Deprivation and Its Association with Child Health and Nutrition in the Greater Kampala Metropolitan Area of Uganda.

African cities are experiencing increasing living standard disparities with limited evidence of intra-urban health disparities. Using data from the 2006-2016 Uganda Demographic and Health Surveys, we employed the UN-Habitat definition to examine slum-like household conditions in the Greater Kampala Metropolitan Area (GKMA). Subsequently, we developed a slum-like severity index and assessed its association with under-5 common morbidities and healthcare access. We also assessed the characteristics of people in slum-like household conditions. We identified five slum-like conditions: substandard housing conditions, limited water access, overcrowding, unclean cooking fuel, and limited toilet access. By 2016, 67% of GKMA households were classified as slum-like conditions, including 31% in severe conditions. Limited toilet access, overcrowding, and limited water access were the main forms of deprivation.Living in slum-like household conditions correlated with lower education levels, youth status, unprofessional jobs, and marriage. Compared to neighboring Kampala city urban outskirts, Kampala city households had lower slum-like prevalence. Children in GKMA living in slum-like household conditions were more likely to experience diarrhea (moderate: OR = 1.21[95% CI: 1.05-1.39], severe: OR = 1.47 [95% CI: 1.27-1.7]); fever (moderate: OR = 2.67 [95% CI: 1.23-5.8], severe: OR = 3.09 [95% CI: 1.63-5.85]); anemia (moderate: OR = 1.18 [95% CI: 0.88-1.58], severe: OR = 1.44 [95% CI: 1.11-1.86]); and stunting (moderate: OR = 1.23 [95% CI: 1.23-1.25], severe: OR = 1.40 [95% CI: 1.41-1.47]) compared to those living in less slum-like conditions. However, seeking treatment for fever was less likely in slum-like household conditions, and the association of slum-like household conditions with diarrhea was insignificant. These findings underscore the precarious urban living conditions and the need for targeted health interventions addressing the social determinants of health in urban settings.

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.

Identifying and Characterizing the Poorest Urban Population Using National Household Surveys in 38 Cities in Sub-Saharan Africa.

Identifying and classifying poor and rich groups in cities depends on several factors. Using data from available nationally representative surveys from 38 sub-Saharan African countries, we aimed to identify, through different poverty classifications, the best classification in urban and large city contexts. Additionally, we characterized the poor and rich groups in terms of living standards and schooling. We relied on absolute and relative measures in the identification process. For absolute ones, we selected people living below the poverty line, socioeconomic deprivation status and the UN-Habitat slum definition. We used different cut-off points for relative measures based on wealth distribution: 30%, 40%, 50%, and 60%. We analyzed all these measures according to the absence of electricity, improved drinking water and sanitation facilities, the proportion of children out-of-school, and any household member aged 10 or more with less than 6 years of education. We used the sample size, the gap between the poorest and richest groups, and the observed agreement between absolute and relative measures to identify the best measure. The best classification was based on 40% of the wealth since it has good discriminatory power between groups and median observed agreement higher than 60% in all selected cities. Using this measure, the median prevalence of absence of improved sanitation facilities was 82% among the poorer, and this indicator presented the highest inequalities. Educational indicators presented the lower prevalence and inequalities. Luanda, Ouagadougou, and N'Djaména were considered the worst performers, while Lagos, Douala, and Nairobi were the best performers. The higher the human development index, the lower the observed inequalities. When analyzing cities using nationally representative surveys, we recommend using the relative measure of 40% of wealth to characterize the poorest group. This classification presented large gaps in the selected outcomes and good agreement with absolute measures.

Delivery and postnatal care among women in 71 low- and middle-income countries: analyzing coverage gaps using household surveys.

