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Med Decis Making. 2012 Sep-Oct;32(5):712-21.

Dynamic transmission modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-5.

Author information

1
Oxford Outcomes, Oxford, United Kingdom (RP)
2
Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (DF)
3
Ivey School of Business, University of Western Ontario, London, Canada (GSZ)
4
Unit of PharmacoEpidemiology and PharmacoEconomics, Department of Pharmacy, University of Groningen, Groningen, Netherlands (MP)
5
Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, and Center for Infectious Disease Control, RIVM, Bilthoven, Netherlands (MK)
6
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom (JE)
7
URESP, Centre de Recherche FRSQ du CHA Universitaire de Que´ bec and De´ partement de Me´ decine Sociale et Pre´ ventive, Laval University, Quebec City, Canada (MB)

Abstract

The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the population, will change over time, and will feed back into the future force of infection. These nonlinear interactions produce transmission dynamics that require specific consideration when modeling an intervention that has an impact on the transmission of a pathogen. Best practices for designing and building these models are set out in this paper.

PMID:
22990086
DOI:
10.1177/0272989X12454578
[Indexed for MEDLINE]

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