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Frequency and Combination of Sequential Sexual Acts That May Lead to Sexually Transmitted Infections at Different Anatomic Sites Within the Same Person.

Christine M KhosropourDavid M CoomesLindley A Barbee
Published in: Archives of sexual behavior (2022)
Modeling studies suggest that transmission of gonorrhea and chlamydia to multiple anatomic sites within the same person is necessary to reproduce observed high rates of extragenital gonorrhea/chlamydia. Limited empiric behavioral data support this idea. In this cross-sectional study, we enrolled individuals assigned male at birth who reported sex with men (MSM) and denied receptive anal sex (RAS) in the past 2 years. Participants enrolled in-person at the Sexual Health Clinic in Seattle, Washington (December 2019-September 2021) or online (July 2021-September 2021), and completed a sexual history questionnaire that asked about specific sexual acts and sequence of those acts during their last sexual encounter. We enrolled 210 MSM during the 16-month recruiting period. The median number of sex acts reported at last sexual encounter was 4 (interquartile range 3-5). The most commonly reported acts at last sex were: kissing (83%), receiving oral sex (82%), and insertive anal sex (65%). There was substantial variability in the sequence of acts reported; no unique sequence of sex acts was reported by more than 12% of the population. Ninety percent of participants reported sequences of behaviors that could lead to gonorrhea or chlamydia transmission within the same person (respondent or partner); the most common of these combinations was kissing followed by receiving oral sex (64% reporting). Engaging in multiple sex acts within a single sexual encounter is common and may lead to gonorrhea/chlamydia transmission within the same person. This complicates empiric measurements of transmission probabilities needed to estimate population-level transmission.
Keyphrases
  • men who have sex with men
  • mental health
  • hiv testing
  • machine learning
  • high grade
  • emergency department
  • cross sectional
  • electronic health record
  • big data