An agent-based platform for simulating the impact of chlamydia vaccine in the US population
Qi Deng1,2, Grégoire Ranson2,3, Nicola Luigi Bragazzi2,4,5
1Centre of Excellence in Artificial Intelligence for Public Health Advancement, York University, Toronto, Canada.
Abstract:
Chlamydia trachomatis (CT) remains the most reported bacterial sexually transmitted infection in the United States (US), underscoring the urgent need for an effective vaccine. An agent-based model calibrated to the US National Survey of Family Growth (NSFG) and National Health and Nutrition Examination Survey (NHANES) datasets was developed and used to study the impact of vaccine on the CT and all-cause pelvic inflammatory disease (PID) burden. The model was further validated against independent epidemiological data. Here we show that a conventional vaccine with 50% efficacy and 60% coverage can achieve a 64.2% [95%CI: 43.0-68.1] reduction in chlamydia prevalence and a 14.3% [95%CI: 10.1-29.4] reduction in the prevalence of women with one or more lifetime episodes of all-cause PID. Prioritizing vaccination among individuals aged 15-24 yielded the greatest impact, even with moderate vaccine performance, highlighting the importance of age-targeted, gender-inclusive strategies. These findings provide quantitative evidence to support the design and implementation of chlamydia vaccination programs and highlight the value of agent-based modeling frameworks for evaluating complex intervention strategies in sexually transmitted infections.
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