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Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems

During the last 30 years it has become commonplace for epidemiological studies to collect locational attributes of disease data. Although this advancement was driven largely by the introduction of handheld global positioning systems (GPS), and more recently, smartphones and tablets with built-in GPS...

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Detalles Bibliográficos
Autores principales: Stevens, Kim B., Pfeiffer, Dirk U.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102771/
https://www.ncbi.nlm.nih.gov/pubmed/26046634
http://dx.doi.org/10.1016/j.sste.2015.04.003
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author Stevens, Kim B.
Pfeiffer, Dirk U.
author_facet Stevens, Kim B.
Pfeiffer, Dirk U.
author_sort Stevens, Kim B.
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description During the last 30 years it has become commonplace for epidemiological studies to collect locational attributes of disease data. Although this advancement was driven largely by the introduction of handheld global positioning systems (GPS), and more recently, smartphones and tablets with built-in GPS, the collection of georeferenced disease data has moved beyond the use of handheld GPS devices and there now exist numerous sources of crowdsourced georeferenced disease data such as that available from georeferencing of Google search queries or Twitter messages. In addition, cartography has moved beyond the realm of professionals to crowdsourced mapping projects that play a crucial role in disease control and surveillance of outbreaks such as the 2014 West Africa Ebola epidemic. This paper provides a comprehensive review of a range of innovative sources of spatial animal and human health data including data warehouses, mHealth, Google Earth, volunteered geographic information and mining of internet-based big data sources such as Google and Twitter. We discuss the advantages, limitations and applications of each, and highlight studies where they have been used effectively.
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spelling pubmed-71027712020-03-31 Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems Stevens, Kim B. Pfeiffer, Dirk U. Spat Spatiotemporal Epidemiol Article During the last 30 years it has become commonplace for epidemiological studies to collect locational attributes of disease data. Although this advancement was driven largely by the introduction of handheld global positioning systems (GPS), and more recently, smartphones and tablets with built-in GPS, the collection of georeferenced disease data has moved beyond the use of handheld GPS devices and there now exist numerous sources of crowdsourced georeferenced disease data such as that available from georeferencing of Google search queries or Twitter messages. In addition, cartography has moved beyond the realm of professionals to crowdsourced mapping projects that play a crucial role in disease control and surveillance of outbreaks such as the 2014 West Africa Ebola epidemic. This paper provides a comprehensive review of a range of innovative sources of spatial animal and human health data including data warehouses, mHealth, Google Earth, volunteered geographic information and mining of internet-based big data sources such as Google and Twitter. We discuss the advantages, limitations and applications of each, and highlight studies where they have been used effectively. Elsevier Ltd. 2015-04 2015-05-08 /pmc/articles/PMC7102771/ /pubmed/26046634 http://dx.doi.org/10.1016/j.sste.2015.04.003 Text en Copyright © 2015 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Stevens, Kim B.
Pfeiffer, Dirk U.
Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems
title Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems
title_full Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems
title_fullStr Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems
title_full_unstemmed Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems
title_short Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems
title_sort sources of spatial animal and human health data: casting the net wide to deal more effectively with increasingly complex disease problems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102771/
https://www.ncbi.nlm.nih.gov/pubmed/26046634
http://dx.doi.org/10.1016/j.sste.2015.04.003
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