Patch models of EVD transmission dynamics

Bruce Pell, Javier Baez, Tin Phan, Daozhou Gao, Gerardo Chowell, Yang Kuang

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

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 inWest 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.

Original languageEnglish (US)
Title of host publicationMathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases
PublisherSpringer International Publishing
Pages147-167
Number of pages21
ISBN (Electronic)9783319404134
ISBN (Print)9783319404110
DOIs
StatePublished - Jan 1 2016

Keywords

  • Behavior change
  • Bootstrap
  • Ebola
  • Infectious disease forecasting
  • Logistic equation
  • Patchmodel

ASJC Scopus subject areas

  • Mathematics(all)
  • Medicine(all)

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