The proposed research applies an innovative network measurement application - Cell-phone Assisted Network Detection and Identification (CANDID) - to establish a communication network and examine its relation to health related behaviors for men at high risk for HIV infection. Most network studies of health and behavior have used egocentric surveys of individuals that depend on respondents generating the names of alters in their network and providing information on them. However, the utility of egocentric data collection for network characterization has several clear limitations. Recent advances in use of archival computerized network data including email messages, citations, and cell phone provider data has allowed for more objective analyses of "whole" network structure. However, deficiencies in health or behavioral information are inherent to such datasets. We plan to address at least two limitations of current basic network research: respondent bias (recall, recognition and forgetting) and deficiencies in archival network data (especially the lack of behavioral health related data) by applying a newly developed network measurement algorithm, CANDID, combined with a name interpreter. CANDID is a low-cost application that utilizes a cell-phone Subscriber Identity Module (SIM) card reader and associated software to allow for tie/alter identification from respondents'cell phone contact lists. A transformation of cell phone numbers will serve as a "unique identifier" for each respondent and contact. With strong privacy protections in place, we are able to unambiguously link contact lists of all sampled respondents to generate an "augmented" network, that is, network tie information for respondents plus tie information for all other actors (including non-sampled actors). Name interpreter data of sampled respondents then provides complementary tie/alter attribute information. This approach of linking cell phone contact lists from sampled respondents combines archival and egocentric network data collection allowing for measurement of undirected and directed ties between actors with confidence and through survey data, tie attributes and actor health behavior characteristics. This hybrid approach will be leveraged to explore communication network structures in Indian men who have sex with men (MSM). It will then be specifically applied via an empirical analytic framework to explore the complex interactions between marital status, sex position and HIV risk among a large augmented network of Indian MSM.

Public Health Relevance

The proposed study will utilize an innovative novel social network characterization application - Cell-phone Assisted Network Detection and identification (CANDID) - and field test it in a population of men at high risk for HIV infection. This hybrid CANDID application will allow for investigators to address limitations of two common social network data collection methods - egocentric and archival - and will be leveraged to explore network structure. It will then be specifically applied via an empirical analytic framework to explore potential network explanations for the complex interactions between marital status, sex position and risk of HIV among Indian high risk men.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZRG1-RPHB-L (51))
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Newcomer, Susan
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University of Chicago
Internal Medicine/Medicine
Schools of Medicine
United States
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Schneider, John A; Zhou, A Ning; Laumann, Edward O (2015) A new HIV prevention network approach: sociometric peer change agent selection. Soc Sci Med 125:192-202
Hochberg, Chad H; Schneider, John A; Dandona, Rakhi et al. (2015) Population and dyadic-based seroincidence of herpes simplex virus-2 and syphilis in southern India. Sex Transm Infect 91:375-82
Satyanarayan, Sammita; Kapur, Abhinav; Azhar, Sameena et al. (2015) Women Connected to at Risk Indian Men Who Have Sex with Men: An Unexplored Network. AIDS Behav 19:1031-6
Kapur, Abhinav; Schneider, John A; Heard, Daniel et al. (2014) A digital network approach to infer sex behavior in emerging HIV epidemics. PLoS One 9:e101416
Livak, Britt; Schneider, John A (2014) Using sociometric measures to assess nonresponse bias. Ann Epidemiol 24:554-7
Armbruster, Benjamin; Roy, Sourya; Kapur, Abhinav et al. (2013) Sex role segregation and mixing among men who have sex with men: implications for biomedical HIV prevention interventions. PLoS One 8:e70043