HPTN Bibliographic Record
Nguyen NL, Powers KA, Hughes JP, MacPhail CL, Piwowar-Manning E, Patel EU, Gomez-Olive FX, Kahn K, Pettifor AE. Sexual Partnership Patterns Among South African Adolescent Girls Enrolled in STI Preventions Trial Network 068: Measurement Challenges and Implications for HIV/STI Transmission. Sex Transm Dis. 2015, 42: 612-8.
BACKGROUND: Estimates of sexual partnership durations, gaps between partnerships, and overlaps across partnerships are important for understanding sexual partnership patterns and developing interventions to prevent transmission of HIV/sexually transmitted infections (STIs). However, a validated, optimal approach for estimating these parameters, particularly when partnerships are ongoing, has not been established. METHODS: We assessed 4 approaches for estimating partnership parameters using cross-sectional reports on dates of first and most recent sex and partnership status (ongoing or not) from 654 adolescent girls in rural South Africa. The first, commonly used, approach assumes all partnerships have ended, resulting in underestimated durations for ongoing partnerships. The second approach treats reportedly ongoing partnerships as right-censored, resulting in bias if partnership status is reported with error. We propose 2 "hybrid" approaches, which assign partnership status to reportedly ongoing partnerships based on how recently girls last had sex with their partner. We estimate partnership duration, gap length, and overlap length under each approach using Kaplan-Meier methods with a robust variance estimator. RESULTS: Median partnership duration and overlap length varied considerably across approaches (from 368 to 1024 days and 168 to 409 days, respectively), but gap length was stable. Lifetime prevalence of concurrency ranged from 28% to 33%, and at least half of gap lengths were shorter than 6 months, suggesting considerable potential for HIV/STI transmission. CONCLUSIONS: Estimates of partnership duration and overlap lengths are highly dependent on measurement approach. Understanding the effect of different approaches on estimates is critical for interpreting partnership data and using estimates to predict HIV/STI transmission rates.