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A modified SEIR model for the spread of Ebola in Western Africa and metrics for resource allocation

Paul Diaz, Paul Constantine, Kelsey Kalmbach, Eric Jones and Stephen Pankavich

Applied Mathematics and Computation, 2018, vol. 324, issue C, 141-155

Abstract: A modified, deterministic SEIR model is developed for the 2014 Ebola epidemic occurring in the West African nations of Guinea, Liberia, and Sierra Leone. The model describes the dynamical interaction of susceptible and infected populations, while accounting for the effects of hospitalization and the spread of disease through interactions with deceased, but infectious, individuals. Using data from the World Health Organization (WHO), parameters within the model are fit to recent estimates of infected and deceased cases from each nation. The model is then analyzed using these parameter values. Finally, several metrics are proposed to determine which of these nations is in greatest need of additional resources to combat the spread of infection. These include local and global sensitivity metrics of both the infected population and the basic reproduction number with respect to rates of hospitalization and proper burial.

Keywords: Epidemiology; Ebola; Uncertainty quantification; Active subspaces; Stability (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:eee:apmaco:v:324:y:2018:i:c:p:141-155