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Title

A Digital Network Approach to Infer Sex Behavior in Emerging HIV Epidemics.

Authors

A. Kapur, JA Schneider, D. Heard, et al. 

Network Affiliation

 

Organization

 

Journal Name

PLoS One

Publication Date

7/1/2014

PubMed Search

http://www.ncbi.nlm.nih.gov/pubmed/24992340

Link to full-text

 

PMID

24992340

Abstract

PURPOSE:

Improve the ability to infer sex behaviors more accurately using network data.

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.

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.

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.

Keywords

 

Topic

Behavior

Attachments

Created at 7/14/2014 1:34 PM by Davis, Gregory P
Last modified at 7/14/2014 1:34 PM by Davis, Gregory P