Abstract:
Saharan dust and BM incidence are strongly correlated. Peaks in PM10 concentrations, low
humidity, and high temperature precede meningitis outbreaks by 2 to 4 weeks, especially in the
Sahelian zone.
ENSO influence West African dust variability through modulation of synoptic systems. During
El Niño, weakened Azores High and reduced pressure gradients lead to lower dust activity.
During La Niña or positive NAO phases, the Azores High strengthens, intensifying dust
transport. In addition, due to the Siberian High enhancing the north-south pressure gradient
during winter, Harmattan wind strength increases and promotes dry, dusty airflow over the
region.
Predictive models using climate and environmental variables provide early warning with 2–3
weeks lead time. Machine learning models like Machine learning models like XGBoost in
Nigeria, CatBoost in Burkina Faso) highlight vaccination, RH, and meridional wind as the most
influential predictors across countries.
Description:
A Thesis submitted to the West African Science Service Centre on Climate Change and Adapted Land Use and the Federal University of Technology, Akure, Nigeria, in partial fulfillment of the requirements for the degree of Doctor of Philosophy Degree in West African Climate Systems
