Measuring concurrency using a joint multistate and point process model for retrospective sexual history data.

Understanding the impact of concurrency, defined as overlapping sexual partnerships, on the spread of HIV within various communities has been complicated by difficulties in measuring concurrency. Retrospective sexual history data consisting of first and last dates of sexual intercourse for each previous and ongoing partnership is often obtained through use of cross-sectional surveys. Previous attempts to empirically estimate the magnitude and extent of concurrency among these surveyed populations have inadequately accounted for the dependence between partnerships and used only a snapshot of the available data. We introduce a joint multistate and point process model in which states are defined as the number of ongoing partnerships an individual is engaged in at a given time. Sexual partnerships starting and ending on the same date are referred to as one-offs and modeled as discrete events. The proposed method treats each individual's continuation in and transition through various numbers of ongoing partnerships as a separate stochastic process and allows the occurrence of one-offs to impact subsequent rates of partnership formation and dissolution. Estimators for the concurrent partnership distribution and mean sojourn times during which a person has k ongoing partnerships are presented. We demonstrate this modeling approach using epidemiological data collected from a sample of men having sex with men and seeking HIV testing at a Los Angeles clinic. Among this sample, the estimated point prevalence of concurrency was higher among men later diagnosed HIV positive. One-offs were associated with increased rates of subsequent partnership dissolution.