Coverage Of Health Interventions Research Articles

Erosion of the Capital City Advantage in Child Survival and Reproductive, Maternal, Newborn, and Child Health Intervention Coverage in Sub-Saharan Africa.

The place of residence is a major determinant of RMNCH outcomes, with rural areas often lagging in sub-Saharan Africa. This long-held pattern may be changing given differential progress across areas and increasing urbanization. We assessed inequalities in child mortality and RMNCH coverage across capital cities and other urban and rural areas. We analyzed mortality data from 163 DHS and MICS in 39 countries with the most recent survey conducted between 1990 and 2020 and RMNCH coverage data from 39 countries. We assessed inequality trends in neonatal and under-five mortality and in RMNCH coverage using multilevel linear regression models. Under-five mortality rates and RMNCH service coverage inequalities by place of residence have reduced substantially in sub-Saharan Africa, with rural areas experiencing faster progress than other areas. The absolute gap in child mortality between rural areas and capital cities and that between rural and other urban areas reduced respectively from 41 and 26 deaths per 1000 live births in 2000 to 23 and 15 by 2015. Capital cities are losing their primacy in child survival and RMNCH coverage over other urban areas and rural areas, especially in Eastern Africa where under-five mortality gap between capital cities and rural areas closed almost completely by 2015. While child mortality and RMNCH coverage inequalities are closing rapidly by place of residence, slower trends in capital cities and urban areas suggest gradual erosion of capital city and urban health advantage. Monitoring child mortality and RMNCH coverage trends in urban areas, especially among the urban poor, and addressing factors of within urban inequalities are urgently needed.

Coverage, Trends, and Inequalities of Maternal, Newborn, and Child Health Indicators among the Poor and Non-Poor in the Most Populous Cities from 38 Sub-Saharan African Countries.

Rapid urbanization is likely to be associated with suboptimal access to essential health services. This is especially true in cities from sub-Saharan Africa (SSA), where urbanization is outpacing improvements in infrastructure. We assessed the current situation in regard to several markers of maternal, newborn, and child health, including indicators of coverage of health interventions (demand for family planning satisfied with modern methods, at least four antenatal care visits (ANC4+), institutional birth, and three doses of DPT vaccine[diphtheria, pertussis and tetanus]) and health status (stunting in children under 5 years, neonatal and under-5 mortality rates) among the poor and non-poor in the most populous cities from 38 SSA countries. We analyzed 136 population-based surveys (year range 2000-2019), contrasting the poorest 40% of households (referred to as poor) with the richest 60% (non-poor). Coverage in the most recent survey was higher for the city non-poor compared to the poor for all interventions in virtually all cities, with the largest median gap observed for ANC4+ (13.5 percentage points higher for the non-poor). Stunting, neonatal, and under-5 mortality rates were higher among the poor (7.6 percentage points, 21.2 and 10.3 deaths per 1000 live births, respectively). The gaps in coverage between the two groups were reducing, except for ANC4, with similar median average annual rate of change in both groups. Similar rates of change were also observed for stunting and the mortality indicators. Continuation of these positive trends is needed to eliminate inequalities in essential health services and child survival in SSA cities.

Reproductive, maternal, newborn, and child health intervention coverage in 70 low-income and middle-income countries, 2000–30: trends, projections, and inequities

Monitoring the progress in reproductive, maternal, newborn, and child health (RMNCH) using the composite coverage index (CCI) is crucial to evaluate the advancement of low-income and middle-income countries (LMICs) towards the attainment of Sustainable Development Goal target 3. We present current benchmarking for 70 LMICs, forecasting to 2030, and an analysis of inequities within and across countries. In this cross-sectional secondary data analysis, we extracted 291 data points from the WHO Equity Monitor, and Demographic and Health Survey Statcompiler for 70 LMICs. We selected countries on the basis of whether they belonged to LMICs, had complete information about the predictors between 2000 and 2030, and had at least one data point related to CCI. CCI was calculated on the basis of eight types of RMNCH interventions in four domains, comprising family planning, antenatal care, immunisations, and management of childhood illnesses. This study examined CCI as the main outcome variable. Bayesian hierarchical models were used to estimate trends and projections of the CCI at regional and national levels, as well as the area of residence, educational level, and wealth quintile. Despite progress, only 18 countries are projected to reach the 80% CCI target by 2030. Regionally, CCI is projected to increase in all regions of Asia (in southern Asia from 51·8% in 2000 to 89·2% in 2030; in southeastern Asia from 58·8% to 84·4%; in central Asia from 70·3% to 87·0%; in eastern Asia from 76·8% to 82·1%; and in western Asia from 56·5% to 72·1%), Africa (in sub-Saharan Africa from 46·3% in 2000 to 72·2% in 2030 and in northern Africa from 55·0% to 81·7%), and Latin America and the Caribbean (from 67·0% in 2000 to 83·4% in 2030). By contrast, southern Europe is predicted to experience a decline in CCI over the same period (70·1% in 2000 to 55·2% in 2030). Across LMICs, CCIs are higher in urban areas, in populations in which women have higher education levels, and in populations with a high income. Governments of countries where the universal target of 80% CCI has not yet been reached must develop evidence-based policies aimed at enhancing RMNCH coverage. Additionally, they should focus on reducing the extent of existing inequalities within their populations to drive progress in RMNCH. Hitotsubashi University and Japan Society for the Promotion of Science.

