Events

Date: 19 February 2026   Time: 14:00 - 15:00

Location: Hybrid: MB503, SMS, QMUL, or via the Teams link below

High-resolution risk maps of infectious diseases such as Guinea worm disease (GWD, dracunculiasis) are crucial to guide the planning, implementation and monitoring of intervention strategies, including water treatment with Abate™ and surveillance activities. Maps help to identify transmission hotspots, optimize resource allocation and support adaptation to evolving disease dynamics. The map production process can also help to identify environmental, demographic and socioeconomic factors that characterise disease suitability. Despite their demonstrated utility, risk maps for GWD are currently unavailable for most endemic countries, except Chad. In this talk, I will present a study which addresses this gap by developing a hybrid geostatistical and machine learning modelling framework for producing 1x1 km risk maps of GWD and associated uncertainties in six endemic countries: Chad, South Sudan, Ethiopia, Mali, Angola and Cameroon. The methodology is implemented in a Bayesian framework using the INLA-SPDE approach and predictive performance evaluated using both random and spatially stratified cross-validation. Initial results reveal temporal changes in the drivers of disease transmission, as well as pronounced spatial and spatiotemporal patterns in infection risk. These also highlight transmission hotspots and estimate populations at risk to support targeted programmatic action.
My talk will also include introductions to the WorldPop and VaxPop projects.

Short Bio: Dr C. Edson Utazi is an Associate Professor of Spatial Data Science in the School of Geography and Environmental Science at the University of Southampton. He holds a PhD in Statistics from Lancaster University, where his doctoral research focused on the spatiotemporal modelling of partially observed processes. His research spans Bayesian modelling and computation, spatial and spatiotemporal statistics and time series analysis. He joined the University of Southampton in 2014 as a Research Fellow in Statistics with the WorldPop research program. His current work focuses on the development of spatiotemporal statistical methods to quantify health inequalities, including infectious disease prevalence and vaccination coverage in low- and middle-income countries (LMICs). He currently leads WorldPop's VaxPop project, which produces high-resolution estimates of vaccination coverage, along with corresponding estimates of zero-dose and under-vaccinated children, to inform vaccination strategies in priority countries.