Estimating c-section coverage: Assessing method performance and characterizing variations in coverage.

Background: Cesarean section (c-section) is an essential tool for preventing, stillbirths, maternal, and newborn death. However, data on coverage of medically necessary c-section is limited in low- and middle-income settings. Methods: We estimated national c-section coverage using household survey data from 98 low- and middle-income countries. To disaggregate elective and medically necessary c-sections, we estimated the proportion of women in each survey wealth quintile who gave birth via c-section assuming a denominator that 12.5% of births necessitate a c-section delivery. We capped stratum coverage at 100%. We estimated national c-section coverage weighting for the proportion of births occurring in each wealth quintile. We examined 1) variation in estimated c-section by wealth quintile, national income classification, and stage in the obstetric transition, 2) how varying definitions impact the classification of countries' access to c-section, and 3) correlation between c-section and related mortality outcomes. Results: Both increasing national and household wealth are associated with increasing levels of c-section coverage and c-section rate. C-section coverage was highly inequitable by wealth within a country. Differentials in coverage were most pronounced in countries with c-section rates below 10%; however, some countries showed significant gaps in c-section coverage in poor subpopulations despite high c-section rates nationally. The choice of indicator and threshold altered whether a country was classified as having adequate access to c-section services. C-section coverage estimates showed a stronger relationship with closely related health outcomes than national c-section rates. Conclusions: Generating estimates of c-section coverage is crucial for gauging gaps in c-section access. Our approach for calculating c-section coverage using stratification by wealth to adjust for potential elective c-sections is supported by the strong correlations between household wealth and subnational c-section rate, and the association between our coverage estimates and health outcomes at a national level. Looking at national c-section rates alone may paint an inaccurate picture of c-section access and mask subnational inequities in coverage. The need to accurately measure access to c-section will continue to increase as growth in LMICs drives inequities in coverage and introduces dual concerns related to c-section overuse in some populations while others lack access to care.

Estimating the health impact of vaccination against ten pathogens in 98 low-income and middle-income countries from 2000 to 2030: a modelling study.

BACKGROUND: The past two decades have seen expansion of childhood vaccination programmes in low-income and middle-income countries (LMICs). We quantify the health impact of these programmes by estimating the deaths and disability-adjusted life-years (DALYs) averted by vaccination against ten pathogens in 98 LMICs between 2000 and 2030. METHODS: 16 independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever. Using standardised demographic data and vaccine coverage, the impact of vaccination programmes was determined by comparing model estimates from a no-vaccination counterfactual scenario with those from a reported and projected vaccination scenario. We present deaths and DALYs averted between 2000 and 2030 by calendar year and by annual birth cohort. FINDINGS: We estimate that vaccination of the ten selected pathogens will have averted 69 million (95% credible interval 52-88) deaths between 2000 and 2030, of which 37 million (30-48) were averted between 2000 and 2019. From 2000 to 2019, this represents a 45% (36-58) reduction in deaths compared with the counterfactual scenario of no vaccination. Most of this impact is concentrated in a reduction in mortality among children younger than 5 years (57% reduction [52-66]), most notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 120 million (93-150) deaths will be averted by vaccination, of which 58 million (39-76) are due to measles vaccination and 38 million (25-52) are due to hepatitis B vaccination. We estimate that increases in vaccine coverage and introductions of additional vaccines will result in a 72% (59-81) reduction in lifetime mortality in the 2019 birth cohort. INTERPRETATION: Increases in vaccine coverage and the introduction of new vaccines into LMICs have had a major impact in reducing mortality. These public health gains are predicted to increase in coming decades if progress in increasing coverage is sustained. FUNDING: Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.

Early estimates of the indirect effects of the COVID-19 pandemic on maternal and child mortality in low-income and middle-income countries: a modelling study.

