOR 1.63; 95% CI 1.38-1.99) and SBA (aOR 1.72; 95% CI 1.38-1.99) were at least 60% higher at endline than baseline surveillance. A two-fold and four-fold increase in the odds of mothers receiving PNC from an appropriate skilled provider (aOR 2.13; 95% CI 1.62-2.79) and a SMAG (aOR 4.87; 95% CI 3.14-7.54), respectively, were observed at endline. Receiving birth preparedness messages from a SMAG during pregnancy (aOR 1.76; 95% CI, 1.20-2.19) and receiving ANC from a skilled provider (aOR 4.01; 95% CI, 2.88-5.75) were significant predictors for SBA at delivery and PNC. CONCLUSIONS: Strengthening community-based action groups in poor and remote districts through the support of mothers by SMAGs was associated with increased coverage of maternal and newborn health interventions, measured through ANC, SBA and PNC. In remote and marginalised settings, where the need is greatest, context-specific and innovative task-sharing strategies using community health volunteers can be effective in improving coverage of maternal and neonatal services and hold promise for better maternal and child survival in poorly-resourced parts of sub-Saharan Africa.

Costs of implementing integrated community case management (iCCM) in six African countries: implications for sustainability.

BACKGROUND: Sub-Saharan Africa still reports the highest rates of under-five mortality. Low cost, high impact interventions exist, however poor access remains a challenge. Integrated community case management (iCCM) was introduced to improve access to essential services for children 2-59 months through diagnosis, treatment and referral services by community health workers for malaria, pneumonia and diarrhea. This paper presents the results of an economic analysis of iCCM implementation in regions supported by UNICEF in six countries and assesses country-level scale-up implications. The paper focuses on costs to provider (health system and donors) to inform planning and budgeting, and does not cover cost-effectiveness. METHODS: The analysis combines annualised set-up costs and 1 year implementation costs to calculate incremental economic and financial costs per treatment from a provider perspective. Affordability is assessed by calculating the per capita financial cost of the program as a percentage of the public health expenditure per capita. Time and financial implications of a 30% increase in utilization were modeled. Country scale-up is modeled for all children under 5 in rural areas. RESULTS: Utilization of iCCM services varied from 0.05 treatment/y/under-five in Ethiopia to over 1 in Niger. There were between 10 and 603 treatments/community health worker (CHW)/y. Consultation cost represented between 93% and 22% of economic costs per treatment influenced by the level of utilization. Weighted economic cost per treatment ranged from US$ 13 (2015 USD) in Ghana to US$ 2 in Malawi. CHWs spent from 1 to 9 hours a week on iCCM. A 30% increase in utilization would add up to 2 hours a week, but reduce cost per treatment (by 20% in countries with low utilization). Country scale up would amount to under US$ 0.8 per capita total population (US$ 0.06-US$0.74), between 0.5% and 2% of public health expenditure per capita but 8% in Niger. CONCLUSIONS: iCCM addresses unmet needs and impacts on under 5 mortality. An economic cost of under US$ 1/capita/y represents a sound investment. Utilization remains low however, and strategies must be developed as a priority to improve demand. Continued donor support is required to sustain iCCM services and strengthen its integration within national health systems.

Does adjusting for recall in trend analysis affect coverage estimates for maternal and child health indicators? An analysis of DHS and MICS survey data.

BACKGROUND: The Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) are the major data sources in low- and middle-income countries (LMICs) for evaluating health service coverage. For certain maternal and child health (MCH) indicators, the two surveys use different recall periods: 5 years for DHS and 2 years for MICS. OBJECTIVE: We explored whether the different recall periods for DHS and MICS affect coverage trend analyses as well as missing data and coverage estimates. DESIGNS: We estimated coverage, using proportions with 95% confidence intervals, for four MCH indicators: intermittent preventive treatment of malaria in pregnancy, tetanus vaccination, early breastfeeding and postnatal care. Trends in coverage were compared using data from 1) standard 5-year DHS and 2-year MICS recall periods (unmatched) and 2) DHS restricted to 2-year recall to match the MICS 2-year recall periods (matched). Linear regression was used to explore the relationship between length of recall, missing data and coverage estimates. RESULTS: Differences in coverage trends were observed between matched and unmatched data in 7 of 18 (39%) comparisons performed. The differences were in the direction of the trend over time, the slope of the coverage change or the significance levels. Consistent trends were seen in 11 of the 18 (61%) comparisons. Proportion of missing data was inversely associated with coverage estimates in both short (2 years) and longer (5 years) recall of the DHS (r=-0.3, p=0.02 and r=-0.4, p=0.004, respectively). The amount of missing information was increased for longer recall compared with shorter recall for all indicators (significant odds ratios ranging between 1.44 and 7.43). CONCLUSIONS: In a context where most LMICs are dependent on population-based household surveys to derive coverage estimates, users of these types of data need to ensure that variability in recall periods and the proportion of missing data across data sources are appropriately accounted for when trend analyses are conducted.

