Abstract:
Ebola has emerged as a threat to public health in Africa after a major outbreak occurred in West Africa in 2014. Efforts to prevent further transmission are underway in Africa and the world at large. Mathematical models are key tools in deriving new knowledge and guiding decisions before and after the occurrence of diseases. In this project, we develop and simulate mathematical models of Ebola to investigate the dynamics and effects of various prevention and control strategies, and investigate the minimum effort needed for a targeted type host to prevent the Ebola disease for informed decisions. We revisited an ordinary differential equation model of Ebola epidemic and extend it to incorporate community, hospitals, and funeral components, necessary categorization for the Ebola transmission dynamics and control. The models were analysed and numerically simulated to investigate effects of prevention and control. Control of this disease should be immediate, as many individuals would die within a few days if nothing is done. Hospital closure, efficient treatment, and vaccination of healthcare workers have a greater impact and potentially eradicate Ebola from the community. Therefore, results suggest that, the effect of control measures are dependent on the type of intervention and group of people that it targets. Although the results presented in this report are based on the assumptions of the models developed, results are useful to consider when designing interventions. This work has highlighted the importance of mathematical models in the generating essential knowledge for evidence based decisions and for designing better ways of controlling Ebola. Keywords: Ebola, Reproduction number, Simulation, Intervention, Control.