BACKGROUND: High levels of maternal morbidity and mortality persist in low- and middle-income countries, despite increases in coverage of facility delivery and skilled assistance at delivery. We compared levels of facility birth to a summary delivery care measure and quantified gaps. METHODS: We approximated a delivery care score from type of delivery (home, lower-level facility, or hospital), skilled attendant at delivery, a stay of 24-or-more-hours after delivery, and a health check within 48-h after delivery. Data were obtained from 333,316 women aged 15-49 who had a live birth in the previous 2 years, and from 71 countries with nationally representative surveys between 2013 and 2020. We computed facility delivery and delivery care coverage estimates to assess the gap. We stratified the analysis by country characteristics, including the national maternal mortality ratio (MMR), to assess the size of coverage gaps, and we assessed missed opportunities through coverage cascades. We looked at the association between MMR and delivery care coverage. RESULTS: Delivery care coverage varied by country, ranging from 24% in Sudan to 100% in Cuba. Median coverage was 70% with an interquartile range of 30 percentage points (55% and 85%). The cascade showed that while 76% of women delivered in a facility, only 41% received all four interventions. Coverage gaps exist across all MMR levels. Gaps between highest and lowest wealth quintiles were greatest in countries with MMR levels of 100 or higher, and the gap narrowed in countries with MMR levels below 100. The delivery care indicator had a negative association with MMR. CONCLUSIONS: In addition to providing high-quality evidenced-based care to women during birth and the postpartum period, there is also a need to address gaps in delivery care, which occur within and between countries, wealth quintiles, and MMR phases.

Endoscopic Third Ventriculostomy with Choroid Plexus Cauterization in Infantile Hydrocephalus: An Experience from Mali.

INTRODUCTION: Pediatric hydrocephalus is a common disease in sub-Saharan Africa. In Mali, 350-400 new cases are diagnosed in our center yearly. With a total land mass of 1,241,000 km2, patients in remote areas must travel up to 1,500 km to access neurosurgical care. Hence, treatment and follow-ups of "shunted" patients are difficult. In this context, endoscopic third ventriculostomy with choroid plexus cauterization (ETV/CPC) provides an opportunity for an affordable and less constraining treatment for hydrocephalus children under 12 months of age. METHODS: We performed a retrospective analysis of ETV/CPC performed on infants from July 2013 to January 2015. Patients were followed postoperatively on day 15, month 6, and month 12. Statistical analysis was conducted using Prism 9 GraphPad software. ETV successes were categorized according to the patient's age into 3 groups: ≤3 months, 3-6 months, and 6-12 months. Statistical significance was defined at p < 0.05. RESULTS: During the study period, 199 patients were included with 40% of patients aged between 0 and 6 months. The head circumference ranged from 35 cm to 79 cm. The etiology was congenital malformation in 55%. ETV/CPC was a success in 69% of 6- to 12-month-old patients, 54% in the 3- to 6-month-old patients, and 29% in ≤3-month-old patients. Overall, 94 (47%) patients were successfully treated without a shunt. The postoperative infection rate was 1% and mortality at 12 months was 8%. CONCLUSION: In a low-income environment such as Mali, ETV/CPC stands as a viable and alternative treatment option for pediatric hydrocephalus patients; our findings suggest that age is an important factor in predicting ETV success.

The effect of sampling health facilities on estimates of effective coverage: a simulation study.

BACKGROUND: Most existing facility assessments collect data on a sample of health facilities. Sampling of health facilities may introduce bias into estimates of effective coverage generated by ecologically linking individuals to health providers based on geographic proximity or administrative catchment. METHODS: We assessed the bias introduced to effective coverage estimates produced through two ecological linking approaches (administrative unit and Euclidean distance) applied to a sample of health facilities. Our analysis linked MICS household survey data on care-seeking for child illness and childbirth care with data on service quality collected from a census of health facilities in the Savanes region of Cote d'Ivoire. To assess the bias introduced by sampling, we drew 20 random samples of three different sample sizes from our census of health facilities. We calculated effective coverage of sick child and childbirth care using both ecological linking methods applied to each sampled facility data set. We compared the sampled effective coverage estimates to ecologically linked census-based estimates and estimates based on true source of care. We performed sensitivity analyses with simulated preferential care-seeking from higher-quality providers and randomly generated provider quality scores. RESULTS: Sampling of health facilities did not significantly bias effective coverage compared to either the ecologically linked estimates derived from a census of facilities or true effective coverage estimates using the original data or simulated random quality sensitivity analysis. However, a few estimates based on sampling in a setting where individuals preferentially sought care from higher-quality providers fell outside of the estimate bounds of true effective coverage. Those cases predominantly occurred using smaller sample sizes and the Euclidean distance linking method. None of the sample-based estimates fell outside the bounds of the ecologically linked census-derived estimates. CONCLUSIONS: Our analyses suggest that current health facility sampling approaches do not significantly bias estimates of effective coverage produced through ecological linking. Choice of ecological linking methods is a greater source of bias from true effective coverage estimates, although facility sampling can exacerbate this bias in certain scenarios. Careful selection of ecological linking methods is essential to minimize the potential effect of both ecological linking and sampling error.

