Open AccessIncorporating individual health-protective decisions into disease transmission models: a mathematical framework
Author(s) -
David P. Durham,
Elizabeth A. Casman
Publication year - 2011
Publication title -
journal of the royal society interface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.655
H-Index - 139
eISSN - 1742-5689
pISSN - 1742-5662
DOI - 10.1098/rsif.2011.0325
Subject(s) - disease , transmission (telecommunications) , computer science , situational ethics , infectious disease (medical specialty) , disease transmission , outbreak , interpretation (philosophy) , management science , epidemic model , mathematical model , computational model , risk analysis (engineering) , operations research , artificial intelligence , medicine , psychology , environmental health , social psychology , virology , mathematics , engineering , population , pathology , telecommunications , statistics , programming language
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.
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