Going deeper with health equity measurement: how much more can surveys reveal about inequalities in health intervention coverage and mortality in Zambia?

BackgroundAlthough Zambia has achieved notable improvements in reproductive, maternal, newborn and child health (RMNCH), continued efforts to address gaps are essential to reach the Sustainable Development Goals by 2030. Research to better uncover who is being most left behind with poor health outcomes is crucial. This study aimed to understand how much more demographic health surveys can reveal about Zambia’s progress in reducing inequalities in under-five mortality rates and RMNCH intervention coverage.MethodsUsing four nationally-representative Zambia Demographic Health Surveys (2001/2, 2007, 2013/14, 2018), we estimated under-five mortality rates (U5MR) and RMNCH composite coverage indices (CCI) comparing wealth quintiles, urban‐rural residence and provinces. We further used multi-tier measures including wealth deciles and double disaggregation between wealth and region (urban residence, then provinces). These were summarised using slope indices of inequality, weighted mean differences from overall mean, Theil and concentration indices.ResultsInequalities in RMNCH coverage and under-five mortality narrowed between wealth groups, residence and provinces over time, but in different ways. Comparing measures of inequalities over time, disaggregation with multiple socio-economic and geographic stratifiers was often valuable and provided additional insights compared to conventional measures. Wealth quintiles were sufficient in revealing mortality inequalities compared to deciles, but comparing CCI by deciles provided more nuance by showing that the poorest 10% were left behind by 2018. Examining wealth in only urban areas helped reveal closing gaps in under-five mortality and CCI between the poorest and richest quintiles. Though challenged by lower precision, wealth gaps appeared to close in every province for both mortality and CCI. Still, inequalities remained higher in provinces with worse outcomes.ConclusionsMulti-tier equity measures provided similarly plausible and precise estimates as conventional measures for most comparisons, except mortality among some wealth deciles, and wealth tertiles by province. This suggests that related research could readily use these multi-tier measures to gain deeper insights on inequality patterns for both health coverage and impact indicators, given sufficient samples. Future household survey analyses using fit-for-purpose equity measures are needed to uncover intersecting inequalities and target efforts towards effective coverage that will leave no woman or child behind in Zambia and beyond.

Geographic inequalities in health intervention coverage – mapping the composite coverage index in Peru using geospatial modelling

BackgroundThe composite coverage index (CCI) provides an integrated perspective towards universal health coverage in the context of reproductive, maternal, newborn and child health. Given the sample design of most household surveys does not provide coverage estimates below the first administrative level, approaches for achieving more granular estimates are needed. We used a model-based geostatistical approach to estimate the CCI at multiple resolutions in Peru.MethodsWe generated estimates for the eight indicators on which the CCI is based for the departments, provinces, and areas of 5 × 5 km of Peru using data from two national household surveys carried out in 2018 and 2019 plus geospatial covariates. Bayesian geostatistical models were fit using the INLA-SPDE approach. We assessed model fit using cross-validation at the survey cluster level and by comparing modelled and direct survey estimates at the department-level.ResultsCCI coverage in the provinces along the coast was consistently higher than in the remainder of the country. Jungle areas in the north and east presented the lowest coverage levels and the largest gaps between and within provinces. The greatest inequalities were found, unsurprisingly, in the largest provinces where populations are scattered in jungle territory and are difficult to reach.ConclusionsOur study highlighted provinces with high levels of inequality in CCI coverage indicating areas, mostly low-populated jungle areas, where more attention is needed. We also uncovered other areas, such as the border with Bolivia, where coverage is lower than the coastal provinces and should receive increased efforts. More generally, our results make the case for high-resolution estimates to unveil geographic inequities otherwise hidden by the usual levels of survey representativeness.

