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|Title:||Age difference between heterosexual partners in Britain : implications for the spread of Chlamydia trachomatis|
|Authors :||Smid, Joost H.|
Mercer, Catherine H.
Althaus, Christian L.
|Published in :||Epidemics|
|Publisher / Ed. Institution :||Elsevier|
|License (according to publishing contract) :||CC BY 4.0: Namensnennung 4.0 International|
|Type of review:||Peer review (Publication)|
|Subjects :||Age disparity; Chlamydia trachomatis; Mathematical model; Sexual behaviour; Sexually transmitted diseases|
|Subject (DDC) :||616: Internal medicine and diseases|
|Abstract:||Heterosexual partners often differ in age. Integrating realistic patterns of sexual mixing by age into dynamic transmission models has been challenging. The effects of these patterns on the transmission of sexually transmitted infections (STI) including Chlamydia trachomatis (chlamydia), the most common bacterial STI are not well understood. We describe age mixing between new heterosexual partners using age- and sex-specific data about sexual behavior reported by people aged 16-63 years in the 2000 and 2010 British National Surveys of Sexual Attitudes and Lifestyles. We incorporate mixing patterns into a compartmental transmission model fitted to age- and sex-specific, chlamydia positivity from the same surveys, to investigate C. trachomatis transmission. We show that distributions of ages of new sex partners reported by women and by men in Britain are not consistent with each other. After balancing these distributions, new heterosexual partnerships tend to involve men who are older than women (median age difference 2, IQR -1, 5 years). We identified the most likely age combinations of heterosexual partners where incident C. trachomatis infections are generated. The model results show that in >50% of chlamydia transmitting partnerships, at least one partner is ≥25 years old. This study illustrates how sexual behavior data can be used to reconstruct detailed sexual mixing patterns by age, and how these patterns can be integrated into dynamic transmission models. The proposed framework can be extended to study the effects of age-dependent transmission on incidence in any STI.|
|Departement:||Life Sciences und Facility Management|
|Organisational Unit:||Institute of Applied Simulation (IAS)|
|Publication type:||Article in scientific Journal|
|Appears in Collections:||Publikationen Life Sciences und Facility Management|
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