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15 March 2005

Volume 191, Number 6
The Journal of Infectious Diseases 2005;191:899–906
© 2005 by the Infectious Diseases Society of America. All rights reserved.
0022-1899/2005/19106-0011$15.00
DOI: 10.1086/427661
MAJOR ARTICLE

Identification of Networks of Sexually Transmitted Infection: A Molecular, Geographic, and Social Network Analysis

John L. Wylie,1,2

Teresa Cabral,1 and

Ann M. Jolly3,4

1Department of Medical Microbiology, University of Manitoba, and 2Cadham Provincial Laboratory, Manitoba Health, Winnipeg, Manitoba, and 3Centre for Infectious Disease Prevention and Control, Population and Public Health Branch, Health Canada, and 4Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada.

Background.Despite widespread efforts to control it, Chlamydia trachomatis remains the most frequently diagnosed bacterial sexually transmitted infection (STI). Analysis of sexual networks has been proposed as a novel tool for control of and research into STI. In the present study, we combine molecular genotype data, analysis of geographic clusters, and sociodemographic descriptors to facilitate analysis of large sexual networks.

Methods.Individual chlamydia genotypes found in Manitoba, Canada, were analyzed to identify geographic clusters, and the identified clusters were further characterized by statistical analysis of sociodemographic variables.

Results.A total of 10 geographic clusters of chlamydia‐genotype infection were identified. Clusters in Winnipeg showed no or little geographic overlap and could be further differentiated on the basis of the sociodemographic characteristics of the individuals within a cluster. Several clusters in northern Manitoba overlapped geographically but, nonetheless, could be differentiated on the basis of the sociodemographic characteristics of the infected individuals.

Conclusions.On the basis of results of the combined analyses, each geographic cluster appeared to represent a relatively distinct transmission network within the larger sexual network. The geographic analysis of the molecular data provided a basis for establishment of potential epidemiological connections between small groups of unlinked individuals. Analytic approaches of the type described here would help to decipher the patterns that exist within large social network data sets and would be applicable to many types of infectious agents.

Received 21 July 2004; accepted 8 September 2004; electronically published 14 February 2005.

Reprints or correspondence: John L. Wylie, Cadham Provincial Laboratory, PO Box 8450, Winnipeg, Manitoba, Canada R3C 3Y1 ().

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  • Presented in part: International Society for Sexually Transmitted Diseases Research Congress, Ottawa, Ontario, Canada, 27–30 July 2003.

    Financial support: Manitoba Health Research Council; Manitoba Medical Services Foundation.

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