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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...

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Autores principales: Shausan, Aminath, Nazarathy, Yoni, Dyda, Amalie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
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.
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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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