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Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference
Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144899/ https://www.ncbi.nlm.nih.gov/pubmed/28830109 http://dx.doi.org/10.1093/infdis/jiw344 |
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author | Lee, Elizabeth C. Asher, Jason M. Goldlust, Sandra Kraemer, John D. Lawson, Andrew B. Bansal, Shweta |
author_facet | Lee, Elizabeth C. Asher, Jason M. Goldlust, Sandra Kraemer, John D. Lawson, Andrew B. Bansal, Shweta |
author_sort | Lee, Elizabeth C. |
collection | PubMed |
description | Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales. |
format | Online Article Text |
id | pubmed-5144899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-51448992016-12-09 Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference Lee, Elizabeth C. Asher, Jason M. Goldlust, Sandra Kraemer, John D. Lawson, Andrew B. Bansal, Shweta J Infect Dis Big Data for Infectious Disease Surveillance and Modeling Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales. Oxford University Press 2016-12-01 2016-11-14 /pmc/articles/PMC5144899/ /pubmed/28830109 http://dx.doi.org/10.1093/infdis/jiw344 Text en © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, contact journals.permissions@oup.com. |
spellingShingle | Big Data for Infectious Disease Surveillance and Modeling Lee, Elizabeth C. Asher, Jason M. Goldlust, Sandra Kraemer, John D. Lawson, Andrew B. Bansal, Shweta Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference |
title | Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference |
title_full | Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference |
title_fullStr | Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference |
title_full_unstemmed | Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference |
title_short | Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference |
title_sort | mind the scales: harnessing spatial big data for infectious disease surveillance and inference |
topic | Big Data for Infectious Disease Surveillance and Modeling |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144899/ https://www.ncbi.nlm.nih.gov/pubmed/28830109 http://dx.doi.org/10.1093/infdis/jiw344 |
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