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Patch Models of EVD Transmission Dynamics

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

Author

Listed:
  • Bruce Pell

    (Arizona State)

  • Javier Baez

    (Arizona State)

  • Tin Phan

    (Arizona State)

  • Daozhou Gao

    (Shanghai Normal University, Mathematics and Science College)

  • Gerardo Chowell

    (Georgia State University, School of Public Health)

  • Yang Kuang

    (Arizona State)

Abstract

Mathematical models have the potential to be useful to forecast the course of epidemics. In this chapter, a family of logistic patch models are preliminarily evaluated for use in disease modeling and forecasting. Here we also derive the logistic equation in an infectious disease transmission context based on population behavior and used it for forecasting the trajectories of the 2013–2015 Ebola epidemic in West Africa. The logistic model is then extended to include spatial population heterogeneity by using multi-patch models that incorporate migration between patches and logistic growth within each patch. Each model’s ability to forecast epidemic data was assessed by comparing model forecasting error, parameter distributions and parameter confidence intervals as functions of the number of data points used to calibrate the models. The patch models show an improvement over the logistic model in short-term forecasting, but naturally require the estimation of more parameters from limited data.

Suggested Citation

  • Bruce Pell & Javier Baez & Tin Phan & Daozhou Gao & Gerardo Chowell & Yang Kuang, 2016. "Patch Models of EVD Transmission Dynamics," Springer Books, in: Gerardo Chowell & James M. Hyman (ed.), Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases, pages 147-167, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-40413-4_10
    DOI: 10.1007/978-3-319-40413-4_10
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