Dynamic Variation in Sexual Contact Rates in a Cohort of HIV-Negative Gay Men

Am J Epidemiol. 2015 Aug 1;182(3):255-62. doi: 10.1093/aje/kwv044. Epub 2015 May 20.

Abstract

Human immunodeficiency virus (HIV) transmission models that include variability in sexual behavior over time have shown increased incidence, prevalence, and acute-state transmission rates for a given population risk profile. This raises the question of whether dynamic variation in individual sexual behavior is a real phenomenon that can be observed and measured. To study this dynamic variation, we developed a model incorporating heterogeneity in both between-person and within-person sexual contact patterns. Using novel methodology that we call iterated filtering for longitudinal data, we fitted this model by maximum likelihood to longitudinal survey data from the Centers for Disease Control and Prevention's Collaborative HIV Seroincidence Study (1992-1995). We found evidence for individual heterogeneity in sexual behavior over time. We simulated an epidemic process and found that inclusion of empirically measured levels of dynamic variation in individual-level sexual behavior brought the theoretical predictions of HIV incidence into closer alignment with reality given the measured per-act probabilities of transmission. The methods developed here provide a framework for quantifying variation in sexual behaviors that helps in understanding the HIV epidemic among gay men.

Keywords: HIV; HIV risk; disease transmission; gay men; iterated filtering; partially observed Markov process; sexual behavior.

Publication types

  • Observational Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Disease Outbreaks / statistics & numerical data
  • HIV Infections / epidemiology
  • HIV Infections / transmission
  • HIV Seropositivity / epidemiology
  • Homosexuality, Male / statistics & numerical data*
  • Humans
  • Incidence
  • Likelihood Functions
  • Longitudinal Studies
  • Male
  • Markov Chains
  • Models, Statistical*
  • Monte Carlo Method
  • Prevalence
  • Risk Assessment
  • Risk-Taking
  • Sexual Behavior / statistics & numerical data*
  • Sexual Partners
  • Stochastic Processes
  • United States / epidemiology