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O20.3 Sex in Seattle: Mechanistic Modeling of Sexual Partnership Dynamics
  1. J W Glasser1,
  2. H W Chesson1,
  3. S N Glick2,
  4. K Owusu-Edusei1,
  5. T L Gift1,
  6. S O Aral1
  1. 1Centers for Disease Control and Prevention, Atlanta, GA, United States
  2. 2George Washington University, Washington, DC, United States


Background To devise sexually-transmitted disease (STD) surveillance and intervention strategies based on the importance of individuals or relationships in pathogen diffusion, mechanistic models of sexual partnerships are needed.We modelled heterosexual partnerships, chose functions and estimated parameters by re-analysing information from a 2003–04 random-digit dialling survey among Seattle residents.

Methods We created artificial populations having the joint distributions of age and gender from a recent U.S. census. We used partnership formation rates calculated from the complete histories of male and female survey participants with and without partners to determine stochastically at each time-step who in the population was eligible to form new partnerships; these were matched according to age preferences from the National Health and Social Life Survey using the algorithm for which Shapley received the 2012 Nobel Prize in Economics. Similarly, we used durations from survival analyses of partnerships formed by survey participants to schedule the dissolution of new and reschedule the dissolution of existing partnerships when concurrent partners would replace existing ones.

Results Most modelled partnerships are short-lived, as are the gaps and overlaps between them. This finding matches those from several published studies. Heterosexual adolescents and young adults form and dissolve concurrent partnerships at approximately 0.1 and 10 times, respectively, the rates at which they form and dissolve exclusive ones. Consequently, concurrent partnerships are ephemeral relative to exclusive ones. We estimate that, by age 45 years, approximately 20% of men and women have had concurrent partners, but at any particular time, most have 0 or 1 partners.

Conclusions Few individuals have multiple partners at any time, but lifetime partner numbers increase with age at gender-specific rates. The risk of infection increases with the number of partners; thus, public health messages that refer to concurrent partners may not adequately address the STD risk associated with lifetime partner numbers.

  • dynamic
  • modeling
  • network

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