Cristina Bradatan , Texas Tech University
Sharmistha Swain, Texas Tech University
Xiaopeng Song, Texas Tech University
Brandon Wagner, Texas Tech University
This project analyzes how malaria prevalence is influenced by socioeconomic factors, climate anomalies, deforestation, and access to treatment in Sub Saharan Africa. Biomarkers of malaria prevalence, treatment availability and socio-economic data are measured at two points in time, from cross sectional, nationally representative biomarkers and social data covering 350 million people in Sub Saharan Africa. These health data (together with demographic, social and economic information) will be further linked to high-resolution precipitation, temperature and deforestation information. Spatial regression models will then be employed to analyze the effects these covariates have on malaria prevalence. The research will advance the understanding of the connections between malaria prevalence and socio-economic factors/ access to treatment. While there is a wealth of literature focused on the climate- malaria link, there is no large-scale study in which all the most relevant factors (climate, land changes, socio-economic characteristics and access to treatment) are studied together on a large, nationally representative, scale.
Presented in Session P10. Health Consequences of Environmental and Climate Change