This research protocol describes the CHEAQI–MNCH project, which forms part of the HE²AT Center’s broader efforts to strengthen data science capacity and generate policy-relevant evidence for health in Africa. Published in the Journal of Global Health Economics and Policy, the study will develop and validate air pollution proxy indicators using data from Kenya, The Gambia and Mozambique to examine the impacts of air quality on maternal, newborn and child health outcomes across sub-Saharan Africa.
By combining geospatial methods, machine learning and existing cohort and clinical trial data, the project aims to address critical evidence gaps in settings where air quality monitoring remains limited. The project also seeks to build a sustainable data science ecosystem, strengthen analytical capacity among early-career researchers, and support knowledge translation through collaboration with partners, policymakers and data providers.
Read more:
Munthali, L., Mushore, T. D., Nyoni, H. B., et al. (2026). Characterizing effects of air quality in maternal, newborn and child health (CHEAQI–MNCH) in sub-Saharan Africa: A research protocol. Journal of Global Health Economics and Policy, 6, e2026004.

