Using Big Data to Monitor the Introduction and Spread of Chikungunya, Europe, 2017

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

doi:10.3201/eid2506.180138

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.

Highlights

With regard to fully harvesting the potential of big data, public health lags behind other fields
Many sectors of society have taken full advantage of new opportunities provided by big data, but public health has not [1]
Crowdsourcing of symptoms through emails, text messages, or tweets has been explored, and outbreaks have been tracked by scanning high-volume surveillance systems [5,6]. When it comes to fully harvesting the potential of big data, public health still lags behind other fields

Summary

Introduction

With regard to fully harvesting the potential of big data, public health lags behind other fields. Climate Suitability: Vectorial Capacity The vectorial capacity of Ae. albopictus mosquitoes to transmit chikungunya virus in areas of Europe where the vector is established [17], such as the outbreak zones in France and Italy, was estimated to be high in July and August but lower in September and October.

Results

Conclusion