This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Van der Ploeg, C. P. B. Articles by Habbema, J. D. F. Search for Related Content

STDSIM: A Microsimulation Model for Decision Support in STD Control

Centre for Decision Sciences in Tropical Disease Control, Erasmus University Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
Centre for Decision Sciences in Tropical Disease Control, Erasmus University Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
Centre for Decision Sciences in Tropical Disease Control, Erasmus University Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
Department of Medical Microbiology, University of Nairobi, PO Box 19676, Nairobi, Kenya
Commission of the European Communities, Rue de la Loi 200, B-1049 Brussels, Belgium
Centre for Decision Sciences in Tropical Disease Control, Erasmus University Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands
Centre for Decision Sciences in Tropical Disease Control, Erasmus University Rotterdam, PO Box 1738, 3000 DR Rotterdam, The Netherlands

STDSIM is a dynamic stochastic simulation model for decision support in attempts to control sexually transmitted diseases (STDs). It describes the mechanisms responsible for the transmission of five STDs, including HIV/AIDS, at the level of individuals. A large variety of outcome measures (for example, STD prevalence, incidence, and mortality) can be calculated for different groups of the population (for example, adolescents, prostitutes, pregnant women, and migrants) to evaluate the effects of alternative STD control interventions. We designed the model to support decision making for different settings in developing countries, with Nairobi (Kenya) as its first application area. The model adequately describes STD prevalences and the time-trend of HIV prevalence measured in Nairobi. As an illustration of the possibilities of the model, we show model predictions of the effects of improved STD care and increased condom use on the prevalence and incidence of HIV.

Key Words: decision analysis; applications; health care; epidemiology

This article has been cited by other articles:

				E L Korenromp, R Bakker, R Gray, M J Wawer, D Serwadda, and J D F Habbema The effect of HIV, behavioural change, and STD syndromic management on STD epidemiology in sub-Saharan Africa: simulations of Uganda Sex Transm Inf, April 1, 2002; 78(90001): i55 - 63. [Abstract] [Full Text] [PDF]

				R. S. Bernstein, D. C. Sokal, S. T. Seitz, B. Auvert, J. Stover, and W. Naamara Simulating the Control of a Heterosexual HIV Epidemic in a Severely Affected East African City Interfaces, May 1, 1998; 28(3): 101 - 126. [Abstract] [PDF]