Lessons and Implementation Challenges of Community Health Information System in LMICs: A Scoping Review of Literature.

Accurate and timely information on health intervention coverage, quality, and equity is the foundation of public health practice. To achieve this, countries have made efforts to improve the quality and availability of community health data by implementing the community health information system that is used to collect data in the field generated by community health workers and other community-facing providers. Despite all the efforts, evidence on the current state is scant in Low Middle Income Countries (LMICs). To summarize the available evidence on the current implementation status, lessons learned and implementation challenges of community health information system (CHIS) in LMICs. We conducted a scoping review that included studies searched using electronic databases like Pubmed/Medline, World Health Organization (WHO) Library, Science Direct, Cochrane Library. We also searched Google and Google Scholar using different combinations of search strategies. Studies that applied any study design, data collection and analysis methods related to CHIS were included. The review included all studies published until February 30, 2022. Two authors extracted the data and resolved disagreements by discussion consulting a third author. A total of 1,552 potentially relevant articles/reports were generated from the initial search, of which 21 were considered for the final review. The review found that CHIS is implemented in various structures using various tools across different LMICs. For the CHIS implementation majority used registers, family folder/card, mobile technologies and chalk/white board. Community level information was fragmented, incomplete and in most cases flowed only one way, with a bottom-up approach. The review also indicated that, technology particularly Electronic Community Health Information System (eCHIS) and mobile applications plays a role in strengthening CHIS implementation in most LMICs. Many challenges remain for effective implementation of CHIS with unintegrated systems including existence of parallel recording & reporting tools. Besides, lack of resources, low technical capacity, shortage of human resource and poor Information Communication Technology (ICT) infrastructure were reported as barriers for effective implementation of CHIS in LMICs. Generally, community health information system implementation in LMICs is in its early stage. There was not a universal or standard CHIS design and implementation modality across countries. There are also promising practices on digitalizing the community health information systems. Different organizational, technical, behavioural and economic barriers exist for effective implementation of CHIS. Hence, greater collaboration, coordination, and joint action are needed to address these challenges. Strong leadership, motivation, capacity building and regular feedback are also important to strengthen the CHIS in LMICs. Moreover, CHIS should be transformed in to eCHIS with integration of different technology solutions. Local ownership is also critical to the long-term sustainability of CHIS implementation.

Impact of mass distribution of insecticide-treated nets in Mozambique, 2012 to 2025: Estimates of child lives saved using the Lives Saved Tool.

Malaria was the leading cause of post-neonatal deaths in Mozambique in 2017. The use of insecticide treated nets (ITNs) is recognized as one of the most effective ways to reduce malaria mortality in children. No previous analyses have estimated changes in mortality attributable to the scale-up of ITNs, accounting for provincial differences in mortality rates and coverage of health interventions. Based upon annual provincial ownership coverage of ITNs, the Lives Saved Tool (LiST), a multi-cause mathematical model, estimated under-5 lives saved attributable to increased household ITN coverage in 10 provinces of Mozambique between 2012 and 2018, and projected lives saved from 2019 to 2025 if 2018 coverage levels are sustained. An estimated 14,040 under-5 child deaths were averted between 2012 and 2018. If 2018 coverage levels are maintained until 2025, an additional 33,277 child deaths could be avoided. If coverage reaches at least 85% in all ten provinces by 2022, then a projected 36,063 child lives can be saved. From 2012 to 2018, the estimated number of lives saved was highest in Zambezia and Tete provinces. Increases in ITN coverage can save a substantial number of child lives in Mozambique. Without continued investment, thousands of avoidable child deaths will occur.

Ethnic inequalities in health intervention coverage among Mexican women at the individual and municipality levels.

BackgroundUsing data from Mexico, the country with the largest indigenous population in Latin America, we describe ethnic inequalities in coverage with women's health interventions at individual and municipal levels.MethodsCross-sectional study using data from the National Health and Nutrition Survey 2018 and the Mexican Intercensal Survey 2015. We selected five outcomes: modern contraceptive use, content-qualified antenatal care (ANCq), and skilled birth attendant (SBA) for women aged 15–49 years; Pap smear test and mammogram among women aged 25-64 and 40-69 years respectively. Municipalities were classified into three groups by the percentage of indigenous population: <10%, 10% – 39%, and ≥40%. We calculated crude and adjusted coverage ratios (CR) and 95% confidence intervals (CI) using Poisson regression.FindingsWomen living in municipalities with indigenous population ≥40% were poorer, less educated, and more rural. Coverage was lower for indigenous than non-indigenous for modern contraceptive use (CR: 0·73; CI 0·65-0·83), ANCq (CR: 0·72; CI 0·62-0·83), SBA (CR: 0·83; CI 0·77-0·90) and undergoing a mammogram (CR: 0·54; CI 0·41-0·71), but not for Pap smears (CR: 0·94; CI 0·83-1·07). Coverage with the five interventions increased as the municipal proportions of indigenous population decreased, both for indigenous and non-indigenous women. Coverage gaps at municipal level tended to be wider than at individual level.InterpretationBoth indigenous and non-indigenous women living in municipalities with high proportions of indigenous people were systematically excluded from reproductive and maternal interventions. Our findings suggest that social and health interventions targeted at the individual level should be complemented by structural interventions in municipalities with high proportions of indigenous people, including strengthening health and social services.

