title: Modelling Ebola within a community.
abstract: The 2014 Ebola epidemic was the largest on record. It evidenced the need for improved models of the spread of Ebola. In this research we focus on modelling Ebola within a small village or community. Specifically, we investigate the potential of basic Susceptible-Exposed-Infectious-Recovered (SEIR) models to describe the initial Ebola outbreak, which occurred in Meliandou, Guinea. Data from the World Health Organization is used to compare the accuracy of various models in order to select the most accurate models of transmission and disease-induced responses. Our results suggest that (i) density-dependent transmission and mortality-induced behavioural changes shaped the course of the Ebola epidemic in Meliandou, while (ii) frequency-dependent transmission, disease-induced emigration, and infection-induced behavioural changes are not consistent with the data from this epidemic.
authors.affiliation: Department of Mathematical Sciences,Middle Tennessee State University,Murfreesboro,TN,USA.
authors.forename: R N
authors.initials: RN
authors.lastname: Leander
authors.affiliation: Department of Mathematical Sciences,Middle Tennessee State University,Murfreesboro,TN,USA.
authors.forename: W S
authors.initials: WS
authors.lastname: Goff
authors.affiliation: Department of Mathematical Sciences,Middle Tennessee State University,Murfreesboro,TN,USA.
authors.forename: C W
authors.initials: CW
authors.lastname: Murphy
authors.affiliation: Department of Mathematical Sciences,Middle Tennessee State University,Murfreesboro,TN,USA.
authors.forename: S A
authors.initials: SA
authors.lastname: Pulido
mesh_terms: D004196:Disease Outbreaks; D029043:Ebolavirus / Q000502:physiology*; D005843:Geography; D016701:Guinea / Q000453:epidemiology; D019142:Hemorrhagic Fever, Ebola / Q000453:epidemiology* / Q000635:transmission / Q000821:virology; D006801:Humans; D008962:Models, Theoretical; D011156:Population Density
keywords: Ebola virus; modelling