| Description |
The Sub-Saharan Africa (SSA) region has the worst health conditions, on average, in the world. The reasons for poor health conditions for people in SSA are complex and vary at different individual, household, community, and government jurisdiction levels within this region. The majority of people in this region live in rural communities and practice subsistence farming. Agriculture in rural SSA is fundamental to achieving significant health benefits, sustainable development, poverty reduction, and food security in SSA. This research focuses on both health and farming methods in Burkina Faso. I performed three studies using geospatial analysis and remote sensing techniques to examine health demand for healthcare facilities, farming methods and malnutrition in rural Burkina Faso, Africa. The first chapter provides a methodology that utilizes health data in Burkina Faso to demonstrate how spatial analysis can be used to identify areas of health demand for healthcare facilities. Factors used to locate demand per administrative province included population density, proximity to major road networks, economic wealth index, birth rate, childhood stunting, and malaria rates. Major health issues in populated areas along access routes ultimately determined the estimated demand for healthcare facility locations in this analysis. The second chapter analyzes modeling maximum NDVI values using environmental factors for both conventional and water harvesting farms. The results suggest that environmental variables had a different impact on crops yields for the different farming methods. Water harvesting farms were iv less dependent on precipitation than conventional farming methods. The third chapter focuses on the correlation between malnutrition and farming methods. This study analyzes if there is a correlation between healthier children in the rural areas of Burkina Faso and innovative farming methods based on the clustering of farming methods within Demographic Health Survey (DHS) locations using a multilevel regression model. The results suggest that areas where there is a high concentration of water harvesting farms are significantly negatively correlated with stunting. |
