Incorporating individual health-protective decisions into disease transmission models: a mathematical framework
Identifieur interne : 002362 ( Ncbi/Merge ); précédent : 002361; suivant : 002363Incorporating individual health-protective decisions into disease transmission models: a mathematical framework
Auteurs : David P. Durham [États-Unis] ; Elizabeth A. Casman [États-Unis]Source :
- Journal of the Royal Society Interface [ 1742-5689 ] ; 2011.
Abstract
It is anticipated that the next generation of computational epidemic models will simulate both infectious disease transmission and dynamic human behaviour change. Individual agents within a simulation will not only infect one another, but will also have situational awareness and a decision algorithm that enables them to modify their behaviour. This paper develops such a model of behavioural response, presenting a mathematical interpretation of a well-known psychological model of individual decision making, the health belief model, suitable for incorporation within an agent-based disease-transmission model. We formalize the health belief model and demonstrate its application in modelling the prevalence of facemask use observed over the course of the 2003 Hong Kong SARS epidemic, a well-documented example of behaviour change in response to a disease outbreak.
Url:
DOI: 10.1098/rsif.2011.0325
PubMed: 21775324
PubMed Central: 3262418
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PMC:3262418Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>It is anticipated that the next generation of computational epidemic models will simulate both infectious disease transmission and dynamic human behaviour change. Individual agents within a simulation will not only infect one another, but will also have situational awareness and a decision algorithm that enables them to modify their behaviour. This paper develops such a model of behavioural response, presenting a mathematical interpretation of a well-known psychological model of individual decision making, the health belief model, suitable for incorporation within an agent-based disease-transmission model. We formalize the health belief model and demonstrate its application in modelling the prevalence of facemask use observed over the course of the 2003 Hong Kong SARS epidemic, a well-documented example of behaviour change in response to a disease outbreak.</p>
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Author for correspondence (<email>ddurham@alumni.cmu.edu</email>
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<abstract><p>It is anticipated that the next generation of computational epidemic models will simulate both infectious disease transmission and dynamic human behaviour change. Individual agents within a simulation will not only infect one another, but will also have situational awareness and a decision algorithm that enables them to modify their behaviour. This paper develops such a model of behavioural response, presenting a mathematical interpretation of a well-known psychological model of individual decision making, the health belief model, suitable for incorporation within an agent-based disease-transmission model. We formalize the health belief model and demonstrate its application in modelling the prevalence of facemask use observed over the course of the 2003 Hong Kong SARS epidemic, a well-documented example of behaviour change in response to a disease outbreak.</p>
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<kwd-group><kwd>epidemiological modelling</kwd>
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