Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Their burden remains highest in lower income settings and is accelerated by climate change and rapid urbanization. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease understanding. While the first generation of generative models have focussed on exploiting large and diverse datasets in higher income settings, more recent developments in AI have shown better performance in data-limited settings.
A first stage of work at the institute will evaluate the extent to which pre-trained generative AI models are able to reconstruct and predict trajectories of infectious disease outbreaks of major public health relevance integrating multi-modal data sources from across African countries. A second stage will look at adapting current modelling frameworks via feedback from stakeholders to improve the accuracy and actionability of outputs generated from these models. Throughout the fellowship I will work closely with country partners from West, Southern, and Eastern Africa and regional centres (WHO Afro, Africa CDC), convening workshops on public health decision making in the era of AI.