The proposed research harnesses data science applications to establish the spatial variability in the impact of ambient PM2.5 exposure on children's health in Sub-Saharan Africa (SSA) and further identify the explanatory and moderating factors. The proposed research is relevant as it focuses on leveraging data science tools to address a very pressing public health problem in Africa in line with the overarching goals of the DSI-Africa program. The proposed research will enhance public health data science capacity on the continent and with the findings triggering investment in air pollution control as well as policy action for addressing area and household poverty to help improve child health and survival in SSA.