Statistical data analysis of the 1995 Ebola outbreak in the Democratic Republic of Congo

Ebola is a lethal viral hemorrhagic fever with the potential to cause major epidemics. We analyse the 1995 outbreak in the Democratic Republic of Congo using two sets of data (onset and death data). Numerical simulations showed that the model fits the observed onset Ebola data at 99.95% and the observed death data at 98.6%. Since Bayesian inference cannot be performed analytically for complex models, Markov Chain Monte Carlo algorithm is then used as the second approach to obtain a solution. Results obtained from both approaches are contrasted and compared. © 2011 African Mathematical Union and Springer-Verlag.