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<p>One-time sexual partnerships have the potential to generate densely connected sexual networks. The distribution of one-time partnerships among MSM is often right-skewed, wherein a small proportion of MSM have a high number of partners. Identifying a set of covariates to predict who these individuals are can aid in developing and deploying STI prevention interventions and contribute to our understanding of STI transmission dynamics. We fit several negative binomial models to estimate the count of one-time partnerships among US MSM using data from a web-based egocentric network survey. Penalized logistic models were fit to evaluate predictors of MSM with high partnership counts at different binary cut points. Several covariates were significant predictors of a high one-time partnership rate in every model, including the number of main (partner considered a boyfriend, significant other, or life partner) and casual (an ongoing relationship, but not a main partner) partners, engaging in exchange sex, mobile app or internet use to meet men, and non-injection drug use. In the negative binomial models, the rate of one-time partnership formation was lower for those having one main partner compared to none, and higher for those with &gt; 1 main partner, or any casual partners. Logistic models for partnership rates with a cut point at 6 partners per year considered as a high count had the overall best predictive performance. Overall, risk factors for HIV tend to occur together. We identified a set of covariates that were consistent predictors of high partnership rates. These models and predictors could be used as indicators for HIV/STI prevention interventions, such as partner-based services, and to aid in the parameterization of transmission models.</p>

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Predictive Models to Identify Factors Associated with a High One-Time Sexual Partnership Rate Among U.S. Men Who Have Sex with Men

  • 期刊论文

  • 发表日期：

    2026年4月4日

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  • Emeli J. Anderson,
  • Neel R. Gandhi,
  • Travis H. Sanchez,
  • Eva A. Enns,
  • Samuel M. Jenness

摘要

One-time sexual partnerships have the potential to generate densely connected sexual networks. The distribution of one-time partnerships among MSM is often right-skewed, wherein a small proportion of MSM have a high number of partners. Identifying a set of covariates to predict who these individuals are can aid in developing and deploying STI prevention interventions and contribute to our understanding of STI transmission dynamics. We fit several negative binomial models to estimate the count of one-time partnerships among US MSM using data from a web-based egocentric network survey. Penalized logistic models were fit to evaluate predictors of MSM with high partnership counts at different binary cut points. Several covariates were significant predictors of a high one-time partnership rate in every model, including the number of main (partner considered a boyfriend, significant other, or life partner) and casual (an ongoing relationship, but not a main partner) partners, engaging in exchange sex, mobile app or internet use to meet men, and non-injection drug use. In the negative binomial models, the rate of one-time partnership formation was lower for those having one main partner compared to none, and higher for those with > 1 main partner, or any casual partners. Logistic models for partnership rates with a cut point at 6 partners per year considered as a high count had the overall best predictive performance. Overall, risk factors for HIV tend to occur together. We identified a set of covariates that were consistent predictors of high partnership rates. These models and predictors could be used as indicators for HIV/STI prevention interventions, such as partner-based services, and to aid in the parameterization of transmission models.