Ahead of Print - Using Big Data to Monitor the Introduction and Spread of Chikungunya, Europe, 2017 - Volume 25, Number 6—June 2019 - Emerging Infectious Diseases journal - CDC

Ahead of Print - Using Big Data to Monitor the Introduction and Spread of Chikungunya, Europe, 2017 - Volume 25, Number 6—June 2019 - Emerging Infectious Diseases journal - CDC

Volume 25, Number 6—June 2019

Perspective

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

On This Page

Climate Suitability: Vectorial Capacity

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Long-Range Importation: Air Passenger Volume

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Short-Range Dispersion: Geocoded Tweets

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Synergistic Effects: Human Mobility and Transmission Suitability

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Wikipedia and Google Trend Indicators

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Big Data and Emerging Infectious Diseases

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Suggested Citation

Figures

Figure 1

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

Tables

Table

Downloads

Appendix 1 

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Appendix 2 

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Appendix 3 

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RIS [TXT - 2 KB] 

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

Author affiliations: Umeå University, Umeå, Sweden (J. Rocklöv, A. Ramadona, M.O. Sewe, W. Lohr); New York University, New York, New York, USA (Y. Tozan); European Centre for Disease Prevention and Control, Stockholm, Sweden (B. Sudre, J. Garrido, C.B. de Saint Lary, J.C. Semenza)

Suggested citation for this article

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 albopictusmosquitoes) 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.