Can We Use Routine Data for Strategic Decision Making? A Time Trend Comparison Between Survey and Routine Data in Mali

Countries with scarce resources need timely and high-quality data on coverage of health interventions to make strategic decisions about where to allocate investments in health. Household survey data are generally regarded as "gold standard," high-quality data. This study assessed the comparability of intervention coverage time trends from routine and survey data at national and subnational levels in Mali. We compared 3 coverage indicators: contraceptive prevalence rate, institutional delivery, and 3 doses of diphtheria, pertussis, and tetanus (DPT3) vaccine, using 3 Mali Demographic and Health Surveys (DHS 2001, 2006, and 2012-2013) and routine health system data covering 2001-2012. For routine data, we used local health information system (HIS) annual reports and an HIS database. To compare time trends between the data sources, we calculated the percentage point change and 95% confidence interval from 2001-2006 and 2006-2012. We then computed the absolute and relative differences between the 2 data sources for each indicator over time at national and regional levels and assessed their level of significance. The direction and magnitude of the time trends of contraceptive prevalence rate, institutional delivery, and DPT3 vaccine from 2001 to 2012 were similar at the national level between data sources. At the regional level, there were significant differences in the magnitude and direction of time trends for institutional delivery and the DPT3 vaccine; contraceptive prevalence trends were more consistent. Routine data tended to overestimate DPT3 coverage, and underestimate institutional delivery and contraceptive prevalence relative to survey data. Routine data in Mali-particularly at the national level-appear to be appropriate for use to inform program planning and prioritization, but routine time trends should be interpreted with caution at the subnational level. For program evaluations, routine data may not be appropriate to draw accurate inferences about program impact.

The impact of child health interventions and risk factors on child survival in Kenya, 1993\u20132014: a Bayesian spatio-temporal analysis with counterfactual scenarios

BackgroundDuring the millennium development goals period, reduction in under-five mortality (U5M) and increases in child health intervention coverage were characterised by sub-national disparities and inequities across Kenya. The contribution of changing risk factors and intervention coverage on the sub-national changes in U5M remains poorly defined.MethodsSub-national county-level data on U5M and 43 factors known to be associated with U5M spanning 1993 and 2014 were assembled. Using a Bayesian ecological mixed-effects regression model, the relationships between U5M and significant intervention and infection risk ecological factors were quantified across 47 sub-national counties. The coefficients generated were used within a counterfactual framework to estimate U5M and under-five deaths averted (U5-DA) for every county and year (1993–2014) associated with changes in the coverage of interventions and disease infection prevalence relative to 1993.ResultsNationally, the stagnation and increase in U5M in the 1990s were associated with rising human immunodeficiency virus (HIV) prevalence and reduced maternal autonomy while improvements after 2006 were associated with a decline in the prevalence of HIV and malaria, increase in access to better sanitation, fever treatment-seeking rates and maternal autonomy. Reduced stunting and increased coverage of early breastfeeding and institutional deliveries were associated with a smaller number of U5-DA compared to other factors while a reduction in high parity and fully immunised children were associated with under-five lives lost. Most of the U5-DA occurred after 2006 and varied spatially across counties. The highest number of U5-DA was recorded in western and coastal Kenya while northern Kenya recorded a lower number of U5-DA than western. Central Kenya had the lowest U5-DA. The deaths averted across the different regions were associated with a unique set of factors.ConclusionContributions of interventions and risk factors to changing U5M vary sub-nationally. This has important implications for targeting future interventions within decentralised health systems such as those operated in Kenya. Targeting specific factors where U5M has been high and intervention coverage poor would lead to the highest likelihood of sub-national attainment of sustainable development goal (SDG) 3.2 on U5M in Kenya.

