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Modelling Ebola within a community

  • R. N. LEANDER (a1), W. S. GOFF (a1), C. W. MURPHY (a1) and S. A. PULIDO (a1)
Abstract
SUMMARY

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.

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Corresponding author
*Author for correspondence: Professor R. N. Leander, Department of Mathematical Sciences,Middle Tennessee State University, Murfreesboro, TN 37132, USA. (Email: rachel.leander@mtsu.edu)
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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

1. World Health Organization Ebola Response Team. Ebola virus disease in West Africa: the first 9 months of the epidemic and forward projections. New England Journal of Medicine 2014; 371: 14811495.

12. H McCallum , N Barlow , J Hone . How should pathogen transmission be modeled? Trends in Ecology and Evolution 2001; 16: 295300.

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Epidemiology & Infection
  • ISSN: 0950-2688
  • EISSN: 1469-4409
  • URL: /core/journals/epidemiology-and-infection
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