We will assess peer change agent communication effectiveness through mathematical models that utilize change agent attribute and structural position parameters developed through existing digital communication networks. Peer change agent (PCA)-based HIV prevention programs capitalize on the phenomenon of peer influence and how members in social networks communicate with one another. PCA-based interventions are the most frequently used outreach HIV prevention interventions and have been widely implemented both domestically and internationally. Existing PCA-based interventions, however, have yielded disappointing results in international settings. The central postulate of this proposa is that the change agent can often be more important than the message itself. Oftentimes, the messages promoted by public health officials may be of limited interest to others, even to those at increased HIV risk. In fact, when messages are of limited interest, those at increased HIV risk will tend to focus more on who the change agent is. The selection of change agents based in whole or in part upon their structural position as measured by formal social network characterization is one approach to increase potency of peer influence: it has been successful in business organization-based interventions. It has not, however, been empirically tested in the public health realm. By adopting this methodology, this proposal moves beyond traditional peer outreach models. In addition to utilizing the structural network position of PCAs to enhance the diffusion of innovation, our model also parameterizes important attributes of PCAs, which are determined by primary data collection from a large network of men who have sex with men in South India. These PCA attributes include social status features, leadership and communication behavior, tie qualities with members of their network, and physical attributes. Previously we have developed an innovative approach to social network characterization in this setting that allows for augmented network characterization through the use of cell phone communication networks in high- risk men. We have field survey data collection expertise in India and experience with large scale social network data collection and analyses. We also have experience in diffusion of innovation analyses through social networks and utilizing mathematical models for determining diffusion of disease and/or information through networks of men who have sex with men (MSM). Thus we will model condom communication within the network using attributes generated from participant interviews and social network-generated structural positions. Candidate PCAs will be selected using three classes of algorithms: (1) attribute-based;(2) position- based;and (3) combined attribute- and position-based. Flow of condom information in the network will be explored using multiple stochastic models that address missing data and are parameterized using self- and peer-evaluation data. In future work, we will test how novel bio-behavioral prevention interventions, diffuse through a network facilitated by strategically selected peer change agents.

Public Health Relevance

Peer outreach workers are commonly used to provide messages and strategies for individuals at high risk for HIV infection to decrease their risk for infection. However, there are a number of approaches to determine which of these workers are the best suited for the task. We will use mathematical models to determine what characteristics are most conducive to communication about condoms in a high-risk population.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21AI098599-02
Application #
8624654
Study Section
Behavioral and Social Science Approaches to Preventing HIV/AIDS Study Section (BSPH)
Program Officer
Mathias, Cherlynn
Project Start
2013-03-01
Project End
2015-02-28
Budget Start
2014-03-01
Budget End
2015-02-28
Support Year
2
Fiscal Year
2014
Total Cost
$192,654
Indirect Cost
$38,050
Name
University of Chicago
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
005421136
City
Chicago
State
IL
Country
United States
Zip Code
60637
Schneider, John; Schumm, L Philip; Fraser, Maya et al. (2018) A Gold-Standard for Entity Resolution within Sexually Transmitted Infection Networks. Sci Rep 8:8776
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
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
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