Better public decisions on COVID-19: A thought experiment in metrics

Objectives: Poor decision-making is a hallmark of the COVID-19 pandemic. Better metrics would help improve decision-makers' understanding of the scope of the pandemic and allow for better public understanding/review of these decisions. Study design: Two novel metrics of disease impact were comp...

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Autores principales:	David J. Tonjes, Krista L. Thyberg, Elizabeth Hewitt
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Disease metrics Decision support Public involvement Infectious population Odds ratio Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/c459d8efd94c4b1a9977c3230aaf887c
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id	oai:doaj.org-article:c459d8efd94c4b1a9977c3230aaf887c
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spelling	oai:doaj.org-article:c459d8efd94c4b1a9977c3230aaf887c2021-11-04T04:41:33ZBetter public decisions on COVID-19: A thought experiment in metrics2666-535210.1016/j.puhip.2021.100208https://doaj.org/article/c459d8efd94c4b1a9977c3230aaf887c2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666535221001336https://doaj.org/toc/2666-5352Objectives: Poor decision-making is a hallmark of the COVID-19 pandemic. Better metrics would help improve decision-makers' understanding of the scope of the pandemic and allow for better public understanding/review of these decisions. Study design: Two novel metrics of disease impact were compared with more commonly used standard metrics. Methods: A multi-criteria decision analysis technique, used previously to support metric selection in solid waste planning, was adapted to compare number of deaths, hospitalisations, positive test results and positivity rates (standard COVID-19 impact metrics) with a simple model that estimates the total number of potentially infectious people in an area and an associated odds ratio for infectious people. Results: The odds ratio and total infectious population estimate metrics scored better in a comparison analysis than number of deaths, hospitalisations, positive test results and positivity rates (in that order). Conclusions: The novel metrics provide a more effective means of communication than other more common measures of the outbreak. These superior metrics should support decision-making processes and result in a more informed population.David J. TonjesKrista L. ThybergElizabeth HewittElsevierarticleDisease metricsDecision supportPublic involvementInfectious populationOdds ratioPublic aspects of medicineRA1-1270ENPublic Health in Practice, Vol 2, Iss , Pp 100208- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Disease metrics Decision support Public involvement Infectious population Odds ratio Public aspects of medicine RA1-1270
spellingShingle	Disease metrics Decision support Public involvement Infectious population Odds ratio Public aspects of medicine RA1-1270 David J. Tonjes Krista L. Thyberg Elizabeth Hewitt Better public decisions on COVID-19: A thought experiment in metrics
description	Objectives: Poor decision-making is a hallmark of the COVID-19 pandemic. Better metrics would help improve decision-makers' understanding of the scope of the pandemic and allow for better public understanding/review of these decisions. Study design: Two novel metrics of disease impact were compared with more commonly used standard metrics. Methods: A multi-criteria decision analysis technique, used previously to support metric selection in solid waste planning, was adapted to compare number of deaths, hospitalisations, positive test results and positivity rates (standard COVID-19 impact metrics) with a simple model that estimates the total number of potentially infectious people in an area and an associated odds ratio for infectious people. Results: The odds ratio and total infectious population estimate metrics scored better in a comparison analysis than number of deaths, hospitalisations, positive test results and positivity rates (in that order). Conclusions: The novel metrics provide a more effective means of communication than other more common measures of the outbreak. These superior metrics should support decision-making processes and result in a more informed population.
format	article
author	David J. Tonjes Krista L. Thyberg Elizabeth Hewitt
author_facet	David J. Tonjes Krista L. Thyberg Elizabeth Hewitt
author_sort	David J. Tonjes
title	Better public decisions on COVID-19: A thought experiment in metrics
title_short	Better public decisions on COVID-19: A thought experiment in metrics
title_full	Better public decisions on COVID-19: A thought experiment in metrics
title_fullStr	Better public decisions on COVID-19: A thought experiment in metrics
title_full_unstemmed	Better public decisions on COVID-19: A thought experiment in metrics
title_sort	better public decisions on covid-19: a thought experiment in metrics
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/c459d8efd94c4b1a9977c3230aaf887c
work_keys_str_mv	AT davidjtonjes betterpublicdecisionsoncovid19athoughtexperimentinmetrics AT kristalthyberg betterpublicdecisionsoncovid19athoughtexperimentinmetrics AT elizabethhewitt betterpublicdecisionsoncovid19athoughtexperimentinmetrics
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Better public decisions on COVID-19: A thought experiment in metrics

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