Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models

Social distancing, vaccination, and medical treatments have been extensively studied and widely used to control the spread of infectious diseases. However, it is still a difficult task for health administrators to determine the optimal combination of these strategies when confronting disease outbrea...

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Main Authors: Geisel Alpízar, Luis F. Gordillo
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2013/681689
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author Geisel Alpízar
Luis F. Gordillo
author_facet Geisel Alpízar
Luis F. Gordillo
author_sort Geisel Alpízar
collection DOAJ
description Social distancing, vaccination, and medical treatments have been extensively studied and widely used to control the spread of infectious diseases. However, it is still a difficult task for health administrators to determine the optimal combination of these strategies when confronting disease outbreaks with limited resources, especially in the case of interconnected populations, where the flow of individuals is usually restricted with the hope of avoiding further contamination. We consider two coupled populations and examine them independently under two variants of well-known discrete time disease models. In both examples we compute approximations for the control levels necessary to minimize costs and quickly contain outbreaks. The main technique used is simulated annealing, a stochastic search optimization tool that, in contrast with traditional analytical methods, allows easy implementation to any number of patches with different kinds of couplings and internal dynamics.
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spelling doaj-art-c685cb0707df48c5a292a82a75c9c5cf2025-02-03T01:33:28ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2013-01-01201310.1155/2013/681689681689Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time ModelsGeisel Alpízar0Luis F. Gordillo1Departamento de Matemáticas, Instituto Tecnológico de Costa Rica, Cartago 30101, Costa RicaDepartment of Mathematics and Statistics, Utah State University, Logan, UT 84322, USASocial distancing, vaccination, and medical treatments have been extensively studied and widely used to control the spread of infectious diseases. However, it is still a difficult task for health administrators to determine the optimal combination of these strategies when confronting disease outbreaks with limited resources, especially in the case of interconnected populations, where the flow of individuals is usually restricted with the hope of avoiding further contamination. We consider two coupled populations and examine them independently under two variants of well-known discrete time disease models. In both examples we compute approximations for the control levels necessary to minimize costs and quickly contain outbreaks. The main technique used is simulated annealing, a stochastic search optimization tool that, in contrast with traditional analytical methods, allows easy implementation to any number of patches with different kinds of couplings and internal dynamics.http://dx.doi.org/10.1155/2013/681689
spellingShingle Geisel Alpízar
Luis F. Gordillo
Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models
Discrete Dynamics in Nature and Society
title Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models
title_full Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models
title_fullStr Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models
title_full_unstemmed Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models
title_short Disease Spread in Coupled Populations: Minimizing Response Strategies Costs in Discrete Time Models
title_sort disease spread in coupled populations minimizing response strategies costs in discrete time models
url http://dx.doi.org/10.1155/2013/681689
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