P031 Estimating local chlamydia incidence and prevalence using surveillance data. (30th June 2016)

• Record Type: Journal Article
• Authors: Lewis, Joanna; White, Peter
• Is Part Of: Sexually transmitted infections. Volume 92(2016)Supplement 1
• Page Start: A29
• Page End: A30
• Publication Date: 2016-06-30
• Subjects: Sexually transmitted diseases -- Periodicals; HIV infections -- Periodicals; 616.951005
• DOI: 10.1136/sextrans-2016-052718.85
• Languages: English
• ISSNs: 1368-4973

Abstract

Abstract : Background/introduction: Understanding patterns of chlamydia prevalence is important for addressing inequalities and assessing interventions. Population-based surveys are expensive; the best UK data come from the Natsal national surveys which are only available once per decade and not powered to compare prevalence in different localities. Estimates at finer spatial and temporal scales are required. Aim(s)/objectives: We aimed to estimate chlamydia prevalence from numbers of tests and diagnoses reported in surveillance data. Methods: Our method is based on a simple model for the infection, testing and treatment processes and informed by the literature on infection natural history and treatment seeking behaviour. By combining this information with surveillance data we obtain estimates of chlamydia screening rates, incidence and prevalence. We validate and illustrate the method by application to national and local-level data from England. Results: Estimates of national prevalence by sex and age group agree with results from the Natsal-3 survey. They could be improved by additional information on the number of diagnoses that were symptomatic. There is substantial local-level variation in prevalence, with more infection in deprived areas. Incidence in each sex is strongly correlated with prevalence in the other. Importantly, we find that positivity (the proportion of tests which were positive) does not provide a reliable proxy for prevalence. Discussion/conclusion: This approach provides a powerful tool to identify prevalence trends with time and location, and understand the effects of control strategies. Estimates could be more accurate if surveillance systems recorded which patients were symptomatic and the duration of symptoms before care-seeking.