Inferences about spatiotemporal variation in dengue virus transmission are sensitive to assumptions about human mobility: a case study using geolocated tweets from Lahore, Pakistan.

Kraemer, Moritz U G; Bisanzio, D; Reiner, R C; Zakar, R; Hawkins, J B; Freifeld, C C; Smith, D L; Hay, S I; Brownstein, J S; Perkins, T Alex

Kraemer, Moritz U G; Bisanzio, D; Reiner, R C; Zakar, R; Hawkins, J B; Freifeld, C C; Smith, D L; Hay, S I; Brownstein, J S; Perkins, T Alex.

Afiliação

Kraemer MUG; 1Department of Pediatrics, Harvard Medical School, Boston, USA.
Bisanzio D; 2Computational Epidemiology Lab, Boston Children's Hospital, Boston, USA.
Reiner RC; 3Department of Zoology, University of Oxford, Oxford, UK.
Zakar R; 4RTI International, Washington, USA.
Hawkins JB; 5Center for Tropical Diseases, Sacro Cuore-Don Calabria Hospital, Negrar, Italy.
Freifeld CC; 6Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA.
Smith DL; 7Department of Public Health, University of Punjab, Lahore, Pakistan.
Hay SI; 1Department of Pediatrics, Harvard Medical School, Boston, USA.
Brownstein JS; 2Computational Epidemiology Lab, Boston Children's Hospital, Boston, USA.
Perkins TA; 2Computational Epidemiology Lab, Boston Children's Hospital, Boston, USA.

EPJ Data Sci ; 7(1): 16, 2018.

Article em En | MEDLINE | ID: mdl-30854281

Palavras-chave

Big data; Disease dynamics; Geo-located tweets; Gravity model; Human mobility; Radiation model; Spatiotemporal analysis; Twitter data

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: EPJ Data Sci Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google