Patch Models of EVD Transmission Dynamics

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

A chapter in Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases, 2016, pp 147-167 from Springer

Abstract: 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.

Keywords: Logistic equation; Infectious disease forecasting; Patch model; Ebola; Behavior change; Bootstrap (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-40413-4_10

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DOI: 10.1007/978-3-319-40413-4_10

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