Validity of using mobile phone surveys to evaluate community health worker program in Mali.

BACKGROUND: The monitoring and evaluation of public health programs based on traditional face-to-face interviews in hard-to-reach and unstable regions present many challenges. Mobile phone-based methods are considered to be an effective alternative, but the validity of mobile phone-based data for assessing implementation strength has not been sufficiently studied yet. Nested within an evaluation project for an integrated community case management (iCCM) and family planning program in Mali, this study aimed to assess the validity of a mobile phone-based health provider survey to measure the implementation strength of this program. METHODS: From July to August 2018, a cross-sectional survey was conducted among the community health workers (ASCs) from six rural districts working with the iCCM and family planning program. ASCs were first reached to complete the mobile phone-based survey; within a week, ASCs were visited in their communities to complete the in-person survey. Both surveys used identical implementation strength tools to collect data on program activities related to iCCM and family planning. Sensitivity and specificity were calculated for each implementation strength indicator collected from the phone-based survey, with the in-person survey as the gold standard. A threshold of ≥ 80% for sensitivity and specificity was considered adequate for evaluation purposes. RESULTS: Of the 157 ASCs interviewed by mobile phone, 115 (73.2%) were reached in person. Most of the training (2/2 indicators), supervision (2/3), treatment/modern contraceptive supply (9/9), and reporting (3/3) indicators reached the 80% threshold for sensitivity, while only one supervision indicator and one supply indicator reached 80% for specificity. In contrast, most of the stock-out indicators (8/9) reached 80% for specificity, while only two indicators reached the threshold for sensitivity. CONCLUSIONS: The validity of mobile phone-based data was adequate for general training, supervision, and supply indicators for iCCM and family planning. With sufficient mobile phone coverage and reliable mobile network connection, mobile phone-based surveys are useful as an alternative for data collection to assess the implementation strength of general activities in hard-to-reach areas.

The role of gender power relations on women's health outcomes: evidence from a maternal health coverage survey in Simiyu region, Tanzania.

BACKGROUND: Gender is a crucial consideration of human rights that impacts many priority maternal health outcomes. However, gender is often only reported in relation to sex-disaggregated data in health coverage surveys. Few coverage surveys to date have integrated a more expansive set of gender-related questions and indicators, especially in low- to middle-income countries that have high levels of reported gender inequality. Using various gender-sensitive indicators, we investigated the role of gender power relations within households on women's health outcomes in Simiyu region, Tanzania. METHODS: We assessed 34 questions around gender dynamics reported by men and women against 18 women's health outcomes. We created directed acyclic graphs (DAGs) to theorize the relationship between indicators, outcomes, and sociodemographic covariates. We grouped gender variables into four categories using an established gender framework: (1) women's decision-making, (2) household labor-sharing, (3) women's resource access, and (4) norms/beliefs. Gender indicators that were most proximate to the health outcomes in the DAG were tested using multivariate logistic regression, adjusting for sociodemographic factors. RESULTS: The overall percent agreement of gender-related indicators within couples was 68.6%. The lowest couple concordance was a woman's autonomy to decide to see family/friends without permission from her husband/partner (40.1%). A number of relationships between gender-related indicators and health outcomes emerged: questions from the decision-making domain were found to play a large role in women's health outcomes, and condoms and contraceptive outcomes had the most robust relationship with gender indicators. Women who reported being able to make their own health decisions were 1.57 times (95% CI: 1.12, 2.20) more likely to use condoms. Women who reported that they decide how many children they had also reported high contraception use (OR: 1.79, 95% CI: 1.34, 2.39). Seeking care at the health facility was also associated with women's autonomy for making major household purchases (OR: 1.35, 95% CI: 1.13, 1.62). CONCLUSIONS: The association between decision-making and other gender domains with women's health outcomes highlights the need for heightened attention to gender dimensions of intervention coverage in maternal health. Future studies should integrate and analyze gender-sensitive questions within coverage surveys.

