Network analysis is an approach to research that is uniquely suited to describing, exploring, and understanding structural and relational aspects of health. It is both a methodological tool and a theoretical paradigm that allows us to pose and answer important ecological questions in public health. In this review we trace the history of network analysis, provide a methodological overview of network techniques, and discuss where and how network analysis has been used in public health. We show how network analysis has its roots in mathematics, statistics, sociology, anthropology, psychology, biology, physics, and computer science. In public health, network analysis has been used to study primarily disease transmission, especially for HIV/AIDS and other sexually transmitted diseases; information transmission, particularly for diffusion of innovations; the role of social support and social capital; the influence of personal and social networks on health behavior; and the interorganizational structure of health systems. We conclude with future directions for network analysis in public health.

The gap between discovery of public health knowledge and application in practice settings and policy development is due in part to ineffective dissemination. This article describes (1) lessons related to dissemination from related disciplines (eg, communication, agriculture, social marketing, political science), (2) current practices among researchers, (3) key audience characteristics, (4) available tools for dissemination, and (5) measures of impact. Dissemination efforts need to take into account the message, source, audience, and channel. Practitioners and policy makers can be more effectively reached via news media, social media, issue or policy briefs, one-on-one meetings, and workshops and seminars. Numerous “upstream” and “midstream” indicators of impact include changes in public perception or awareness, greater use of evidence-based interventions, and changes in policy. By employing ideas outlined in this article, scientific discoveries are more likely to be applied in public health agencies and policy-making bodies.