Assessment of Bias in Estimates of Sexual Network Degree using Prospective Cohort Data. Issue 2 (March 2020) - Uong, Stephen; Rosenberg, Eli S.; Goodreau, Steven M.; Luisi, Nicole; Sullivan, Patrick; Jenness, Samuel M.
Abstract : Background: Sexual network degree, a count of ongoing partnerships, plays a critical role in the transmission dynamics of human immunodeficiency virus and other sexually transmitted infections. Researchers often quantify degree using self-reported cross-sectional data on the day of survey, which may result in bias because of uncertainty about future sexual activity. Methods: We evaluated the bias of a cross-sectional degree measure with a prospective cohort study of men who have sex with men (MSM). At baseline, we asked men about whether recent sexual partnerships were ongoing. We confirmed the true, ongoing status of those partnerships at baseline at follow-up. With logistic regression, we estimated the partnership-level predictors of baseline measure accuracy. With Poisson regression, we estimated the longitudinally confirmed degree as a function of baseline predicted degree. Results: Across partnership types, the baseline ongoing status measure was 70% accurate, with higher negative predictive value (91%) than positive predictive value (39%). Partnership exclusivity and racial pairing were associated with higher accuracy. Baseline degree generally overestimated confirmed degree. Bias, or number of ongoing partners different than predicted at baseline, was −0.28 overall, ranging from −1.91 to −0.41 for MSM with any ongoing partnerships at baseline. Comparing MSM of the same baseline degree, the level of bias was stronger for black compared with white MSM, and for younger compared with older MSM. Conclusions: Research studies may overestimate degree when it is quantified cross-sectionally. Adjustment and structured sensitivity analyses may account for bias in studies of human immunodeficiency virus or sexually transmitted infection prevention interventions. Abstract : Supplemental Digital Content is available in the text.