Estimating population-based coverage of reproductive, maternal, newborn, and child health (RMNCH) interventions from health management information systems: a comprehensive review.

BACKGROUND: Routinely collected health facility data usually captured and stored in Health Management Information Systems (HMIS) are potential sources of data for frequent and local disaggregated estimation of the coverage of reproductive, maternal, newborn, and child health interventions (RMNCH), but have been under-utilized due to concerns over data quality. We reviewed methods for estimation of national or subnational coverage of RMNCH interventions using HMIS data exclusively or in conjunction with survey data from low- and middle-income countries (LMICs). METHODS: We conducted a comprehensive review of studies indexed in PubMed and Scopus to identify potential papers based on predefined search terms. Two reviewers screened the papers using defined inclusion and exclusion criteria. Following sequences of title, abstract and full paper reviews, we retained 18 relevant papers. RESULTS: 12 papers used only HMIS data and 6 used both HMIS and survey data. There is enormous lack of standards in the existing methods for estimating RMNCH intervention coverage; all appearing to be highly author dependent. The denominators for coverage measures were estimated using census, non-census and combined projection-based methods. No satisfactory methods were found for treatment-based coverage indicators for which the estimation of target population requires the population prevalence of underlying conditions. The estimates of numerators for the coverage measures were obtained from the count of users or visits and in some cases correction for completeness of reporting in the HMIS following an assessment of data quality. CONCLUSIONS: Standard methods for correcting numerators from HMIS data for accurate estimation of coverage of RMNCH interventions are needed to expand the use of these data. More research and investments are required to improve denominators for health facility-derived statistics. Improvement in routine data quality and analytical methods would allow for timely estimation of RMNCH intervention coverage at the national and subnational levels.

Measuring coverage of maternal and child health services using routine health facility data: a Sierra Leone case study.

BACKGROUND: There are limited existing approaches to generate estimates from Routine Health Information Systems (RHIS) data, despite the growing interest to these data. We calculated and assessed the consistency of maternal and child health service coverage estimates from RHIS data, using census-based and health service-based denominators in Sierra Leone. METHODS: We used Sierra Leone 2016 RHIS data to calculate coverage of first antenatal care contact (ANC1), institutional delivery and diphtheria-pertussis-tetanus 3 (DPT3) immunization service provision. For each indicator, national and district level coverages were calculated using denominators derived from two census-based and three health service-based methods. We compared the coverage estimates from RHIS data to estimates from MICS 2017. We considered the agreement adequate when estimates from RHIS fell within the 95% confidence interval of the survey estimate. RESULTS: We found an overall poor consistency of the coverage estimates calculated from the census-based methods. ANC1 and institutional delivery coverage estimates from these methods were greater than 100% in about half of the fourteen districts, and only 3 of the 14 districts had estimates consistent with the survey data. Health service-based methods generated better estimates. For institutional delivery coverage, five districts met the agreement criteria using BCG service-based method. We found better agreement for DPT3 coverage estimates using DPT1 service-based method as national coverage was close to survey data, and estimates were consistent for 8 out of 14 districts. DPT3 estimates were consistent in almost half of the districts (6/14) using ANC1 service-based method. CONCLUSION: The study highlighted the challenge in determining an appropriate denominator for RHIS-based coverage estimates. Systematic and transparent data quality check and correction, as well as rigorous approaches to determining denominators are key considerations to generate accurate coverage statistics using RHIS data.

Wealth-related inequalities in the coverage of reproductive, maternal, newborn and child health interventions in 36 countries in the African Region.

