title: Incorporating individual health-protective decisions into disease transmission models: a mathematical framework.
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.
authors.affiliation: Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA. ddurham@alumni.cmu.edu
authors.forename: David P
authors.initials: DP
authors.lastname: Durham
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Casman
mesh_terms: D003198:Computer Simulation; D003657:Decision Making / Q000502:physiology*; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D015438:Health Behavior; D007722:Health Knowledge, Attitudes, Practice; D006723:Hong Kong / Q000453:epidemiology; D006801:Humans; D008397:Masks / Q000706:statistics & numerical data*; D008960:Models, Psychological; D045169:Severe Acute Respiratory Syndrome / Q000453:epidemiology* / Q000635:transmission*