Estimating chlamydia re-infection rates: an empirical example
- Elizabeth A Torrone1,2,
- Catherine L Satterwhite1,
- Delia Scholes3,
- Onchee Yu3,
- Stuart Berman4,
- Thomas A Peterman1
- 1Division of STD Prevention, Centers for Disease Control and Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Atlanta, Georgia, USA
- 2Division of Applied Sciences, Epidemic Intelligence Service, Centers for Disease Control and Prevention, Scientific Education and Professional Development Program Office, Atlanta, Georgia, USA
- 3Group Health Research Institute, Group Health Cooperative, Seattle, Washington, USA
- 4Centers for Disease Control and Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Atlanta, Georgia, USA
- Correspondence to Dr Elizabeth A Torrone, Division of STD Prevention, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, M/S E-02, Atlanta, GA 30333;
- Received 10 December 2012
- Revised 26 March 2013
- Accepted 6 April 2013
- Published Online First 4 May 2013
Objective Chlamydia re-infection data are used to inform and evaluate chlamydia control programmes. We quantitatively investigated the effect of denominator selection on estimating re-infection rates and trends.
Methods Using data on women aged 15–44 years enrolled in Group Health Cooperative (GH), a Pacific Northwest health plan, annual chlamydia re-infection rates from 1998 to 2006 were calculated. Three different denominators were compared using person-years contributed by: (1) all women; (2) women with a prior documented chlamydial infection regardless of whether they were retested; and (3) women with a prior chlamydial infection who were retested within 14 months.
Results From 1998 to 2006, among all women 15–44 years enrolled in GH, re-infection rates increased from 64 to 149 cases per 100 000 person-years. Among women with a prior infection, rates decreased from 10 857 to 8782 cases per 100 000 person-years. Among women with a prior infection who were retested, rates increased from 29 374 to 42 475 cases per 100 000 person-years.
Conclusions Using the same dataset, we demonstrate that it is possible to tell three different stories about the magnitude of rates and trends in chlamydia re-infection among women by using different denominators. All of these strategies have limitations, but restricting the denominator to women with a prior infection who are retested may best represent the population at-risk for re-infection. Still, rates do not account for additional factors influencing the number of re-infections diagnosed, including screening coverage and changes in test technology. Caution is needed in examining and comparing re-infection data.