OBJECTIVE: To investigate whether sub-Saharan African countries have succeeded in reducing wealth-related inequalities in the coverage of reproductive, maternal, newborn and child health interventions. METHODS: We analysed survey data from 36 countries, grouped into Central, East, Southern and West Africa subregions, in which at least two surveys had been conducted since 1995. We calculated the composite coverage index, a function of essential maternal and child health intervention parameters. We adopted the wealth index, divided into quintiles from poorest to wealthiest, to investigate wealth-related inequalities in coverage. We quantified trends with time by calculating average annual change in index using a least-squares weighted regression. We calculated population attributable risk to measure the contribution of wealth to the coverage index. FINDINGS: We noted large differences between the four regions, with a median composite coverage index ranging from 50.8% for West Africa to 75.3% for Southern Africa. Wealth-related inequalities were prevalent in all subregions, and were highest for West Africa and lowest for Southern Africa. Absolute income was not a predictor of coverage, as we observed a higher coverage in Southern (around 70%) compared with Central and West (around 40%) subregions for the same income. Wealth-related inequalities in coverage were reduced by the greatest amount in Southern Africa, and we found no evidence of inequality reduction in Central Africa. CONCLUSION: Our data show that most countries in sub-Saharan Africa have succeeded in reducing wealth-related inequalities in the coverage of essential health services, even in the presence of conflict, economic hardship or political instability.

Diarrhea management in children under five in sub-Saharan Africa: does the source of care matter? A Countdown analysis.

BACKGROUND: Diarrhea remains a high burden disease, responsible for nine percent of deaths in children under five globally. We analyzed diarrhea management practices in young children and their association with the source of care. METHODS: We used Demographic and Health Survey data from 12 countries in sub-Saharan Africa with high burdens of childhood diarrhea. We classified the quality of diarrhea management practices as good, fair, or poor based on mothers' reports for children with diarrhea, using WHO/UNICEF recommendations for appropriate treatment. We described the prevalence of diarrhea management by type and assessed the association between good management and source of care, adjusting for potential confounders. RESULTS: Prevalence of good diarrhea management is low in 11 of the 12 analyzed surveys, varying from 17 % in Cote d'Ivoire to 38 % in Niger. The exception is Sierra Leone, where prevalence of good practice is 67 %. Prevalence of good management was low even among children taken to health facilities [median 52 %, range: 34-64 %]. Diarrhea careseeking from health facilities or community providers was associated with higher odds of good management than care from traditional/informal sources or no care. Careseeking from facilities did not result systematically in a higher likelihood of good diarrhea management than care from community providers. The odds of good diarrhea management were similar for community versus facility providers in six countries, higher in community than facility providers in two countries, and higher in facility than in community providers in four countries. CONCLUSION: Many children's lives can be saved with correct management of childhood diarrhea. Too many children are not receiving adequate care for diarrhea in high-burden sub-Saharan African countries, even among those seen in health facilities. Redoubling efforts to increase careseeking and improve quality of care for childhood diarrhea in both health facilities and at community level is an urgent priority.

Levels, trends and inequalities in mortality among 5-19-year-olds in Tanzania: Magu Health and Demographic Surveillance Study (1995-2022).

Background: For the past two decades, health priorities in Tanzania have focussed on children under-five, leaving behind the older children and adolescents (5-19 years). Understanding mortality patterns beyond 5 years is important in bridging a healthy gap between childhood to adulthood. We aimed to estimate mortality levels, trends, and inequalities among 5-19-year-olds using population data from the Magu Health and Demographic Surveillance Site (HDSS) in Tanzania and further compare the population level estimates with global estimates. Methods: Using data from the Magu HDSS from 1995 to 2022, from Kaplan Meir survival probabilities, we computed annual mortality probabilities for ages 5-9, 10-14 and 15-19 and determined the average annual rate of change in mortality by fitting the variance weighted least square regression on annual mortality probabilities. We compared 5-19 trends with younger children aged 1-4 years. We further disaggregated mortality by sex, area of residence and wealth tertiles, and we computed age-stratified risk ratios with respective 95% confidence intervals (CIs) using Cox proportional hazard model to determine inequalities. We further compared population-level estimates in all-cause mortality with global estimates from the United Nations Inter-agency Group for Child Mortality Estimation and the Global Burden of Disease study by computing the relative differences to the estimates. Results: Mortality declined steadily among the three age groups from 1995 to 2022, whereby the average annual rate of decline increased with age (2.2%, 2.7%, and 2.9% for 5-9-, 10-14-, and 15-19-year-old age groups, respectively). The pace of this decline was lower than that of younger children aged 1-4 years (4.8% decline). We observed significant mortality inequalities with boys, those residing in rural areas, and those from poorest wealth tertiles lagging behind. While Magu estimates were close to global estimates for the 5-9-year-old age group, we observed divergent results for adolescents (10-19 years), with Magu estimates lying between the global estimates. Conclusion: The pace of mortality decline was lower for the 5-19-year-old age group compared to younger children, with observable inequalities by socio-demographic characteristics. Determining the burden of disease across different strata is important in the development of evidence-based targeted interventions to address the mortality burden and inequalities in this age group, as it is an important transition period to adulthood.

