Abstract
PurposeImprove the ability to infer sex behaviors more accurately using network data.MethodsA hybrid network analytic approach was utilized to integrate: (1) the plurality of reports from others tied to individual(s) of interest; and (2) structural features of the network generated from those ties. Network data was generated from digitally extracted cell-phone contact lists of a purposeful sample of 241 high-risk men in India. These data were integrated with interview responses to describe the corresponding individuals in the contact lists and the ties between them. HIV serostatus was collected for each respondent and served as an internal validation of the model’s predictions of sex behavior.ResultsWe found that network-based model predictions of sex behavior and self-reported sex behavior had limited correlation (54% agreement). Additionally, when respondent sex behaviors were re-classified to network model predictions from self-reported data, there was a 30.7% decrease in HIV seroprevalence among groups of men with lower risk behavior, which is consistent with HIV transmission biology.ConclusionCombining the relative completeness and objectivity of digital network data with the substantive details of classical interview and HIV biomarker data permitted new analyses and insights into the accuracy of self-reported sex behavior.
Highlights
Since the first cases of HIV were reported among high risk men in 1981, global HIV prevention research has been dominated by individual-level assessments that utilize self-reported behavior to determine risk of HIV acquisition
men who have sex with men (MSM) study respondents were recruited until the chance of a new respondent already being part of the network was .95%
All respondents were in the contact list of at least one other respondent. This process resulted in a network of MSM (n = 241; 706 ties) and an augmented MSM network including those who were not interviewed directly (n = 4991 MSM; 6548 ties) (Figure 4)
Summary
Since the first cases of HIV were reported among high risk men in 1981, global HIV prevention research has been dominated by individual-level assessments that utilize self-reported behavior to determine risk of HIV acquisition. Methodologies used in collecting self-reported risk behavior such as computer assisted surveys or online health diaries have contributed to improving the accuracy of sensitive sex behavior data [1,2]. Self-reported sex behavior may be insufficient to determine actual sex behavior in addition to the downstream HIV infection risks that occur. In contrast to individual level selfreported information, a network based approach that elicits information from other network members may help improve inference of sex behavior [6]
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