At a recent seminar on Health Systems Research, attendees from various countries met to share and discuss the uses, limitations, and applications of social network analysis in global health.
Social network analysis has been used for decades in various fields. In recent years, partially in response to the vast amount of computing power now available, it has been used to trace and predict infectious disease outbreaks, to follow the diffusion of innovations, to understand the “contagiousness” of group behaviors, and to fathom how countries make or break political alliances.
In previous blogs we have discussed the increasing interest in leveraging human social networks for the dissemination of knowledge. We have also highlighted the work of researchers like Nicholas Christakis, whose approach to network mapping has expanded our understanding of the applications of social network analysis to behavior change in complex social systems.
Those who study social networks describe individual behaviors in the context of the relationships that are weaved in and through human interactions.
At the meeting in Beijing we learned of ways in which funders, policy makers, and implementers can use social network analysis to improve the odds of successfully introducing a new vaccine in Nigeria or to improve the translation of research into policy in Burkina Faso. Complementing a recent blog on practical knowledge, we learned this past week of the applications of network analysis methods to address policy bottlenecks and implementation challenges that are common in developing countries.
Social network experts see networks as maps that contain a constellation of inter-connected dots, like the stations and routes in a subway. The metaphor of social networks as maps also serves to highlight the oftentimes complex web of connections that underline human behavior, including friendship, kinship, love, electoral patterns, or the transmission of obesity and happiness.
In Beijing we learned that those who study social networks have a unique take on human behaviors. They describe individual behaviors in the context of the relationships that are weaved in and through human interactions. In this view of the world, individual characteristics become less relevant to understand behaviors than the features of the relationships in which our lives are rooted.
The approaches from these studies can be applied to help scale-up health impact. Imagine that we could improve the exchange of information between community health workers and the families whom they attend to, or between implementers of life-saving health programs in Bihar, India.
If being well-connected and alike makes you more likely to exchange information, let’s leverage this to attain maximum intervention reach and behavior change.
Network analysis can fill a valuable gap in the shaping of delivery systems. Can we design delivery networks for essential commodities -- such as contraceptives or vaccines -- that become more efficient and resilient than the poorly structured supply chains we have today? Are we one step closer to an ideal network structure to help scale-up life-saving interventions?
The example of the introduction of a new vaccine in Nigeria highlighted the relevance of identifying influential gatekeepers and champions who can “make-or-break” the adoption and scaling up of life saving innovations at the national and community levels. Social network analysis thus opens up new avenues to encourage the adoption of innovations that attempt to improve effective coverage of quality deliveries, immunization, or family planning.
While many of the methods and big ideas we heard of in Beijing have been, or are being tried, we believe that the current challenge for this exciting field lies in bridging the gap between the fringe of theory and the mainstream of health delivery practice.
It is not uncommon for gatherings of researchers to close with calls for more research or with the identification of bigger questions. We left Beijing with an optimistic note as we saw a small community of practice emerge right in front of us. We expect that through ever increasing connections among researchers and practitioners, social network analysis will continue to help us find big answers to the challenges of large scale health impact.
While the widespread application of network analysis in global health is still aspirational, we believe it has huge potential for improving the odds of successful scaling up of impact.