{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:57:29Z","timestamp":1789088249609,"version":"build-2803163510"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T00:00:00Z","timestamp":1608595200000},"content-version":"vor","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000272","name":"National Institute for Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Health Protection Research Unit"},{"DOI":"10.13039\/501100002141","name":"Public Health England","doi-asserted-by":"publisher","award":["HPRU-2012-10080"],"award-info":[{"award-number":["HPRU-2012-10080"]}],"id":[{"id":"10.13039\/501100002141","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006662","name":"NIHR","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006662","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Imperial College London and LSHTM","award":["NIHR200908"],"award-info":[{"award-number":["NIHR200908"]}]},{"name":"MRC Centre for Global Infectious Disease Analysis","award":["MR\/R015600\/1"],"award-info":[{"award-number":["MR\/R015600\/1"]}]},{"DOI":"10.13039\/501100000265","name":"UK Medical Research Council","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"crossref"}]},{"name":"UK Foreign, Commonwealth & Development Office"},{"DOI":"10.13039\/501100000265","name":"MRC","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020171","name":"FCDO","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100020171","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100000780","name":"European Union","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018952","name":"NIHR Birmingham Biomedical Research Centre","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100018952","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100013963","name":"University Hospitals Birmingham NHS Foundation Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013963","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000855","name":"University of Birmingham","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000855","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Chlamydia is the most commonly diagnosed sexually transmitted infection worldwide. Mathematical models used to plan and assess control measures rely on accurate estimates of chlamydia\u2019s natural history, including the probability of transmission within a partnership. Several methods for estimating transmission probability have been proposed, but all have limitations.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We have developed a new model for estimating per-partnership chlamydia transmission probabilities from infected to uninfected individuals, using data from population-based surveys. We used data on sexual behaviour and prevalent chlamydia infection from the second UK National Study of Sexual Attitudes and Lifestyles (Natsal-2) and the US National Health and Nutrition Examination Surveys 2009\u20132014 (NHANES) for Bayesian inference of average transmission probabilities, across all new heterosexual partnerships reported. Posterior distributions were estimated by Markov chain Monte Carlo sampling using the Stan software.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Posterior median male-to-female transmission probabilities per partnership were 32.1% [95% credible interval (CrI) 18.4\u201355.9%] (Natsal-2) and 34.9% (95%CrI 22.6\u201354.9%) (NHANES). Female-to-male transmission probabilities were 21.4% (95%CrI 5.1\u201367.0%) (Natsal-2) and 4.6% (95%CrI 1.0\u201313.1%) (NHANES). Posterior predictive checks indicated a well-specified model, although there was some discrepancy between reported and predicted numbers of partners, especially in women.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>The model provides statistically rigorous estimates of per-partnership transmission probability, with associated uncertainty, which is crucial for modelling and understanding chlamydia epidemiology and control. Our estimates incorporate data from several sources, including population-based surveys, and use information contained in the correlation between number of partners and the probability of chlamydia infection. The evidence synthesis approach means that it is easy to include further data as it becomes available.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/ije\/dyaa202","type":"journal-article","created":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T11:14:50Z","timestamp":1601032490000},"page":"510-517","source":"Crossref","is-referenced-by-count":8,"title":["Per-partnership transmission probabilities for <i>Chlamydia trachomatis<\/i> infection: evidence synthesis of population-based survey data"],"prefix":"10.1093","volume":"50","author":[{"given":"Joanna","family":"Lewis","sequence":"first","affiliation":[{"name":"MRC Centre for Global Infectious Disease Analysis and National Institute for Health Research (NIHR) Health Protection Research Unit in Modelling and Health Economics, Imperial College London School of Public Health, London, UK"},{"name":"Centre for Applied Statistics Courses, UCL Great Ormond Street Institute of Child Health, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter J","family":"White","sequence":"additional","affiliation":[{"name":"MRC Centre for Global Infectious Disease Analysis and National Institute for Health Research (NIHR) Health Protection Research Unit in Modelling and Health Economics, Imperial College London School of Public Health, London, UK"},{"name":"Modelling and Economics Unit, National Infection Service, Public Health England, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Malcolm J","family":"Price","sequence":"additional","affiliation":[{"name":"Institute of Applied Health Research, University of Birmingham, Birmingham, UK"},{"name":"NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,12,8]]},"reference":[{"key":"2021051721290621600_dyaa202-B1","volume-title":"Sexually Transmitted Disease Surveillance 2018","year":"2019"},{"key":"2021051721290621600_dyaa202-B2"},{"key":"2021051721290621600_dyaa202-B3","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1097\/EDE.0000000000000655","article-title":"Estimating local chlamydia incidence and prevalence using surveillance data","volume":"28","author":"Lewis","year":"2017","journal-title":"Epidemiology"},{"key":"2021051721290621600_dyaa202-B4","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1097\/OLQ.0b013e31827bd637","article-title":"Screening and treating Chlamydia trachomatis genital infection to prevent pelvic inflammatory disease: interpretation of findings from randomized controlled trials","volume":"40","author":"Gottlieb","year":"2013","journal-title":"Sex Transm Dis"},{"key":"2021051721290621600_dyaa202-B5","doi-asserted-by":"crossref","first-page":"e271","DOI":"10.1016\/S2468-2667(18)30071-9","article-title":"Changes in chlamydia prevalence and duration of infection estimated from testing and diagnosis rates in England: a model-based analysis using surveillance data, 2000--15","volume":"3","author":"Lewis","year":"2018","journal-title":"Lancet Public Health"},{"key":"2021051721290621600_dyaa202-B6","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1093\/aje\/kws583","article-title":"Risk of pelvic inflammatory disease following Chlamydia trachomatis infection: analysis of prospective studies with a multistate model","volume":"178","author":"Price","year":"2013","journal-title":"Am J Epidemiol"},{"key":"2021051721290621600_dyaa202-B7","doi-asserted-by":"crossref","first-page":"8.","DOI":"10.1186\/1742-4682-11-8","article-title":"How robust are the natural history parameters used in chlamydia transmission dynamic models? 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