Quality adjusted coverage of family planning services in low- and middle-income countries: Analysis of 33 countries using Demographic and Health Survey data.

Background: Monitoring service quality for family planning programmes in low- and middle-income countries (LMICs) has been challenging due to data availability. Self-reported service quality from Demographic and Health Surveys (DHS) can provide additional information on quality beyond simple service contact. Methods: The DHS collects need, use and counselling for contraceptives. We used this data from 33 LMICs to develop quality-adjusted demand for modern family planning satisfied indicator (DFPSq). We compared it with the crude indicator (demand for family planning satisfied (DFPS)) and performed an equity analysis. Median, interquartile ranges (IQR) and the absolute and relative gap by country were used to describe the findings. Results: The median DFPS was 49% (IQR = 41-57%) and the median DPFSq was 19% (IQR = 14-27%). We found similar relative differences in the gap stratified by SES indicating quality was universally low. One exception is that adolescents had a higher relative gap (70%, IQR = 57-79%) compared to adults (54%, IQR = 46-68%), indicating lower quality access. Conclusions: Severe and pervasive quality gaps exist in family planning services across most LMICs. Our novel DFPSq indicator is one additional tool for monitoring access and quality of service that is critical to meet the family planning needs of women.

Effective multi-sectoral approach for rapid reduction in maternal and neonatal mortality: the exceptional case of Bangladesh.

BACKGROUND: Bangladesh experienced impressive reductions in maternal and neonatal mortality over the past several decades with annual rates of decline surpassing 4% since 2000. We comprehensively assessed health system and non-health factors that drove Bangladesh's success in mortality reduction. METHODS: We operationalised a comprehensive conceptual framework and analysed available household surveys for trends and inequalities in mortality, intervention coverage and quality of care. These include 12 household surveys totalling over 1.3 million births in the 15 years preceding the surveys. Literature and desk reviews permitted a reconstruction of policy and programme development and financing since 1990. These were supplemented with key informant interviews to understand implementation decisions and strategies. RESULTS: Bangladesh prioritised early population policies to manage its rapidly growing population through community-based family planning programmes initiated in mid-1970s. These were followed in the 1990s and 2000s by priority to increase access to health facilities leading to rapid increases in facility delivery, intervention coverage and access to emergency obstetric care, with large contribution from private facilities. A decentralised health system organisation, from communities to the central level, openness to private for-profit sector growth, and efficient financing allocation to maternal and newborn health enabled rapid progress. Other critical levers included poverty reduction, women empowerment, rural development, and culture of data generation and use. However, recent empirical data suggest a slowing down of mortality reductions. CONCLUSION: Bangladesh demonstrated effective multi-sectoral approach and persistent programming, testing and implementation to achieve rapid gains in maternal and neonatal mortality reduction. The slowing down of recent mortality trends suggests that the country will need to revise its strategies to achieve the Sustainable Development Goals. As fertility reached replacement level, further gains in maternal and neonatal mortality will require prioritising universal access to quality facility delivery, and addressing inequalities, including reaching the rural poor.

Challenges in reducing maternal and neonatal mortality in Niger: an in-depth case study.

