The politics of participatory epidemiology: Technologies, social media and influenza surveillance in the US. Issue 2 (June 2017) - Blouin-Genest, Gabriel; Miller, Allison
Abstract: Background: Health surveillance is now being augmented and transformed by the use of "unofficial" knowledge or sources of information. This unofficial data largely comes from Internet-based systems which gather information from non-state actors through intelligence networks, Internet and media scrawling, metadata analysis (online drug sale reports, Google searches, online forums, etc.) and social media analysis. Objectives: The main objective of this article is to explore the policy implications of such a revolution, an issue that has been surprisingly largely ignored by the literature in public policy. The research question underpinning this analysis is: what are the policy implications of the growing use of knowledge/data from Internet-based technologies for health surveillance in the US? The theoretical importance and challenges of these technologies for public policies conclude this paper. Methods: Using influenza as a case study, this article conducts a review of the documented impacts, for public health policy, of the use of communication and Internet-based technologies for surveillance. To do so, we inventory different social media-based initiatives currently used for influenza and public health surveillance while evaluating their consequences/impacts for public health policy. Conclusions: The main conclusion is that the way we access, produce and distribute data/information about influenza (through the use of communication and Internet-based technologies for surveillance) has a direct impact on the risk perception and, ultimately, on public health policies through an "overload" of data. Highlights: Quantity over quality characterizes the production of social media based data. It creates problems of standardization, control and verification. The severity aspects of events can hardly be evaluated and assessed. The result is an overload of data regarding influenza. This overload affects policies by modifying the perception of risk.