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.

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.

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.