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Modeling the Impact of Behavior Change on the Spread of Ebola

In: Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases

Author

Listed:
  • Jessica R. Conrad

    (Tulane University, Department of Mathematics)

  • Ling Xue

    (Tulane University, Department of Mathematics)

  • Jeremy Dewar

    (Tulane University, Department of Mathematics)

  • James M. Hyman

    (Tulane University, Department of Mathematics)

Abstract

We create a compartmental mathematical model to analyze the role of behavior change in slowing the spread of the Ebola virus disease (EVD) in the 2014–2015 Western Africa epidemic. Our model incorporates behavior change, modeled as decreased contact rates between susceptible and infectious individuals, the prevention of traditional funerals, and/or increased access to medical facilities. We derived the basic reproductive number for the model, and approximated the parameter values for the spread of the EVD in Monrovia. We used sensitivity analysis to quantify the relative importance of the timing, and magnitude, of the population reducing their contact rates, avoiding the traditional burial practices, and having access to medical treatment facilities. We found that reducing the number of contacts made by infectious individuals in the general population is the most effective intervention method for mitigating an EVD epidemic. While healthcare interventions delayed the onset of the epidemic, healthcare alone is insufficient to stop the epidemic in the model.

Suggested Citation

  • Jessica R. Conrad & Ling Xue & Jeremy Dewar & James M. Hyman, 2016. "Modeling the Impact of Behavior Change on the Spread of Ebola," Springer Books, in: Gerardo Chowell & James M. Hyman (ed.), Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases, pages 5-23, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-40413-4_2
    DOI: 10.1007/978-3-319-40413-4_2
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