Laboratory Detection of First and Repeat Chlamydia Cases Influenced by Testing Patterns: A Population-Based Study.

Objectives: The purpose of this study was to describe and explore potential driving factors of trends in reported chlamydia infections over time in Manitoba, Canada.

Methods: Surveillance and laboratory testing data from Manitoba Health, Seniors and Active Living were analysed using SAS v9.4. Kaplan-Meier plots of time from the first to second chlamydia infection were constructed, and Cox proportional hazards regression was used to estimate the risk of second repeat chlamydia infections in males and females.

Results: Overall, the number of reported infections found mirrored the number of tests conducted. From 2008 to 2014, the number of first infections found among females decreased as the number of first tests conducted among females also decreased. Between 2008 and 2012, the number of repeat tests among females increased and was accompanied by an increase in the number of repeat positive results from 2009 to 2013. From 2008 to 2016, the number of repeat tests and repeat positive results increased steadily among males.

Conclusions: Chlamydia infection rates consistently included a subset composed of repeat infections. The number of cases identified appears to mirror testing volumes, drawing into question incidence calculations that do not include testing volumes.

Summary box: 1) What is the current understanding of this subject? Chlamydia incidence is high in Manitoba, particularly among young women and in northern Manitoba.2) What does this report add to the literature? This report suggests that incidence calculated using case-based surveillance data alone does not provide an accurate estimate of chlamydia incidence in Manitoba and is heavily influenced by testing patterns.3) What are the implications for public health practice? In general, improving testing rates in clinical practices as well as through the provision of rapid services in non-clinical venues could result in higher screening and treatment rates. In turn, this could lead to a better understanding of true disease occurrence.