Ethnic Inequalities in Health Intervention Coverage Among Mexican Women at the Individual and Municipality Levels

Background: Using data from Mexico, the country with the largest indigenous population in Latin America, we describe ethnic inequalities in coverage with women's health interventions at individual and municipal levels. Methods: Cross-sectional study using data from the National Health and Nutrition Survey 2018 and the Mexican Intercensal Survey 2015. We selected five outcomes: modern contraceptive use, content-qualified antenatal care (ANCq), and skilled birth attendant (SBA) for women aged 15–49 years; Pap smear test and mammogram among women aged 25-64 and 40-69 years respectively. Municipalities were classified into three groups by the percentage of indigenous population: <10%, 10% – 39%, and ≥40%. We calculated crude and adjusted coverage ratios (CR) and 95% confidence intervals (CI) using Poisson regression. Findings: Women living in municipalities with indigenous population ≥40% were poorer, less educated, and more rural. Coverage was lower for indigenous than non-indigenous for modern contraceptive use (CR: 0·73; CI 0·65-0·83), ANCq (CR: 0·72; CI 0·62-0·83), SBA (CR: 0·83; CI 0·77-0·90) and undergoing a mammogram (CR: 0·54; CI 0·41-0·71), but not for Pap smears (CR: 0.94; CI 0.83-1.07). Coverage with the five interventions increased as the municipal proportions of indigenous population decreased, both for indigenous and non-indigenous women. Coverage gaps at municipal level tended to be wider than at individual level. Interpretation: Both indigenous and non-indigenous women living in municipalities with high proportions of indigenous people were systematically excluded from reproductive and maternal interventions. Our findings are relevant for targeting interventions to the most vulnerable groups of women to leave no one behind. Funding: Wellcome Trust and Associacao Brasileira de Saude Coletiva (ABRASCO). Declaration of Interests: We declare no competing interests.

Potential impact of midwives in preventing and reducing maternal and neonatal mortality and stillbirths: a Lives Saved Tool modelling study

SummaryBackgroundStrengthening the capacity of midwives to deliver high-quality maternal and newborn health services has been highlighted as a priority by global health organisations. To support low-income and middle-income countries (LMICs) in their decisions about investments in health, we aimed to estimate the potential impact of midwives on reducing maternal and neonatal deaths and stillbirths under several intervention coverage scenarios.MethodsFor this modelling study, we used the Lives Saved Tool to estimate the number of deaths that would be averted by 2035, if coverage of health interventions that can be delivered by professional midwives were scaled up in 88 countries that account for the vast majority of the world's maternal and neonatal deaths and stillbirths. We used four scenarios to assess the effects of increasing the coverage of midwife-delivered interventions by a modest amount (10% every 5 years), a substantial amount (25% every 5 years), and the amount needed to reach universal coverage of these interventions (ie, to 95%); and the effects of coverage attrition (a 2% decrease every 5 years). We grouped countries in three equal-sized groups according to their Human Development Index. Group A included the 30 countries with the lowest HDI, group B included 29 low-to-medium HDI countries, and group C included 29 medium-to-high HDI countries.FindingsWe estimated that, relative to current coverage, a substantial increase in coverage of midwife-delivered interventions could avert 41% of maternal deaths, 39% of neonatal deaths, and 26% of stillbirths, equating to 2·2 million deaths averted per year by 2035. Even a modest increase in coverage of midwife-delivered interventions could avert 22% of maternal deaths, 23% of neonatal deaths, and 14% of stillbirths, equating to 1·3 million deaths averted per year by 2035. Relative to current coverage, universal coverage of midwife-delivered interventions would avert 67% of maternal deaths, 64% of neonatal deaths, and 65% of stillbirths, allowing 4·3 million lives to be saved annually by 2035. These deaths averted would be particularly concentrated in the group B countries, which currently account for a large proportion of the world's population and have high mortality rates compared with group C.InterpretationMidwives can help to substantially reduce maternal and neonatal mortality and stillbirths in LMICs. However, to realise this potential, midwives need to have skills and competencies in line with recommendations from the International Confederation of Midwives, to be part of a team of sufficient size and skill, and to work in an enabling environment. Our study highlights the potential of midwives but there are many challenges to the achievement of this potential. If increased coverage of midwife-delivered interventions can be achieved, health systems will be better able to provide effective coverage of essential sexual, reproductive, maternal, newborn, and adolescent health interventions.FundingNew Venture Fund.

