Harnessing social networks in public health communication

An article recently published inSciencehas put forward a strong case for tapping into online sentiment and behaviour displayed on social networks to predict how the public respond during infectious disease outbreaks. 

The authors, Bauch and Galvani, claim that analysing comments on social networks about public health topics such as paediatric vaccine coverage, pandemic flu vaccination and acceptance of quarantine during the SARS outbreak, can help gain a greater insight into how ideas spread and influence behaviour.  

Using data from social networks, mathematical models can be used to map how an idea spreads in tandem with the spread of the biological contagion. For example, if a highly connected and influential 'node' in a network was to display anti-vaccine sentiment or promote protective behaviours, this could have a significant effect on how the rest of the people in their network might react as a result. 

Since the groundbreaking Google Flu Trends project, online behaviour has remained a relatively underutilised resource, in terms of informing epidemiological analysis of a virus and feeding back into public health communication strategies.

Bauch and Galvani write:"In many cases... public health communications have a beneficial effect on behavior. In other cases, their message is eclipsed by the influences of peers in social networks and by direct personal experience with infection or vaccination. The complexities of disease-behavior dynamics contribute to this undermining of public health efforts”.

Whilst little is known about online social contagion, an in depth understanding of how social networks are constructed and governed can help modellers predict how people might respond to disease control measures, which could then in turn help public health communicators understand how their message might be received and interpreted. 

This article follows research from the Tell Me projectwhich released a report last year recommending the analysis of social networks to understand sentiment, along with epidemiological and biological analyis, so that evidence-based communication strategies can be formed to address public concerns and displayed behaviours. 

This month, Tell Me project also heard from Professor Sheizaf Rafaeli, from the Center for Internet Research at the University of Haifa, about the “wisdom of crowds”: the public, through online networks, can have a stronger stake by being part of a richer feedback loop during infectious disease outbreaks.