Sexual partnerships between people at higher and lower risk for sexually transmitted infections (STIs) (i.e., bridging) occur through dissortative mixing and concurrent partnerships, yet the relative effects of these network patterns on population STI spread are poorly understood.
Using a stochastic model, the authors investigated the impact of mixing and concurrency on the spread of a persistent viral STI.
A total of 1050 populations were simulated of 1000 subjects over 400 weeks with varied concurrency levels and mixing patterns. STI prevalence and the average number of secondary transmissions per subject were analyzed with regression.
Mixing had a greater impact on prevalence for all groups, whereas concurrency was significant for only the lowest activity group. Mixing patterns moderated the magnitude of concurrency’s impact on secondary transmissions.
Through connecting subgroups of differential risk, sexual mixing facilitates dissemination of STIs throughout a population. Concurrency expedites transmission by shortening the time between sexual contacts among infected and susceptible persons, particularly during the highly infectious period.
A mathematical simulation of sexual networks demonstrated the relative effects of sexual mixing patterns and concurrency levels on viral sexually transmitted infection (STI) transmission. Mixing facilitates and concurrency expedites STI spread.
From the *School of Medicine, University of North Carolina, Chapel Hill, North Carolina; the Departments of †Obstetrics/Gynecology and Reproductive Sciences and ‡Epidemiology and Biostatistics, University of California, San Francisco, California; and the §Department of Pediatrics, Johns Hopkins University, Baltimore, Maryland
The development of this model and the drafting of the manuscript were funded through grants from the National Institute of Allergy and Infectious Diseases (R01-AI48749 and 5 T32 AI007151-27). The authors thank Richard Rothenberg, Steve Selvin, Sevgi Aral, and Jennifer Smith for their helpful suggestions during various phases of this work.
Correspondence: Irene A Doherty, PhD, Postdoctoral Fellow, Division of Infectious Diseases, BioInformatics Bldg., 130 Mason Farm Road, CB 7030, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7030. E-mail: Doherty@med.unc.edu.
Received for publication June 30, 2005, and accepted October 21, 2005.