Operationalising health systems thinking: a pathway to high effective coverage

BackgroundThe global health community has recognised the importance of defining and measuring the effective coverage of health interventions and their implementation strength to monitor progress towards global mortality and morbidity targets. Existing health system models and frameworks guide thinking around these measurement areas; however, they fall short of adequately capturing the dynamic and multi-level relationships between different components of the health system. These relationships must be articulated for measurement and managed to effectively deliver health interventions of sufficient quality to achieve health impacts. Save the Children’s Saving Newborn Lives programme and EnCompass LLC, its evaluation partner, developed and applied the Pathway to High Effective Coverage as a health systems thinking framework (hereafter referred to as the Pathway) in its strategic planning, monitoring and evaluation.MethodsWe used an iterative approach to develop, test and refine thinking around the Pathway. The initial framework was developed based on existing literature, then shared and vetted during consultations with global health thought leaders in maternal and newborn health.ResultsThe Pathway is a robust health systems thinking framework that unpacks system, policy and point of intervention delivery factors, thus encouraging specific actions to address gaps in implementation and facilitate the achievement of high effective coverage. The Pathway includes six main components – (1) national readiness; (2) system structures; (3) management capacity; (4) implementation strength; (5) effective coverage; and (6) impact. Each component is comprised of specific elements reflecting the range of facility-, community- and home-based interventions. We describe applications of the Pathway and results for in-country strategic planning, monitoring of progress and implementation strength, and evaluation.ConclusionsThe Pathway provides a cohesive health systems thinking framework that facilitates assessment and coordinated action to achieve high coverage and impact. Experiences of its application show its utility in guiding strategic planning and in more comprehensive and effective monitoring and evaluation as well as its potential adaptability for use in other health areas and sectors.

Effective coverage of medical treatment for hypertension, diabetes and dyslipidaemia in Japan: An analysis of National Health and Nutrition Surveys 2003-2017.

To examine trends in effective medical treatment coverage for hypertension, diabetes and dyslipidaemia in Japan, using a metric to assess effective coverage of health interventions derived from a health system performance assessment framework. We obtained cross-sectional data for 96,863 individuals aged 40-74 years from the 15 annual Japanese National Health and Nutrition Surveys (2003-2017). We defined treatment need for hypertension, diabetes and dyslipidaemia as biomarkers equal to or greater than diagnostic thresholds or medication use. For individuals needing treatment, we conducted nearest-neighbour matching to estimate treatment effects and effective coverage, defined as the fraction of potential reductions in biomarkers actually achieved in treated individuals by medications. The age-standardized prevalence of treatment need for hypertension, diabetes and dyslipidaemia remained around 40%, 7% and 33%, respectively, in 2003-2017. Average treatment effects for those treated in 2013-2017 were 14.8 mmHg (95% confidence interval: 14.2-15.4) for systolic blood pressure, 1.2 percentage points (0.8-1.6) for haemoglobin A1c and 57.9 mg/dl (56.6-59.2) for non-high-density lipoprotein cholesterol. Effective coverage significantly increased between 2003-2007 (hypertension: 48.4% [44.7-52.0], diabetes: 43.8% [35.7-51.8], dyslipidaemia: 86.3% [83.1-89.5]) and 2013-2017 (hypertension: 76.2% [74.2-78.2], diabetes: 74.7% [71.0-78.5], dyslipidaemia: 94.6% [93.3-95.9]). Effective coverage of medical treatment for metabolic risk factors has increased. Most of the potential reductions in non-high-density lipoprotein cholesterol have been achieved by statins. Further efforts are necessary to improve the effectiveness of antihypertensive and antidiabetic drugs.

Inferring antenatal care visit timing in low- and middle-income countries: Methods to inform potential maternal vaccine coverage.

BackgroundThe timing of antenatal care (ANC) visits directly affect health intervention coverage and impact, especially for those interventions requiring strict gestational age windows for administration, such as maternal respiratory syncytial virus (RSV) vaccine. Existing nationally representative population-based surveys do not record the timing of ANC visits beyond the first, limiting the availability of reliable data around timing of subsequent ANC visits in most low- and middle-income countries (LMICs). Here, we describe a model that estimates the timing of ANC visits by gestational age using publicly available multi-country survey data.Methods and findingsWe used the Demographic and Health Surveys (DHS) data from 69 LMICs. We used several factors to estimate the timing of subsequent ANC visits by gestation age: the timing of the first ANC visit (ANC1) in a given pregnancy, derived from the DHS; the country’s reported average ANC coverage at each ANC visit (ANC1 through the fourth ANC visit [ANC4]); and the World Health Organization’s guidance on recommended ANC visit. We then used the timing of ANC visit by gestation age to predict the coverage of a potential maternal RSV vaccine administered at 24–36 weeks of gestation. We calculated the maternal immunization coverage by summing the number of eligible women vaccinated at any ANC visit divided by the total number of pregnant women. We find, in general, countries with higher ANC1 coverage were predicted to have higher vaccination coverage. In 82% of countries, the modeled vaccine coverage is less than ANC4 coverage.ConclusionsThe methods illustrated in this paper have implications on the precision of estimating impact and programmatic feasibility of time-critical interventions, especially for pregnant women. The methods can be easily adapted to vaccine demand forecasts models, vaccine impact assessments, and cost-effectiveness analyses and can be adapted to other maternal interventions that have administration timing restrictions.

