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.
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.
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.
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.
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By: Nguyen NL1, Powers KA, Hughes JP, MacPhail CL, Piwowar-Manning E, Patel EU, Gomez-Olive FX, Kahn K, Pettifor AE.
- 1From the *Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC; †Department of Biostatistics, University of Washington, Seattle, WA; ‡University of New England, Armidale, New South Wales, Australia; §Department of Pathology, Johns Hopkins University, Baltimore, MD; ¶National Institutes of Health, Bethesda, MD; and ∥MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Witwatersrand, South Africa.
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