STI epidemic re-emergence, socio-epidemiological clusters characterisation and HIV coinfection in Catalonia, Spain, during 2017-2019: a retrospective population-based cohort study.

OBJECTIVES

To describe the epidemiology of sexually transmitted infections (STIs), identify and characterise socio-epidemiological clusters and determine factors associated with HIV coinfection.

DESIGN

Retrospective population-based cohort.

SETTING

Catalonia, Spain.

PARTICIPANTS

42 283 confirmed syphilis, gonorrhoea, chlamydia and lymphogranuloma venereum cases, among 34 600 individuals, reported to the Catalan HIV/STI Registry in 2017-2019.

PRIMARY AND SECONDARY OUTCOMES

Descriptive analysis of confirmed STI cases and incidence rates. Factors associated with HIV coinfection were determined using logistic regression. We identified and characterized socio-epidemiological STI clusters by Basic Health Area (BHA) using K-means clustering.

RESULTS

The incidence rate of STIs increased by 91.3% from 128.2 to 248.9 cases per 100 000 population between 2017 and 2019 (p<0.001), primarily driven by increase among women (132%) and individuals below 30 years old (125%). During 2017-2019, 50.1% of STIs were chlamydia and 31.6% gonorrhoea. Reinfections accounted for 10.8% of all cases and 6% of cases affected HIV-positive individuals. Factors associated with the greatest likelihood of HIV coinfection were male sex (adjusted OR (aOR) 23.69; 95% CI 16.67 to 35.13), age 30-39 years (versus <20 years, aOR 18.58; 95% CI 8.56 to 52.13), having 5-7 STI episodes (vs 1 episode, aOR 5.96; 95% CI 4.26 to 8.24) and living in urban areas (aOR 1.32; 95% CI 1.04 to 1.69). Living in the most deprived BHAs (aOR 0.60; 95% CI 0.50 to 0.72) was associated with the least likelihood of HIV coinfection. K-means clustering identified three distinct clusters, showing that young women in rural and more deprived areas were more affected by chlamydia, while men who have sex with men in urban and less deprived areas showed higher rates of STI incidence, multiple STI episodes and HIV coinfection.

CONCLUSIONS

We recommend socio-epidemiological identification and characterisation of STI clusters and factors associated with HIV coinfection to identify at-risk populations at a small health area level to design effective interventions.