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Viral Epidemiology: Tracking Viruses with Smartphones and Social Media

The science of epidemiology has been developed over the last 200 years, using traditional methods to describe the distribution of diseases by person, place, and time. However, in the last several decades, a new set of technologies has become available, based on the methods of computer sciences, syst...

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Autores principales: Rainwater-Lovett, Kaitlin, Rodriguez-Barraquer, Isabel, Moss, William J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7149612/
http://dx.doi.org/10.1016/B978-0-12-800964-2.00018-5
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author Rainwater-Lovett, Kaitlin
Rodriguez-Barraquer, Isabel
Moss, William J.
author_facet Rainwater-Lovett, Kaitlin
Rodriguez-Barraquer, Isabel
Moss, William J.
author_sort Rainwater-Lovett, Kaitlin
collection PubMed
description The science of epidemiology has been developed over the last 200 years, using traditional methods to describe the distribution of diseases by person, place, and time. However, in the last several decades, a new set of technologies has become available, based on the methods of computer sciences, systems biology, and the extraordinary powers of the Internet. Technological and analytical advances can enhance traditional epidemiological methods to study the emergence, epidemiology, and transmission dynamics of viruses and associated diseases. Social media are increasingly used to detect the emergence and geographic spread of viral disease outbreaks. Large-scale population movement can be estimated using satellite imagery and mobile phone use, and fine-scale population movement can be tracked using global positioning system loggers, allowing estimation of transmission pathways and contact patterns at different spatial scales. Advances in genomic sequencing and bioinformatics permit more accurate determination of viral evolution and the construction of transmission networks, also at different spatial and temporal scales. Phylodynamics links evolutionary and epidemiological processes to better understand viral transmission patterns. More complex and realistic mathematical models of virus transmission within human and animal populations, including detailed agent-based models, are increasingly used to predict transmission patterns and the impact of control interventions such as vaccination and quarantine. In this chapter, we will briefly review traditional epidemiological methods and then describe the new technologies with some examples of their application.
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spelling pubmed-71496122020-04-13 Viral Epidemiology: Tracking Viruses with Smartphones and Social Media Rainwater-Lovett, Kaitlin Rodriguez-Barraquer, Isabel Moss, William J. Viral Pathogenesis Article The science of epidemiology has been developed over the last 200 years, using traditional methods to describe the distribution of diseases by person, place, and time. However, in the last several decades, a new set of technologies has become available, based on the methods of computer sciences, systems biology, and the extraordinary powers of the Internet. Technological and analytical advances can enhance traditional epidemiological methods to study the emergence, epidemiology, and transmission dynamics of viruses and associated diseases. Social media are increasingly used to detect the emergence and geographic spread of viral disease outbreaks. Large-scale population movement can be estimated using satellite imagery and mobile phone use, and fine-scale population movement can be tracked using global positioning system loggers, allowing estimation of transmission pathways and contact patterns at different spatial scales. Advances in genomic sequencing and bioinformatics permit more accurate determination of viral evolution and the construction of transmission networks, also at different spatial and temporal scales. Phylodynamics links evolutionary and epidemiological processes to better understand viral transmission patterns. More complex and realistic mathematical models of virus transmission within human and animal populations, including detailed agent-based models, are increasingly used to predict transmission patterns and the impact of control interventions such as vaccination and quarantine. In this chapter, we will briefly review traditional epidemiological methods and then describe the new technologies with some examples of their application. 2016 2016-02-12 /pmc/articles/PMC7149612/ http://dx.doi.org/10.1016/B978-0-12-800964-2.00018-5 Text en Copyright © 2016 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
Rainwater-Lovett, Kaitlin
Rodriguez-Barraquer, Isabel
Moss, William J.
Viral Epidemiology: Tracking Viruses with Smartphones and Social Media
title Viral Epidemiology: Tracking Viruses with Smartphones and Social Media
title_full Viral Epidemiology: Tracking Viruses with Smartphones and Social Media
title_fullStr Viral Epidemiology: Tracking Viruses with Smartphones and Social Media
title_full_unstemmed Viral Epidemiology: Tracking Viruses with Smartphones and Social Media
title_short Viral Epidemiology: Tracking Viruses with Smartphones and Social Media
title_sort viral epidemiology: tracking viruses with smartphones and social media
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7149612/
http://dx.doi.org/10.1016/B978-0-12-800964-2.00018-5
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