Social media posts and online search behaviour as early-warning system for MRSA outbreaks

van de Belt TH, van Stockum PT, Engelen LJLPG, Lancee J, Schrijver R, Rodríguez-Baño J, Tacconelli E, Saris K, van Gelder MMHJ, Voss A.

Antimicrob Resist Infect Control. 2018 May 30;7:69. doi: 10.1186/s13756-018-0359-4. eCollection 2018.

Background: Despite many preventive measures, outbreaks with multi-drug  resistant micro-organisms (MDROs) still occur. Moreover, current alert  systems from healthcare organizations have shortcomings due to delayed  or incomplete notifications, which may amplify the spread of MDROs by  introducing infected patients into a new healthcare setting and  institutions. Additional sources of information about upcoming and  current outbreaks, may help to prevent further spread of MDROs.The study  objective was to evaluate whether methicillin-resistant Staphylococcus aureus (MRSA) outbreaks could be detected via social media posts or online  search behaviour; if so, this might allow earlier detection than the  official notifications by healthcare organizations.

Methods: We conducted an exploratory study in which we compared information  about MRSA outbreaks in the Netherlands derived from two online  sources, Coosto for Social Media, and Google Trends for search  behaviour, to the mandatory Dutch outbreak notification system  (SO-ZI/AMR). The latter provides information on MDRO outbreaks including  the date of the outbreak, micro-organism involved, the region/location,  and the type of health care organization.

Results: During the research period of 15 months (455 days), 49  notifications of outbreaks were recorded in SO-ZI/AMR. For Coosto, the  number of unique potential outbreaks was 37 and for Google Trends 24.  The use of social media and online search behaviour missed many of the  hospital outbreaks that were reported to SO-ZI/AMR, but detected  additional outbreaks in long-term care facilities.

Conclusions: Despite several limitations, using information from social media  and online search behaviour allows rapid identification of potential  MRSA outbreaks, especially in healthcare settings with a low  notification compliance. When combined in an automated system with  real-time updates, this approach might increase early discovery and  subsequent implementation of preventive measures.

Keywords: Google trends; MRSA; Methicillin-resistant Staphylococcus aureus; Nowcasting; Outbreaks; Social media monitoring.

Conflict of interest statement

Since  the anonymous data used in this study were derived from the public  social media domain without patient involvement, no medical ethical  review was needed in the Netherlands. SO-ZI/AMR allowed us to use  anonymous (not linked to specific hospital organizations) information  from their database.AV is Editor-in-Chief of ARIC. All other authors  declare that they have no competing interests.Springer Nature remains  neutral with regard to jurisdictional claims in published maps and  institutional affiliations.