Niger's Child Survival Success, Contributing Factors and Challenges to Sustainability: A Retrospective Analysis.

BACKGROUND: Household surveys undertaken in Niger since 1998 have revealed steady declines in under-5 mortality which have placed the country 'on track' to reach the fourth Millennium Development goal (MDG). This paper explores Niger's mortality and health coverage data for children under-5 years of age up to 2012 to describe trends in high impact interventions and the resulting impact on childhood deaths averted. The sustainability of these trends are also considered. METHODS AND FINDINGS: Estimates of child mortality using the 2012 Demographic and Health Survey were developed and maternal and child health coverage indicators were calculated over four time periods. Child survival policies and programmes were documented through a review of documents and key informant interviews. The Lives Saved Tool (LiST) was used to estimate the number of child lives saved and identify which interventions had the largest impact on deaths averted. The national mortality rate in children under-5 decreased from 286 child deaths per 1000 live births (95% confidence interval 177 to 394) in the period 1989-1990 to 128 child deaths per 1000 live births in the period 2011-2012 (101 to 155), corresponding to an annual rate of decline of 3.6%, with significant declines taking place after 1998. Improvements in the coverage of maternal and child health interventions between 2006 and 2012 include one and four or more antenatal visits, maternal Fansidar and tetanus toxoid vaccination, measles and DPT3 vaccinations, early and exclusive breastfeeding, oral rehydration salts (ORS) and proportion of children sleeping under an insecticide-treated bed net (ITN). Approximately 26,000 deaths of children under-5 were averted in 2012 due to decreases in stunting rates (27%), increases in ORS (14%), the Hib vaccine (14%), and breastfeeding (11%). Increases in wasting and decreases in vitamin A supplementation negated some of those gains. Care seeking at the community level was responsible for an estimated 7,800 additional deaths averted in 2012. A major policy change occurred in 2006 enabling free health care provision for women and children, and in 2008 the establishment of a community health worker programme. CONCLUSION: Increases in access and coverage of care for mothers and children have averted a considerable number of childhood deaths. The 2006 free health care policy and health post expansion were paramount in reducing barriers to care. However the sustainability of this policy and health service provision is precarious in light of persistently high fertility rates, unpredictable GDP growth, a high dependence on donor support and increasing pressures on government funding.

Assessment of Malawi's success in child mortality reduction through the lens of the Catalytic Initiative Integrated Health Systems Strengthening programme: Retrospective evaluation.

BACKGROUND: Malawi is estimated to have achieved its Millennium Development Goal (MDG) 4 target. This paper explores factors influencing progress in child survival in Malawi including coverage of interventions and the role of key national policies. METHODS: We performed a retrospective evaluation of the Catalytic Initiative (CI) programme of support (2007-2013). We developed estimates of child mortality using four population household surveys undertaken between 2000 and 2010. We recalculated coverage indicators for high impact child health interventions and documented child health programmes and policies. The Lives Saved Tool (LiST) was used to estimate child lives saved in 2013. RESULTS: The mortality rate in children under 5 years decreased rapidly in the 10 CI districts from 219 deaths per 1000 live births (95% confidence interval (CI) 189 to 249) in the period 1991-1995 to 119 deaths (95% CI 105 to 132) in the period 2006-2010. Coverage for all indicators except vitamin A supplementation increased in the 10 CI districts across the time period 2000 to 2013. The LiST analysis estimates that there were 10 800 child deaths averted in the 10 CI districts in 2013, primarily attributable to the introduction of the pneumococcal vaccine (24%) and increased household coverage of insecticide-treated bednets (19%). These improvements have taken place within a context of investment in child health policies and scale up of integrated community case management of childhood illnesses. CONCLUSIONS: Malawi provides a strong example for countries in sub-Saharan Africa of how high impact child health interventions implemented within a decentralised health system with an established community-based delivery platform, can lead to significant reductions in child mortality.

The role of 'hidden' community volunteers in community-based health service delivery platforms: examples from sub-Saharan Africa.

