Impact of a potential Chlamydia vaccine in the USA: mathematical modelling analyses

Chlamydia trachomatis(CT) infection is a global health challenge. New approaches are needed to control CT disease burden.An age-structured deterministic mathematical model calibrated to nationally representative population-based data was developed to investigate the impact of CT vaccination on the population of the USA if a vaccine becomes available. The model’s parameters were chosen based on current knowledge from the literature on CT’s natural history and epidemiology. The model’s calibration used age-specific CT prevalence data sourced from the biannual rounds of the National Health and Nutrition Examination Surveys. The reported data are based on the outcomes generated by the model’s simulations.Over a 10-year period, vaccinating 80% of individuals aged 15–49 with a vaccine that reduces by 50% susceptibility to infection (VES=50%), infectiousness (VEI=50%) or duration of infection (VEP=50%) resulted, respectively, in 36.3%, 26.5% and 42.1% reduction in CT prevalence, and 38.8%, 28.6% and 24.1% reduction in CT incidence rate. Number of averted infections was 11 346 000, 7 583 000 and 6 012 000, respectively. When efficacies acted together (VES=VEI=VEP=50%), CT prevalence and incidence rate were reduced by 66.3% and 61.0%, respectively. Number of vaccinations needed to avert one infection was 17.7 forVES=50%, 26.5 forVEI=50%, 33.4 forVEP=50%and 12.0 forVES=VEI=VEP=50%. Vaccinating individuals aged 15–19 and at highest risk of infection was most effective, requiring only 7.7 and 1.8 vaccinations to prevent one infection, respectively. Vaccination benefits were larger beyond 10 years.A moderately efficacious CT vaccine can significantly reduce CT disease burden. Targeting specific populations can maximise cost-effectiveness. Additional potential ‘breakthrough’ effects of the vaccine on infectiousness and duration of infection could greatly increase its impact. CT vaccine development and implementation should be a public health priority.