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Emerging data inputs for infectious diseases surveillance and decision making
Infectious diseases create a significant health and social burden globally and can lead to outbreaks and epidemics. Timely surveillance for infectious diseases is required to inform both short and long term public responses and health policies. Novel data inputs for infectious disease surveillance a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111015/ https://www.ncbi.nlm.nih.gov/pubmed/37082524 http://dx.doi.org/10.3389/fdgth.2023.1131731 |
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author | Shausan, Aminath Nazarathy, Yoni Dyda, Amalie |
author_facet | Shausan, Aminath Nazarathy, Yoni Dyda, Amalie |
author_sort | Shausan, Aminath |
collection | PubMed |
description | Infectious diseases create a significant health and social burden globally and can lead to outbreaks and epidemics. Timely surveillance for infectious diseases is required to inform both short and long term public responses and health policies. Novel data inputs for infectious disease surveillance and public health decision making are emerging, accelerated by the COVID-19 pandemic. These include the use of technology-enabled physiological measurements, crowd sourcing, field experiments, and artificial intelligence (AI). These technologies may provide benefits in relation to improved timeliness and reduced resource requirements in comparison to traditional methods. In this review paper, we describe current and emerging data inputs being used for infectious disease surveillance and summarize key benefits and limitations. |
format | Online Article Text |
id | pubmed-10111015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101110152023-04-19 Emerging data inputs for infectious diseases surveillance and decision making Shausan, Aminath Nazarathy, Yoni Dyda, Amalie Front Digit Health Digital Health Infectious diseases create a significant health and social burden globally and can lead to outbreaks and epidemics. Timely surveillance for infectious diseases is required to inform both short and long term public responses and health policies. Novel data inputs for infectious disease surveillance and public health decision making are emerging, accelerated by the COVID-19 pandemic. These include the use of technology-enabled physiological measurements, crowd sourcing, field experiments, and artificial intelligence (AI). These technologies may provide benefits in relation to improved timeliness and reduced resource requirements in comparison to traditional methods. In this review paper, we describe current and emerging data inputs being used for infectious disease surveillance and summarize key benefits and limitations. Frontiers Media S.A. 2023-04-04 /pmc/articles/PMC10111015/ /pubmed/37082524 http://dx.doi.org/10.3389/fdgth.2023.1131731 Text en © 2023 Shausan, Nazarathy and Dyda. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Shausan, Aminath Nazarathy, Yoni Dyda, Amalie Emerging data inputs for infectious diseases surveillance and decision making |
title | Emerging data inputs for infectious diseases surveillance and decision making |
title_full | Emerging data inputs for infectious diseases surveillance and decision making |
title_fullStr | Emerging data inputs for infectious diseases surveillance and decision making |
title_full_unstemmed | Emerging data inputs for infectious diseases surveillance and decision making |
title_short | Emerging data inputs for infectious diseases surveillance and decision making |
title_sort | emerging data inputs for infectious diseases surveillance and decision making |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111015/ https://www.ncbi.nlm.nih.gov/pubmed/37082524 http://dx.doi.org/10.3389/fdgth.2023.1131731 |
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