Women in sub-Saharan African countries have the highest maternal mortality ratios globally. This is due to factors (obstacles) which make women vulnerable: environmental, socio-demographic, disease burden, poor access to and low-quality healthcare, suboptimal health-seeking, and dysfunctional health systems. This project examines the variation of ~30 factors across 20 sub-Saharan African cities (conurbations) and construct a maternal health vulnerability index  to identify areas with concurrent disadvantages across space and time (2000–2024). The project makes use of satellite imagery, national household surveys, and socio-demographic data within a suite of advanced geospatial methods with robust validation.  The outputs will be shared with the scientific community and policymaking stakeholders to inform actions to reduce maternal deaths in urban settings of sub-Saharan African countries.

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This study has six objectives:

1. To conceptualize a “conurbation”- a city with its adjoining suburbs and satellite towns – as a unit of analysis for urban maternal health vulnerability and to estimate urbanicity values in each conurbation across time and space for the 20 sub-Saharan African conurbations.

2. To estimate within-conurbation distribution of factors associated with maternal health vulnerability at 1km2 spatial resolution using model-based geostatistics.

3. To model travel time to the nearest emergency obstetric care facility within each conurbation at 20m2 spatial resolution using least cost-path algorithms.

4. To generate relative weights for each maternal health vulnerability index factor (within each conurbation and across all 20 conurbations) using analytical hierarchical process via an online survey.

5. To apply the relative weights (from objective 4) to the factors and generate values of the maternal health vulnerability index at 1km2 spatial resolution within each conurbation.

6. To assess external and context validity of the maternal health vulnerability index using independent secondary and primary data from Lubumbashi (DRC) in order to inform generalizability to other conurbations.