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on the rates among women: a network modelling study for high-prevalence communities.

Abstract

(Ct) is the most commonly reported sexually transmitted infection in the USA and causes important reproductive morbidity in women. The Centers for Disease Control and Prevention recommend routine screening of sexually active women under age 25 but not among men. Despite three decades of screening women, chlamydia prevalence in women remains high. Untested and untreated men can serve as a reservoir of infection in women, and male-screening based intervention can be an effective strategy to reduce infection in women. We assessed the impact of screening men on the Ct prevalence in women.

We created an individual-based network model to simulate a realistic chlamydia epidemic on sexual contact networks for a synthetic population (n=5000). The model is calibrated to the ongoing routine screening among African American (AA) women in the USA and detailed a male-screening programme, Check It, that bundles best practices for Ct control. We used sensitivity analysis to quantify the relative importance of each intervention component.

Heterosexual AA men, aged 15 to 24, who had sex with women in the past 2 months.

Community-based venues in New Orleans, Louisiana, USA.

The findings indicated that male-screening has the potential to substantially reduce the prevalence among women in high-prevalence communities.

Venue-based screening, expedited index treatment, expedited partner treatment and rescreening.

We estimate that by annually screening 7.5% of the AA male population in the age-range, the chlamydia prevalence would be reduced relatively by 8.1% (95% CI 5.9% to 10.4%) in AA women and 8.8% (95% CI 6.9% to 10.8%) in AA men. Each man screened could prevent 0.062 (95% CI 0.030 to 0.094) cases in men and 0.204 (95% CI 0.143 to 0.267) cases in women. The model suggested the importance of intervention components ranked from high to low as venue-based screening, expedited index treatment, expedited partner treatment and rescreening.

MIDAS Network Members

Zhuolin Qu

Assistant Professor
University of Texas at San Antonio

Citation:

Qu Z, Azizi A, Schmidt N, Craig-Kuhn MC, Stoecker C, Hyman JM, Kissinger PJ. (2021). on the rates among women: a network modelling study for high-prevalence communities. BMJ open, 11(1)