Using big data to monitor the introduction and spread of Chikungunya, Europe, 2017

Joacim Rocklöv, Yesim Tozan, Aditya Ramadona, Maquines O. Sewe, Bertrand Sudre, Jon Garrido, Chiara Bellegarde De Saint Lary, Wolfgang Lohr, Jan C. Semenza

Research output: Contribution to journalArticlepeer-review

Abstract

With regard to fully harvesting the potential of big data, public health lags behind other fields. To determine this potential, we applied big data (air passenger volume from international areas with active chikungunya transmission, Twitter data, and vectorial capacity estimates of Aedes albopictus mosquitoes) to the 2017 chikungunya outbreaks in Europe to assess the risks for virus transmission, virus importation, and short-range dispersion from the outbreak foci. We found that indicators based on voluminous and velocious data can help identify virus dispersion from outbreak foci and that vector abundance and vectorial capacity estimates can provide information on local climate suitability for mosquitoborne outbreaks. In contrast, more established indicators based on Wikipedia and Google Trends search strings were less timely. We found that a combination of novel and disparate datasets can be used in real time to prevent and control emerging and reemerging infectious diseases.

Original languageEnglish (US)
Pages (from-to)1041-1049
Number of pages9
JournalEmerging Infectious Diseases
Volume25
Issue number6
DOIs
StatePublished - Jun 2019

ASJC Scopus subject areas

  • Epidemiology
  • Microbiology (medical)
  • Infectious Diseases

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