@article{TEXTUAL,
      recid = {8374},
      author = {Abhinav, Kapur and Schneider, John A. and Heard, Daniel  and Mukherjee, Sayan and Schumm, Phil and Oruganti, Ganesh  and Laumann, Edward O.},
      title = {A Digital Network Approach to Infer Sex Behavior in  Emerging HIV Epidemics},
      journal = {PLOS ONE},
      address = {2014-07-03},
      number = {TEXTUAL},
      abstract = {&lt;p&gt;Purpose: Improve the ability to infer sex behaviors  more accurately using network data.&lt;/p&gt;&lt;p&gt;Methods: A 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.&lt;/p&gt;&lt;p&gt;Results: We  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.&lt;/p&gt;&lt;p&gt;Conclusion: Combining 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.&lt;/p&gt;},
      url = {http://knowledge.uchicago.edu/record/8374},
}