Community-based research on child survival in sub-Saharan Africa has focussed on the increased provision of curative health services by a formalised cadre of lay community health workers (CHWs), but we have identified a particular configuration, that deserves closer scrutiny. We identified a two-tiered CHW system, with the first tier being the lessor known or 'hidden' community/village level volunteers and the second tier being formal, paid CHWs, in Ethiopia, Mali, and Niger. Whilst the disease-focussed tasks of the formal CHW tier may be more amenable to classic epidemiological surveillance, we postulate that understanding the relationship between formalised CHWs and volunteer cadres, in terms of scope, location of practice and ratio to population, would be important for a comprehensive evaluation of child survival in these countries. We report on the findings from our joint qualitative and quantitative investigations, highlighting the need to recognise the 'hidden' contribution of volunteers. We need to better characterize the volunteers' interaction with community-based and primary care services and to better understand ways to improve the volunteer systems with the right type of investments. This is particularly important for considering the models for scale-up of CHWs in sub-Saharan Africa.

Multi-country analysis of routine data from integrated community case management (iCCM) programs in sub-Saharan Africa.

AIM: To identify better performing iCCM programs in sub-Saharan Africa (SSA) and identify factors associated with better performance using routine data. METHODS: We examined 15 evaluations or studies of integrated community case management (iCCM) programs in SSA conducted between 2008 and 2013 and with information about the program; routine data on treatments, supervision, and stockouts; and, where available, data from community health worker (CHW) surveys on supervision and stockouts. Analyses included descriptive statistics, Fisher exact test for differences in median treatment rates, the Kruskal-Wallis test for differences in the distribution of treatment rates, and Spearman's correlation by program factors. RESULTS: The median percent of annual expected cases treated was 27% (1-74%) for total iCCM, 37% (1-80%) for malaria, 155% (7-552%) for pneumonia, and 27% (1-74%) for diarrhoea. Seven programs had above median total iCCM treatments rates. Four programs had above median treatment rates, above median treatments per active CHW per month, and above median percent of expected cases treated. Larger populations under-five targeted were negatively associated with treatment rates for fever, malaria, diarrhea, and total iCCM. The ratio of CHWs per population was positively associated with diarrhoea treatment rates. Use of rapid diagnostic tests (RDTs) was negatively associated with treatment rates for pneumonia. Treatment rates and percent of annual expected cases treated were equivalent between programs with volunteer CHWs and programs with salaried CHWs. CONCLUSIONS: There is large variation in iCCM program performance in SSA. Four programs appear to be higher performing in terms of treatment rates, treatments per CHW per month, and percent of expected cases treated. Treatment rates for diarrhoea are lower than expected across most programmes. CHWs in many programmes are overtreating pneumonia. Programs targeting larger populations under-five tend to have lower treatment rates. The reasons for lower pneumonia treatment rates where CHWs use RDTs need to be explored. Programs with volunteer CHWs and those with salaried CHWs can achieve similar treatment rates and percent of annual expected cases treated but to do so volunteer programs must manage more CHWs per population and salaried CHWs must provide more treatments per CHW per month.

A proposed model to conduct process and outcome evaluations and implementation research of child health programs in Africa using integrated community case management as an example.

AIM: To use a newly devised set of criteria to review the study design and scope of collection of process, outcomes and contextual data for evaluations and implementation research of integrated community case management (iCCM) in Sub-Saharan African. METHODS: We examined 24 program evaluations and implementation research studies of iCCM in sub-Saharan Africa conducted in the last 5 years (2008-2013), assessed the design used and categorized them according to whether or not they collected sufficient information to conduct process and outcome evaluations. RESULTS: Five of the 24 studies used a stepped wedge design and two were randomized control trials. The remaining 17 were quasi-experimental of which 10 had comparison areas; however, not all comparison areas had a pre and post household survey. With regard to process data, 22 of the studies collected sufficient information to report on implementation strength, and all, except one, could report on program implementation. Most common missing data elements were health facility treatments, service costs, and qualitative data to assess demand. For the measurement of program outcomes, 7 of the 24 studies had a year or less of implementation at scale before the endline survey, 6 of the household surveys did not collect point of service, 10 did not collect timeliness (care seeking within 24 hours of symptoms) and 12 did not have socioeconomic (SES) information. Among the 16 studies with comparison areas, only 5 randomly selected comparison areas, while 10 had appropriate comparison areas. CONCLUSIONS: Several evaluations were done too soon after implementation, lacked information on health facility treatments, costs, demand, timeliness or SES and/or did not have a counterfactual. We propose several study designs and minimal data elements to be collected to provide sufficient information to assess whether iCCM increased timely coverage of treatment for the neediest children in a cost-efficient manner.