INTRODUCTION: Recent modelled estimates suggest that Niger made progress in maternal mortality since 2000. However, neonatal mortality has not declined since 2012 and maternal mortality estimates were based on limited data. We researched the drivers of progress and challenges. METHODS: We reviewed two decades of health policies, analysed mortality trends from United Nations data and six national household surveys between 1998 and 2021 and assessed coverage and inequalities of maternal and newborn health indicators. Quality of care was evaluated from health facility surveys in 2015 and 2019 and emergency obstetric assessments in 2011 and 2017. We determined the impact of intervention coverage on maternal and neonatal lives saved between 2000 and 2020. We interviewed 31 key informants to understand the factors underpinning policy implementation. RESULTS: Empirical maternal mortality ratio declined from 709 to 520 per 100 000 live births during 2000-2011, while neonatal mortality rate declined from 46 to 23 per 1000 live births during 2000-2012 then increased to 43 in 2018. Inequalities in neonatal mortality were reduced across socioeconomic and demographic strata. Key maternal and newborn health indicators improved over 2000-2012, except for caesarean sections, although the overall levels were low. Interventions delivered during childbirth saved most maternal and newborn lives. Progress came from health centre expansion, emergency care and the 2006 fee exemptions policy. During the past decade, challenges included expansion of emergency care, continued high fertility, security issues, financing and health workforce. Social determinants saw minimal change. CONCLUSIONS: Niger reduced maternal and neonatal mortality during 2000-2012, but progress has stalled. Further reductions require strategies targeting comprehensive care, referrals, quality of care, fertility reduction, social determinants and improved security nationwide.

The impact of the COVID-19 pandemic on trends in stillbirths, under-5 and maternal mortality in Brazil: Excess deaths and regional inequalities.

Background: Despite the proliferation of studies on the impact of the coronavirus disease 2019 (COVID-19) pandemic, there is less evidence on the indirect death toll compared to the health system and service provision disruptions. We assessed the impact of the COVID-19 pandemic on national and regional trends and differences in stillbirths, under-5 and maternal deaths in Brazil. Methods: We used the nationwide routine health information system data from January 2017 to December 2021, to which we applied descriptive and advanced mixed effects ordinary least squared regression models to measure the percent change in mortality levels during the COVID-19 pandemic (March 2020 to December 2021). We carried out counterfactual analyses comparing the observed and expected mortality levels for each type of mortality at national and regional levels. Results: Stillbirths increased 4.8% (3.1% in 2020 and 6.2% in 2021) and most noticeably maternal deaths increased 71.6% (35.3% in 2020 and 103.3% in 2021) over the COVID-19 period. An opposite pattern was observed in under-5 mortality, which dropped -10.2% (-12.5% in 2020 and -8.1% in 2021). We identified regional disparities, with a higher percent increase in stillbirths observed in the Central-West region and in maternal deaths in the South region. Discussion: Based on pre-pandemic trends and expected number of deaths in the absence of the COVID-19, we observed increases in stillbirths and maternal deaths and reductions in under-5 deaths during the pandemic. The months with the highest number of deaths (stillbirths and maternal deaths) coincided with the months with the highest mortality from COVID-19. The increase in deaths may also have resulted from indirect effects of the pandemic, such as unavailability of health services or even reluctance to go to the hospital when necessary due to fear of contagion. Conclusions: In Brazil, the COVID-19 outbreak and subsequent restrictions had a detrimental impact on stillbirths and maternal deaths. Even before the pandemic, mortality trends highlighted pre-existing regional inequalities in the country's health care system. Although there were some variations, increases were observed in all regions, indicating potential weaknesses in the health system and inadequate management during the pandemic, particularly concerning pregnant and postpartum women.

Use of a digital job-aid in improving antenatal clinical protocols and quality of care in rural primary-level health facilities in Burkina Faso: a quasi-experimental evaluation.

