Theoretical models suggest that the efficacy of public health interventions could be enhanced by tailoring distribution strategies to the network structure of target populations. Such approaches could yield large benefits in low-resource settings, where limited health infrastructure renders standard approaches ineffective, but the concepts lack empirical support. In 32 villages of rural Honduras, a research team and I conducted a randomized controlled trial of network-based public health interventions: chlorine for water purification and multivitamins for micronutrient deficiencies. In one-third of villages, interventions were first introduced to a 5% sample of individuals occupying high in-degree positions. In another third, interventions were introduced to a 5% sample of nominated friends, while the remaining villages were targeted randomly. This proposed project now aims to evaluate the results of this field experiment to examine the dissemination of the interventions, changes in knowledge, attitudes, and behavior, and ultimately health outcomes, in order to test the hypothesis that tailoring public health interventions to local network structure can enhance the spread and adoption of those interventions and thereby improve population health. My long-term career goal is to become an independent physician-investigator who brings together clinical medicine, health policy, and public health to understand and address the social determinants of health and underlying social structures that are associated with health-related knowledge, attitudes, and behaviors. As an MD-PhD candidate in health policy, with a medical sociology focus, I need additional mentorship and training in analytic methods to help me craft an interdisciplinary research approach. My three-year Training Plan will include coursework, supervised data analysis, manuscript writing, and attendance and presentations at professional meetings. I will utilize this training and my Project Sponsors'expertise on conducting research on social networks and health to accomplish my scientific objective: to acquire a more robust understanding of how network-based targeting methods for public health interventions can affect the spread of the interventions. In pursuit of this objective, I will seek to achieve two specific aims: (1) evaluate outcomes of a field experiment implemented in rural Honduras using network-based treatments in a randomized controlled design;and (2) develop a model for how individual-level attributes and network characteristics shape the rate and scope of diffusion of health interventions. The proposed research is innovative because it is among the first to provide empirical evidence for targeting public health interventions based on sociometric segmentation. It is significant because it has the potential to inform theoretical models, and more importantly, future interventions and health policies by providing a more comprehensive understanding of the articulations between social ties and health.

Public Health Relevance

Understanding how social ties are associated with the diffusion of health information, attitudes, and behaviors will help identify strategies to maximize the efficiency and effect of public health initiatives. The issue is particularly relevant in low-resource settings, where social networks may play a particularly prominent structural role and therefore can have an enhanced function in the dissemination of health-related phenomena. This proposed research aims to understand the effects of social network position on the spread of health interventions, and, more broadly, to examine whether network-based health intervention targeting may provide a viable strategy in health policy and public health. ! !

National Institute of Health (NIH)
National Institute on Aging (NIA)
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
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Special Emphasis Panel (ZRG1-F16-L (20))
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Haaga, John G
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Harvard University
Schools of Medicine
United States
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Kim, David A; Hwong, Alison R; Stafford, Derek et al. (2015) Social network targeting to maximise population behaviour change: a cluster randomised controlled trial. Lancet 386:145-53