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Transmission Dynamics and Final Epidemic Size of Ebola Virus Disease Outbreaks with Varying Interventions

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  • Maria Vittoria Barbarossa
  • Attila Dénes
  • Gábor Kiss
  • Yukihiko Nakata
  • Gergely Röst
  • Zsolt Vizi

Abstract

The 2014 Ebola Virus Disease (EVD) outbreak in West Africa was the largest and longest ever reported since the first identification of this disease. We propose a compartmental model for EVD dynamics, including virus transmission in the community, at hospitals, and at funerals. Using time-dependent parameters, we incorporate the increasing intensity of intervention efforts. Fitting the system to the early phase of the 2014 West Africa Ebola outbreak, we estimate the basic reproduction number as 1.44. We derive a final size relation which allows us to forecast the total number of cases during the outbreak when effective interventions are in place. Our model predictions show that, as long as cases are reported in any country, intervention strategies cannot be dismissed. Since the main driver in the current slowdown of the epidemic is not the depletion of susceptibles, future waves of infection might be possible, if control measures or population behavior are relaxed.

Suggested Citation

  • Maria Vittoria Barbarossa & Attila Dénes & Gábor Kiss & Yukihiko Nakata & Gergely Röst & Zsolt Vizi, 2015. "Transmission Dynamics and Final Epidemic Size of Ebola Virus Disease Outbreaks with Varying Interventions," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, July.
    • Handle: RePEc:plo:pone00:0131398
    DOI: 10.1371/journal.pone.0131398
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    References listed on IDEAS

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    1. Phenyo E. Lekone & Bärbel F. Finkenstädt, 2006. "Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study," Biometrics, The International Biometric Society, vol. 62(4), pages 1170-1177, December.
    2. John M Drake & RajReni B Kaul & Laura W Alexander & Suzanne M O’Regan & Andrew M Kramer & J Tomlin Pulliam & Matthew J Ferrari & Andrew W Park, 2015. "Ebola Cases and Health System Demand in Liberia," PLOS Biology, Public Library of Science, vol. 13(1), pages 1-20, January.
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    Cited by:

    1. Robin N Thompson & Christopher A Gilligan & Nik J Cunniffe, 2016. "Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-18, April.
    2. Max S Y Lau & Gavin J Gibson & Hola Adrakey & Amanda McClelland & Steven Riley & Jon Zelner & George Streftaris & Sebastian Funk & Jessica Metcalf & Benjamin D Dalziel & Bryan T Grenfell, 2017. "A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak," PLOS Computational Biology, Public Library of Science, vol. 13(10), pages 1-18, October.

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