C\u2019est vraiment compliqu\xe9: a case study on the delivery of maternal and child health and nutrition interventions in the conflict-affected regions of Mali

BackgroundMali is currently in the midst of ongoing conflicts which involve jihadist groups, rebels, and the state. This conflict has primarily centered in the North of the country. Humanitarian actors delivering services in these geographies must navigate the complex environment created by conflict. This study aimed to understand how humanitarian actors make decisions around health service delivery within this context.MethodsThe current case-study utilized a mixed methods approach and focused on Mopti, Mali’s fifth administrative region and fourth largest in population. Latent content analysis was used to analyze interview transcripts guided by our research objectives and new concepts as they emerged. Indicators of coverage of health interventions in the area of maternal and child health and nutrition were compiled using Mali’s National Evaluation Platform and are presented for the conflict and non-conflict regions. Development assistance estimates for Mali by year were obtained from the Developmental Assistance for Health Database compiled by the Institute for Health Metrics and Evaluation. Administrative data was compiled from the annual reports of Mali’s Système Local d’Information Sanitaire (SLIS), Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS).ResultsOur data suggests that the reaction of the funding mechanisms to the conflict in Mali was a major barrier to timely delivery of health services to populations in need and the nature of the conflict is likely a key modifier of such reaction patterns. Concerns have been raised about the disconnect between the very high administrative capacity of large NGOs that control the work, and the consequent burden it puts on local NGOs. Population displacement and inaccurate estimates of needs made it difficult for organizations to plan program services. Moreover, actors delivering services to populations in need had to navigate an unpredictable context and numerous security threats.ConclusionsOur study highlights the need for a more flexible funding and management mechanism that can better respond to concerns and issues arising at a local level. As the conflict in Mali continues to worsen, there is an urgent need to improve service delivery to conflict-affected populations.

Effective coverage as a new approach to health system performance assessment: a scoping review

BackgroundDelivering interventions is the main task of health systems whose accurate measurement is an essential input into tracking performance. Recently, the concept of effective coverage was introduced by World Health Organization to incorporate into health system performance assessment. The aim of present scoping review was mapping the key elements and steps of effective coverage assessment in practical efforts including kinds of interventions, criteria for selecting them and the need, use and quality estimation approaches and strategies of each intervention.MethodsWe conducted a scoping review of health system/program assessments which assessed effective coverage till May 2017. Seven databases were systematically searched with no time and language restriction through applying combined keyword of “effective coverage”.ResultsEighteen studies contributed findings on monitoring effective coverage of health interventions and they all were included in the review. Only 4 contributed findings on health system and the others were related to specific intervention(s) assessment. The interventions monitored by effective coverage were mainly in child health, prenatal and antenatal care and delivery, and chronic conditions areas. Potential impact on the burden of disease, leading causes of mortality and morbidity, and high occurrence and prevalence rate were among the main intervention selection criteria. Availability of data was the critical prerequisite, especially, in all of the studies applied ex post approach in estimating effective coverage. Estimation based on a norm, self- reporting from surveys and biomarkers were the main strategies and methods of need, utilization and quality measurement, respectively.ConclusionsMore studies are needed to contribute to the ongoing improvement in the development of effective coverage concept and increasing practical efforts, especially through defining prospective approaches and strategies into estimation of composite measures based on the effective coverage framework. Also, further attention needs to be paid to quality measures of effective coverage in a manner that better conceptualizes and measures the connection between coverage rates and interventions’ effectiveness. At the administrative system level, more innovation is needed to develop data systems in order to enhance capacity of routine health service information.