Fluctuations in wasting in vulnerable child populations in the Greater Horn of Africa.

BACKGROUND: Malnutrition in preschool children, usually measured as wasting, is widely used to assess possible needs for emergency humanitarian interventions in areas vulnerable to drought, displacement, and related causes of food insecurity. The extent of fluctuations in wasting by season, year-to-year, and differential effects by livelihood group, need to be better established as a basis for interpretation together with ways of presenting large numbers of survey results to facilitate interpretation. OBJECTIVE: To estimate levels of and fluctuations in wasting prevalences in children from surveys conducted in arid and semiarid areas of the Greater Horn of Africa according to livelihood (pastoral, agricultural, mixed, migrant), season or month, and year from 2000 to 2006. METHODS: Results from around 900 area-level nutrition surveys (typical sample size, about 900 children) were compiled and analyzed. These surveys were carried out largely by nongovernmental organizations, coordinated by UNICEF, in vulnerable areas of Eritrea, Ethiopia, Kenya, Somalia, Southern Sudan, and Uganda. Demographic and Health Survey (DHS) and Multiple Indicator Cluster Survey (MICS) data were used for comparison. Data were taken from measurements of children 0 to 5 years of age (or less than 110 cm in height). RESULTS: Among pastoral child populations, the average prevalence of wasting (< -2 SD weight-for-height) was about 17%, 6-7 percentage points higher than the rates among agricultural populations or populations with mixed livelihoods. Fluctuations in wasting were greater among pastoralists during years of drought, with prevalences rising to 25% or higher; prevalences among agricultural populations seldom exceeded 15%. This difference may be related to very different growth patterns (assessed from DHS and UNICEF/MICS surveys), whereby pastoral children typically grow up thinner but taller than children of agriculturalists. Wasting peaks are seen in the first half of the year, usually during the dry or hunger season. In average years, the seasonal increase is about 5 percentage points. Internally displaced people and urban migrants have somewhat higher prevalence rates of wasting. Year-to-year differences are the largest, loosely correlated with drought at the national level but subject to local variations. CONCLUSIONS: Tracking changes in wasting prevalence over time at the area level--e.g., with time-series graphical presentations--facilitates interpretation of survey results obtained at any given time. Roughly, wasting prevalences exceeding 25% in pastoralists and 15% in agriculturalists (taking account of timing) indicate unusual malnutrition levels. Different populations should be judged by population-specific criteria, and invariant prevalence cutoff points avoided; interpretation rules are suggested. Survey estimates of wasting, when seen in the context of historical values and viewed as specific to different livelihood groups, can provide useful timely warning of the need for intervention to mitigate developing nutritional crises.

Identifying priorities for emergency intervention from child wasting and mortality estimates in vulnerable areas of the Horn of Africa.

BACKGROUND: The relation between anthropometric measures and mortality risk in different populations can provide a basis for deciding how malnutrition prevalences should be interpreted. OBJECTIVE: To assess criteria for deciding on needs for emergency interventions in the Horn of Africa based on associations between child wasting and mortality from 2000 to 2005. METHODS: Data were analyzed on child global acute malnutrition (GAM) prevalences and mortality estimates from about 900 area-level nutrition surveys from Ethiopia, Kenya, Somalia, Sudan, and Uganda; data on drought, floods, and food insecurity were added for Kenya (Rift Valley) and Ethiopia, from Food and Agriculture Organization (FAO) reports at the time. RESULTS: Higher rates of GAM were associated with increased mortality of children under 5 years of age (U5MR), more strongly among populations with pastoral livelihoods than with agricultural livelihoods. In all groups spikes of GAM and U5MR corresponded with drought (and floods). Different GAM cutoff points are needed for different populations. For example, to identify 75% of U5MRs above 2/10,000/day, the GAM cutoff point ranged from 20% GAM in the Rift Valley (Kenya) to 8% in Oromia or SNNPR (Ethiopia). CONCLUSIONS: Survey results should be displayed as time series within geographic areas. Variable GAM cutoff points should be used, depending on livelihood or location. For example, a GAM cutoff point of 15% may be appropriate for pastoral groups and 10% for agricultural livelihood groups. This gives a basis for reexamining the guidelines currently used for interpreting wasting (or GAM) prevalences in terms of implications for intervention.