OBJECTIVE: We assessed the impact of a digital clinical decision support (CDS) tool in improving health providers adherence to recommended antenatal protocols and service quality in rural primary-level health facilities in Burkina Faso. DESIGN: A quasi-experimental evaluation based on a cross-sectional post-intervention assessment comparing the intervention district to a comparison group. SETTING AND PARTICIPANTS: The study included 331 direct observations and exit interviews of pregnant women seeking antenatal care (ANC) across 48 rural primary-level health facilities in Burkina Faso in 2021. INTERVENTION: Digital CDS tool to improve health providers adherence to recommended antenatal protocols. OUTCOME MEASURES: We analysed the quality of care on both the supply and demand sides. Quality-of-care service scores were based on actual care provided and expected care according to standards. Pregnant women's knowledge of counselling and satisfaction score after receiving care were also calculated. Other outcomes included time of clinical encounter. RESULTS: The overall quality of health service provision was comparable across intervention and comparison health facilities (52% vs 51%) despite there being a significantly higher proportion of lower skilled providers in the intervention arm (42.5% vs 17.8%). On average, ANC visits were longer in the intervention area (median 24 min, IQR 18) versus comparison area (median 12 min, IQR: 8). The intervention arm had a significantly higher score difference in women's knowledge of received counselling (16.4 points, 95% CI 10.37 to 22.49), and women's satisfaction (16.18 points, 95% CI: 9.95 to 22.40). CONCLUSION: Digital CDS tools provide a valuable opportunity to achieve substantial improvements of the quality of ANC and broadly maternal and newborn health in settings with high burden mortality and less trained health cadres when adequately implemented.

The RADAR coverage tool: developing a toolkit for rigorous household surveys for reproductive, maternal, newborn, and child health & nutrition indicators.

Population-based intervention coverage data are used to inform the design of projects, programs, and policies and to evaluate their impact. In low- and middle-income countries (LMICs), household surveys are the primary source of coverage data. Many coverage surveys are implemented by organizations with limited experience or resources in population-based data collection. We developed a streamlined survey and set of supporting materials to facilitate rigorous survey design and implementation. The RADAR coverage survey tool aimed to 1) rigorously measure priority reproductive, maternal, newborn, child health & nutrition coverage indicators, and allow for equity and gender analyses; 2) use standard, valid questions, to the extent possible; 3) be as light as possible; 4) be flexible to address users' needs; and 5) be compatible with the Lives Saved Tool for analysis of program impact. Early interactions with stakeholders also highlighted survey planning, implementation, and analysis as challenging areas. We therefore developed a suite of resources to support implementers in these areas. The toolkit was piloted by implementers in Tanzania and in Burkina Faso. Although the toolkit was successfully implemented in these settings and facilitated survey planning and implementation, we found that implementers must still have access to sufficient resources, time, and technical expertise in order to use the tool appropriately. This potentially limits the use of the tool to situations where high-quality surveys or evaluations have been prioritized and adequately resourced.

Measuring and monitoring child health and wellbeing: recommendations for tracking progress with a core set of indicators in the Sustainable Development Goals era.

Although great improvements in child survival were achieved in the past two decades, progress has been uneven within and across countries, and the COVID-19 pandemic threatens to reverse previous advances. Demographic and epidemiological transitions around the world have resulted in shifts in the causes and distribution of child death and diseases, and many children are living with short-term and long-term chronic illnesses and disabilities. These changes, plus global threats such as pandemics, transnational and national security issues, and climate change, mean that regular monitoring of child health and wellbeing is essential if we are to achieve the Sustainable Development Goals. This Health Policy describes the three-phased process undertaken by the Child Health Accountability Tracking technical advisory group (CHAT) to develop a core set of indicators on child health and wellbeing for global monitoring purposes, and presents CHAT's research recommendations to address data gaps. CHAT reached consensus on 20 core indicators specific to the health sector, which include 11 impact-level indicators and nine outcome-level indicators that cover the topics of: acute conditions and prevention; health promotion and child development; and chronic conditions, disabilities, injuries, and violence against children. An additional six indicators (three impact and three outcome) that capture information on child health issues such as malaria and HIV are recommended; however, these indicators are only relevant to high-burden regions. CHAT's four research priorities will require investments in health information systems and measurement activities. These investments will help to increase data on children aged 5-9 years; develop standard metadata and data collection processes to enable cross-country comparisons and progress assessments over time; reach a global consensus on essential interventions and associated indicators for monitoring emerging priority areas such as child development, chronic conditions, disabilities, and injuries; and implement strategies to increase the uptake of data on child health to improve evidence-based planning, programming, and advocacy efforts.