Using Social Media for Disease Surveillance

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Establishment and operation of the surveillance systems are very much resource-driven. We need to use many resources (financial, technical, logistical and others) to establish a sensitive surveillance system. Due to the economic downturn, countries have to plan smartly on their investments. One of the methods which have enabled us to save resources is to have event-based surveillance monitoring of various events through informal sources like community, media etc. Using media information for surveillance is one of the proactive measures that are in place in many countries. Media provides free of cost surveillance services to the ministry of health on disease detection. In addition to media, social media can be used as sources of information for disease control. There is not much evidence of using social media for the disease control programs though. Use of social media for disease control can have multiple scopes as followings:

  1. Early detection of disease or potential outbreak
  2. Contact tracing
  3. Monitoring of disease trends
  4. People’s perception, sentiments and behavior relevant to disease and disease control
  5. Assess the level of awareness and interpretation of disease in the community on the specific disease of international threat or local endemic diseases.
  6. Communication on disease control
  7. Monitor and evaluate the impact of interventions.

Based on these potential scopes, we can conceptualize on utilizing social media for disease control; and in coming days standardize its applicability. For instance, here are a few initiatives and examples, which has been carried out in Nepal and Indonesia.

Example 1: Use of Facebook on contact tracing of a passengers during the early stage of Pandemic H1N1 2009 – (done in 2009)

An analysis of Twitter on Middle East Respiratory Syndrome due to Corona Virus (MERS-CoV) with the following objectives (done in 2014)

  1. Use of social media for the detection of MERS-CoV cases
  2. Consider whether social media could complement the existing systems.

Tweets were analyzed based on followings:

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Detail findings available upon request