Introduction Chlamydia trachomatis (Ct) genital infection is the most commonly reported bacterial infection in the United States (US). High-risk groups include women<25 years. Untreated infections may lead to pelvic inflammatory disease and infertility. Most infections are asymptomatic, so screening high-risk women is important. The US National Commission on Prevention Priorities ranked annual Ct screening of sexually active women as one of the top 10 prevention strategies. The Army screens women <25 yearly, and Ct is reportable. Ct incidence dropped from 2011 ((109/1000 person-years (py)) to 2012 (86/1000 py). A search for artifactual contributions found the proportion of specimens submitted that tested positive remained stable, but screening rates dropped. Subsequently, screening rates improved. During 2012–2014, the reported Ct annual incidence stabilised, averaging 86/1000 py. However, Ct incidence for 2015 increased to 92/1000 py, prompting another review of the relationship between reported Ct incidence and screening rates.
Methods Incidence rates were compiled from Ct reports in non-deployed Soldiers submitted to the military Disease Reporting System-internet. Screening rates were obtained from the Military Health System Population Health Portal. To deal with variations in screening, modelled incidence projections were developed to reflect a theoretical 100% screening compliance.
Results Incidence projections confirmed a decrease in the 2011–2014 modelled incidence/1000 py: 2011–129, 2012–?121, 2013–114 and 2014–109. The modelled Ct incidence for 2015 increased to 114/1000 py. The screening rate fell from a high of 85% in 2011 to a low of 71% in 2012, with subsequent improvement to 81% in 2015.
Conclusion Reported Ct incidence in Army women is related to the actual infection rate and the percentage of at-risk women screened. Ct surveillance programs must review medical report and screening data to improve burden estimates. Incidence projections help assess the magnitude of observed surveillance changes and identify the probable number of missed infections.
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