Using Big Data to Monitor the Introduction and Spread of Chikungunya, Europe, 2017.
Emerg Infect Dis
; 25(6): 1041-1049, 2019 06.
Article
em En
| MEDLINE
| ID: mdl-31107221
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Vírus Chikungunya
/
Febre de Chikungunya
/
Big Data
Tipo de estudo:
Prognostic_studies
Limite:
Animals
/
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
Emerg Infect Dis
Assunto da revista:
DOENCAS TRANSMISSIVEIS
Ano de publicação:
2019
Tipo de documento:
Article