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

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

Abstract Billions of users of mobile phones, social media platforms, and other technologies generate an increasingly large volume of data that has the potential to be leveraged towards solving public health challenges. These and other big data resources tend to be most successful in epidemiological...

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Bibliographic Details
Main Authors: Moritz U. G. Kraemer, D. Bisanzio, R. C. Reiner, R. Zakar, J. B. Hawkins, C. C. Freifeld, D. L. Smith, S. I. Hay, J. S. Brownstein, T. Alex Perkins
Format: Article
Language:English
Published: SpringerOpen 2018-06-01
Series:EPJ Data Science
Subjects:
Big data
Disease dynamics
Geo-located tweets
Gravity model
Human mobility
Radiation model
Online Access:http://link.springer.com/article/10.1140/epjds/s13688-018-0144-x

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http://link.springer.com/article/10.1140/epjds/s13688-018-0144-x

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