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

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

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.

Suggested Citation

  • Diaz, Paul & Constantine, Paul & Kalmbach, Kelsey & Jones, Eric & Pankavich, Stephen, 2018. "A modified SEIR model for the spread of Ebola in Western Africa and metrics for resource allocation," Applied Mathematics and Computation, Elsevier, vol. 324(C), pages 141-155.
    • Handle: RePEc:eee:apmaco:v:324:y:2018:i:c:p:141-155
    DOI: 10.1016/j.amc.2017.11.039
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    References listed on IDEAS

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    1. Constantine, Paul G. & Diaz, Paul, 2017. "Global sensitivity metrics from active subspaces," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 1-13.
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    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Ebola

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    Cited by:

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    2. Dantas, Eber & Tosin, Michel & Cunha Jr, Americo, 2018. "Calibration of a SEIR–SEI epidemic model to describe the Zika virus outbreak in Brazil," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 249-259.
    3. Cen Song & Sijia Zhou & Kyle Hunt & Jun Zhuang, 2022. "Comprehensive Evolution Analysis of Public Perceptions Related to Pediatric Care: A Sina Weibo Case Study (2013–2020)," SAGE Open, , vol. 12(1), pages 21582440221, March.
    4. Dun, Han & Shuting, Yan & She, Han & Lingfei, Qian & Chris, Ampimah Benjamin, 2019. "Research on how the difference of personal propagation ability influences the epidemic spreading in activity-driven network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 311-318.
    5. Abdallah Al-Husban & Noureddine Djenina & Rania Saadeh & Adel Ouannas & Giuseppe Grassi, 2023. "A New Incommensurate Fractional-Order COVID 19: Modelling and Dynamical Analysis," Mathematics, MDPI, vol. 11(3), pages 1-16, January.
    6. Kar, T.K. & Nandi, Swapan Kumar & Jana, Soovoojeet & Mandal, Manotosh, 2019. "Stability and bifurcation analysis of an epidemic model with the effect of media," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 188-199.
    7. Wang, Jinling & Jiang, Haijun & Ma, Tianlong & Hu, Cheng, 2019. "Global dynamics of the multi-lingual SIR rumor spreading model with cross-transmitted mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 148-157.
    8. Liu, Liya & Jiang, Daqing & Hayat, Tasawar, 2021. "Dynamics of an SIR epidemic model with varying population sizes and regime switching in a two patch setting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).

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