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Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic
Agent-based models (ABMs) are one of the main sources of evidence for decisions regarding mitigation and suppression measures against the spread of SARS-CoV-2. These models have not been previously included in the hierarchy of evidence put forth by the evidence-based medicine movement, which priorit...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7816743/ https://www.ncbi.nlm.nih.gov/pubmed/33471199 http://dx.doi.org/10.1007/s40656-020-00357-4 |
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author | Maziarz, Mariusz Zach, Martin |
author_facet | Maziarz, Mariusz Zach, Martin |
author_sort | Maziarz, Mariusz |
collection | PubMed |
description | Agent-based models (ABMs) are one of the main sources of evidence for decisions regarding mitigation and suppression measures against the spread of SARS-CoV-2. These models have not been previously included in the hierarchy of evidence put forth by the evidence-based medicine movement, which prioritizes those research methods that deliver results less susceptible to the risk of confounding. We point out the need to assess the quality of evidence delivered by ABMs and ask the question of what is the risk that assumptions entertained in ABMs do not include all the key factors and make model predictions susceptible to the problem of confounding. |
format | Online Article Text |
id | pubmed-7816743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-78167432021-01-21 Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic Maziarz, Mariusz Zach, Martin Hist Philos Life Sci Notes & Comments Agent-based models (ABMs) are one of the main sources of evidence for decisions regarding mitigation and suppression measures against the spread of SARS-CoV-2. These models have not been previously included in the hierarchy of evidence put forth by the evidence-based medicine movement, which prioritizes those research methods that deliver results less susceptible to the risk of confounding. We point out the need to assess the quality of evidence delivered by ABMs and ask the question of what is the risk that assumptions entertained in ABMs do not include all the key factors and make model predictions susceptible to the problem of confounding. Springer International Publishing 2021-01-20 2021 /pmc/articles/PMC7816743/ /pubmed/33471199 http://dx.doi.org/10.1007/s40656-020-00357-4 Text en © Springer Nature Switzerland AG 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Notes & Comments Maziarz, Mariusz Zach, Martin Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic |
title | Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic |
title_full | Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic |
title_fullStr | Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic |
title_full_unstemmed | Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic |
title_short | Assessing the quality of evidence from epidemiological agent-based models for the COVID-19 pandemic |
title_sort | assessing the quality of evidence from epidemiological agent-based models for the covid-19 pandemic |
topic | Notes & Comments |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7816743/ https://www.ncbi.nlm.nih.gov/pubmed/33471199 http://dx.doi.org/10.1007/s40656-020-00357-4 |
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