Measuring management practices in India's district public health bureaucracy

Weak management is widely recognised as a key impediment to scaling-up coverage of health interventions and ensuring health systems are responsive to population needs. Yet there is scant evidence linking management practices in the public administration to effective health service delivery. We report on the development of a tool to measure management practices in India's district health bureaucracy. We first developed a conceptual framework based on a review of the literature and qualitative interviews with district public health managers. Across 16 management practices, we then drafted and piloted questions to be used with a scoring grid to evaluate process-orientated management practices. We implemented the tool in 34 districts of Maharashtra between April and July 2016, interviewing up to three district public health managers per district (n = 99). Using rigorous psychometric methods, we assessed the acceptability, reliability and validity of the tool. We present three key findings. First, the tool was feasible to implement, response rates were high, and there were no missing data. Second, internal consistency of the tool was high and test-retest reliability was comparable with other management tools used in the literature. Third, there was evidence of validity. The number of staff with a management qualification was positively associated with better management practices. Factor analysis showed that one principal component loaded positively on all the management practices although there was little support for management sub-scales. These findings provide novel evidence on the psychometric properties of a tool designed to measure management practices in the public administration of a developing country. Our framework and tool provide the basis to examine associations between district health management practices and health service delivery, and test the effectiveness of management strengthening interventions in India's public health sector.

A method for estimating maternal and newborn lives saved from health-related investments funded by the UK government Department for International Development using the Lives Saved Tool

BackgroundIn 2010, the UK Government Department for International Development (DFID) committed through its 'Framework for results for reproductive, maternal and newborn health (RMNH)' to save 50,000 maternal lives and 250,000 newborn lives by 2015. They also committed to monitoring the performance of this portfolio of investments to demonstrate transparency and accountability. Methods currently available to directly measure lives saved are cost-, time-, and labour-intensive. The gold standard for calculating the total number of lives saved would require measuring mortality with large scale population based surveys or annual vital events surveillance. Neither is currently available in all low- and middle-income countries. Estimating the independent effect of DFID support relative to all other effects on health would also be challenging.MethodsThe Lives Saved Tool (LiST) is an evidence based software for modelling the effect of changes in health intervention coverage on reproductive, maternal, newborn and child mortality. A multi-country LiST-based analysis protocol was developed to retrospectively assess the total annual number of maternal and newborn lives saved from DFID aid programming in low- and middle-income countries.ResultsAnnual LiST analyses using the latest program data from DFID country offices were conducted between 2013 and 2016, estimating the annual number of maternal and neonatal lives saved across 2010–2015. For each country, independent project results were aggregated into health intervention coverage estimates, with and in the absence of DFID funding. More than 80% of reported projects were suitable for inclusion in the analysis, with 151 projects analysed in the 2016 analysis. Between 2010 and 2014, it is estimated that DFID contributed to saving the lives of 15,000 women in pregnancy and childbirth with health programming and 88,000 with family planning programming. It is estimated that DFID health programming contributed to saving 187,000 newborn lives.ConclusionsIt is feasible to estimate the overall contribution and impact of DFID’s investment in RMNH from currently available information on interventions and coverage from individual country offices. This utilization of LiST, with estimated population coverage based on DFID program inputs, can be applied to similar types of datasets to quantify programme impact. The global data were used to estimate DFID’s progress against the Framework for results targets to inform future programming. The identified limitations can also be considered to inform future monitoring and evaluation program design and implementation within DFID.

The impact of eliminating within-country inequality in health coverage on maternal and child mortality: a Lives Saved Tool analysis

BackgroundInequality in healthcare across population groups in low-income countries is a growing topic of interest in global health. The Lives Saved Tool (LiST), which uses health intervention coverage to model maternal, neonatal, and child health outcomes such as mortality rates, can be used to analyze the impact of within-country inequality.MethodsData from nationally representative household surveys (98 surveys conducted between 1998 and 2014), disaggregated by wealth quintile, were used to create a LiST analysis that models the impact of scaling up health intervention coverage for the entire country from the national average to the rate of the top wealth quintile (richest 20% of the population). Interventions for which household survey data are available were used as proxies for other interventions that are not measured in surveys, based on co-delivery of intervention packages.ResultsFor the 98 countries included in the analysis, 24–32% of child deaths (including 34–47% of neonatal deaths and 16–19% of post-neonatal deaths) could be prevented by scaling up national coverage of key health interventions to the level of the top wealth quintile. On average, the interventions with most unequal coverage rates across wealth quintiles were those related to childbirth in health facilities and to water and sanitation infrastructure; the most equally distributed were those delivered through community-based mass campaigns, such as vaccines, vitamin A supplementation, and bednet distribution.ConclusionsLiST is a powerful tool for exploring the policy and programmatic implications of within-country inequality in low-income, high-mortality-burden countries. An “Equity Tool” app has been developed within the software to make this type of analysis easily accessible to users.