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Insights into the timing of repeated testing after treatment for Chlamydia trachomatis: data and modelling study.

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Publication date 2013
Author Heijne Janneke Cornelia Maria, Herzog Sereina Annik, Althaus Christian Lorenz, Tao Guoyu, Kent Charlotte Kathleen, Low Nicola,
Project Acute and chronic dynamics of HIV and HCV infections, within-host evolution and epidemiological outcomes
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Original article (peer-reviewed)

Journal Sexually transmitted infections
Volume (Issue) 89(1)
Page(s) 57 - 62
Title of proceedings Sexually transmitted infections
DOI 10.1136/sextrans-2011-050468


OBJECTIVES The objective of this study was to determine the optimal time interval for a repeated Chlamydia trachomatis (chlamydia) test. METHODS The authors used claims data for US women aged 15-25 years who were enrolled in commercial health insurance plans in the MarketScan database between 2002 and 2006. The authors determined the numbers of initial positive and negative tests that were followed by a repeated test and the positivity of repeated tests. The authors used a dynamic transmission pair model that reflects the partnership formation and separation processes in 15-25 year olds to determine the time course of repeated infections in women under different levels of notifying the current partner. The authors then explored the additional impact of repeated testing uptake on reducing chlamydia prevalence. RESULTS 40% (4949/12 413) of positive tests were followed by a repeated test compared with 22% (89 119/402 659) of negative tests at any time. Positivity of repeated tests followed by an initial positive test was high: 15% (736) after a positive test versus 3% (2886) after a negative test. The transmission model showed a peak in repeated infections between 2 and 5 months after treatment. For a chlamydia testing uptake of 10% per year, the additional impact of repeated testing on reducing chlamydia population prevalence was modest. CONCLUSIONS The mathematical model predictions support the recommended interval for repeat chlamydia testing. This study provides information that can be used to design randomised controlled trials to determine more effective interventions to prevent chlamydial reinfection.