Alpha Forna

Research Postgraduate
a.forna16 [at]

Alpha's research aims to understand sub-national level trajectories of Ebola Virus Disease (EVD) in West Africa, and the influence of health worker distribution during the epidemic.
He is investigating factors that could be associated with the Pre/Post-Ebola clinical outcomes of survivors and if these also show sub-national variations. Presently, he is using a machine learning (Boosted regression trees) model to impute the outcome (i.e. survival or death) of Ebola cases in the WHO line-list data collected during the West African Ebola outbreak in 2013-2015. The observed and imputed outcomes will improve the current estimates of the case fatality ratio. His PhD is supervised by Imperial's Professor Christl Donnelly, Dr Pierre Nouvellet and Dr Ilaria Dorigatti.