BACKGROUND: While the COVID-19 pandemic will increase mortality due to the virus, it is also likely to increase mortality indirectly. In this study, we estimate the additional maternal and under-5 child deaths resulting from the potential disruption of health systems and decreased access to food. METHODS: We modelled three scenarios in which the coverage of essential maternal and child health interventions is reduced by 9·8-51·9% and the prevalence of wasting is increased by 10-50%. Although our scenarios are hypothetical, we sought to reflect real-world possibilities, given emerging reports of the supply-side and demand-side effects of the pandemic. We used the Lives Saved Tool to estimate the additional maternal and under-5 child deaths under each scenario, in 118 low-income and middle-income countries. We estimated additional deaths for a single month and extrapolated for 3 months, 6 months, and 12 months. FINDINGS: Our least severe scenario (coverage reductions of 9·8-18·5% and wasting increase of 10%) over 6 months would result in 253 500 additional child deaths and 12 200 additional maternal deaths. Our most severe scenario (coverage reductions of 39·3-51·9% and wasting increase of 50%) over 6 months would result in 1 157 000 additional child deaths and 56 700 additional maternal deaths. These additional deaths would represent an increase of 9·8-44·7% in under-5 child deaths per month, and an 8·3-38·6% increase in maternal deaths per month, across the 118 countries. Across our three scenarios, the reduced coverage of four childbirth interventions (parenteral administration of uterotonics, antibiotics, and anticonvulsants, and clean birth environments) would account for approximately 60% of additional maternal deaths. The increase in wasting prevalence would account for 18-23% of additional child deaths and reduced coverage of antibiotics for pneumonia and neonatal sepsis and of oral rehydration solution for diarrhoea would together account for around 41% of additional child deaths. INTERPRETATION: Our estimates are based on tentative assumptions and represent a wide range of outcomes. Nonetheless, they show that, if routine health care is disrupted and access to food is decreased (as a result of unavoidable shocks, health system collapse, or intentional choices made in responding to the pandemic), the increase in child and maternal deaths will be devastating. We hope these numbers add context as policy makers establish guidelines and allocate resources in the days and months to come. FUNDING: Bill & Melinda Gates Foundation, Global Affairs Canada.

Linking household survey and health facility data for effective coverage measures: a comparison of ecological and individual linking methods using the Multiple Indicator Cluster Survey in Côte d'Ivoire.

BACKGROUND: Population-based measures of intervention coverage are used in low- and middle-income countries for program planning, prioritization, and evaluation. There is increased interest in effective coverage, which integrates information about service quality or health outcomes. Approaches proposed for quality-adjusted effective coverage include linking data on need and service contact from population-based surveys with data on service quality from health facility surveys. However, there is limited evidence about the validity of different linking methods for effective coverage estimation. METHODS: We collaborated with the 2016 Côte d'Ivoire Multiple Indicator Cluster Survey (MICS) to link data from a health provider assessment to care-seeking data collected by the MICS in the Savanes region of Côte d'Ivoire. The provider assessment was conducted in a census of public and non-public health facilities and pharmacies in Savanes in May-June 2016. We also included community health workers managing sick children who served the clusters sampled for the MICS. The provider assessment collected information on structural and process quality for antenatal care, delivery and immediate newborn care, postnatal care, and sick child care. We linked the MICS and provider data using exact-match and ecological linking methods, including aggregate linking and geolinking methods. We compared the results obtained from exact-match and ecological methods. RESULTS: We linked 731 of 786 care-seeking episodes (93%) from the MICS to a structural quality score for the provider named by the respondent. Effective coverage estimates computed using exact-match methods were 13%-63% lower than the care-seeking estimates from the MICS. Absolute differences between exact match and ecological linking methods were ±7 percentage points for all ecological methods. Incorporating adjustments for provider category and weighting by service-specific utilization into the ecological methods generally resulted in better agreement between ecological and exact match estimates. CONCLUSIONS: Ecological linking may be a feasible and valid approach for estimating quality-adjusted effective coverage when a census of providers is used. Adjusting for provider type and caseload may improve agreement with exact match results. There remain methodological questions to be addressed to develop guidance on using linking methods for estimating quality-adjusted effective coverage, including the effect of facility sampling and time displacement.