A Nonhomogeneous Agent-Based Simulation Approach to Modeling the Spread of Disease in a Pandemic Outbreak

Dionne M. Aleman (), Theodorus G. Wibisono () and Brian Schwartz ()
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Dionne M. Aleman: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada
Theodorus G. Wibisono: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada
Brian Schwartz: Ontario Agency for Health Protection and Promotion, Toronto, Ontario M5G 1V2, Canada; Department of Family and Community Medicine, University of Toronto, Toronto, Ontario M5S 3G8, Canada

Interfaces, 2011, vol. 41, issue 3, 301-315

Abstract: To effectively prepare for a pandemic disease outbreak, knowledge of how the disease will spread is paramount. The global outbreak of severe acute respiratory syndrome (SARS) in 2002--2003 highlighted the need for such data. This need is also apparent in preparing for and responding to all disease outbreaks, from pandemic influenza to avian flu. Many previous studies of disease make simplistic assumptions about transmission and infection rates and assume that each member of the population is identical or homogeneous. We propose an agent-based simulation model that treats each individual as unique, with nonhomogeneous transmission and infection rates correlated to demographic information and behavior. The results of the model are output to geographic information system software to provide a map of the estimated disease spread area, which can be used as a policy-making tool for determining a suitable mitigation strategy. The Ontario Agency for Health Protection and Promotion (OAHPP) uses the model for pandemic planning for the Greater Toronto area in Ontario, Canada.

Keywords: pandemic; influenza; SARS; disease spread; agent-based simulation; nonhomogeneous mixing model (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (7)

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