This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Schroeder, K. D. Articles by Rojas, F. G. Search for Related Content Social Bookmarking                         What's this?

A Game Theoretical Analysis of Sexually Transmitted Disease Epidemics

807 1/5 N. Poinsettia Pl., Los Angeles, CA 90046, USA

Fabio G. Rojas

Office 350, NORC and the University of Chicago, 1155 E. 60th St., Chicago, IL 60637, USA fgrojas{at}harper.uchicago.edu

Social scientists who study sexual behavior have consistently found that some HIV-infected individuals continue to have unprotected sex with uninfected partners. In this article, we address three questions that stem from this empirical finding. First, what can game theory contribute to the study of sexual behavior? Second, can a person deduce the HIV status of a potential sexual partner from observed behavior? Third, what are the implications of a game theoretic analysis for infection rate dynamics? Briefly, we argue that game theory models capture the interactive aspects of sexual behavior such as signalign status through behavior. We then go on to show that some simple signaling game models predict that behavior does not distinguish infected from uninfected partners. In those models, uninfected individuals will engage in high-risk sex with potentially infected partners if the perceived rate of infection is sufficiently low. Otherwise, they engage in low-risk sex. The final section of the article analyses an epidemiological model where individuals play the signaling game in discrete time periods. Simulations of the model under varying conditions show that the most virulent epidemics occur when individuals randomly select partners but base their estimate of the infection rate on the percentage of socially close individuals who are infected. Simulations also show that epidemics where individuals restrict partners slow the spread of disease more than other models but that the epidemic lasts longer. Another implication is that with replacement, infection rates will oscillate because individuals will switch from low- to high-risk sex as the percentage of infected individuals changes. We conclude by discussing empirically testable predictions of the model.

Key Words: epidemic models • game theory • HIV • computational model • signaling games

Rationality and Society, Vol. 14, No. 3, 353-383 (2002)
DOI: 10.1177/1043463102014003004


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				A. M. Francis and H. M. Mialon The Optimal Penalty for Sexually Transmitting HIV Am. Law Econ. Rev., September 1, 2008; 10(2): 388 - 423. [Abstract] [Full Text] [PDF]