#Swineflu: The Use of Twitter as an EarlyWarning and Risk Communication

  • Kostkova P
  • Szomszor M
  • St. Luis C
  • 26

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Abstract

The need to improve population monitoring and enhance surveillance of infectious diseases has never been more pressing. Factors such as air travel act as a catalyst in the spread of new and existing viruses. The unprecedented user-generated activity on social networks over the last few years has created real-time streams of personal data that provide an invaluable tool for monitoring and sampling large populations. Epidemic intelligence relies on constant monitoring of online media sources for early warning, detection, and rapid response; however, the real-time information available in social networks provides a new paradigm for the early warning function. The communication of risk in any public health emergency is a complex task for governments and healthcare agencies. This task is made more challenging in the current situation when the public has access to a wide range of online resources, ranging from traditional news channels to information posted on blogs and social networks. Twitter’s strength is its two-way communication nature --- both as an information source but also as a central hub for publishing, disseminating and discovering online media. This study addresses these two challenges by investigating the role of Twitter during the 2009 swine flu pandemic by analysing data collected from the SN, and by Twitter using the opposite way for dissemination information through the network. First, we demonstrate the role of the social network for early warning by detecting an upcoming spike in an epidemic before the official surveillance systems by up to two weeks in the U.K. and up to two to three weeks in the U.S. Second, we illustrate how online resources are propagated through Twitter at the time of the WHO’s declaration of the swine flu “pandemic”. Our findings indicate that Twitter does favour reputable t bogus information can still leak into the network.

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Authors

  • Patty Kostkova

  • Martin Szomszor

  • Connie St. Luis

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