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Does it matter that standard preparedness indices did not predict COVID-19 outcomes?
A number of scientific publications and commentaries have suggested that standard preparedness indices such as the Global Health Security Index (GHSI) and Joint External Evaluation (JEE) scores did not predict COVID-19 outcomes. To some, the failure of these metrics to be predictive demonstrates the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517542/ https://www.ncbi.nlm.nih.gov/pubmed/37740185 http://dx.doi.org/10.1186/s12992-023-00973-2 |
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author | Stoto, Michael A. Nelson, Christopher D. Kraemer, John D. |
author_facet | Stoto, Michael A. Nelson, Christopher D. Kraemer, John D. |
author_sort | Stoto, Michael A. |
collection | PubMed |
description | A number of scientific publications and commentaries have suggested that standard preparedness indices such as the Global Health Security Index (GHSI) and Joint External Evaluation (JEE) scores did not predict COVID-19 outcomes. To some, the failure of these metrics to be predictive demonstrates the need for a fundamental reassessment which better aligns preparedness measurement with operational capacities in real-world stress situations, including the points at which coordination structures and decision-making may fail. There are, however, several reasons why these instruments should not be so easily rejected as preparedness measures. From a methodological point of view, these studies use relatively simple outcome measures, mostly based on cumulative numbers of cases and deaths at a fixed point of time. A country’s “success” in dealing with the pandemic is highly multidimensional – both in the health outcomes and type and timing of interventions and policies – is too complex to represent with a single number. In addition, the comparability of mortality data over time and among jurisdictions is questionable due to highly variable completeness and representativeness. Furthermore, the analyses use a cross-sectional design, which is poorly suited for evaluating the impact of interventions, especially for COVID-19. Conceptually, a major reason that current preparedness measures fail to predict pandemic outcomes is that they do not adequately capture variations in the presence of effective political leadership needed to activate and implement existing system, instill confidence in the government’s response; or background levels of interpersonal trust and trust in government institutions and country ability needed to mount fast and adaptable responses. These factors are crucial; capacity alone is insufficient if that capacity is not effectively leveraged. However, preparedness metrics are intended to identify gaps that countries must fill. As important as effective political leadership and trust in institutions, countries cannot be held accountable to one another for having good political leadership or trust in institutions. Therefore, JEE scores, the GHSI, and similar metrics can be useful tools for identifying critical gaps in capacities and capabilities that are necessary but not sufficient for an effective pandemic response. |
format | Online Article Text |
id | pubmed-10517542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105175422023-09-24 Does it matter that standard preparedness indices did not predict COVID-19 outcomes? Stoto, Michael A. Nelson, Christopher D. Kraemer, John D. Global Health Commentary A number of scientific publications and commentaries have suggested that standard preparedness indices such as the Global Health Security Index (GHSI) and Joint External Evaluation (JEE) scores did not predict COVID-19 outcomes. To some, the failure of these metrics to be predictive demonstrates the need for a fundamental reassessment which better aligns preparedness measurement with operational capacities in real-world stress situations, including the points at which coordination structures and decision-making may fail. There are, however, several reasons why these instruments should not be so easily rejected as preparedness measures. From a methodological point of view, these studies use relatively simple outcome measures, mostly based on cumulative numbers of cases and deaths at a fixed point of time. A country’s “success” in dealing with the pandemic is highly multidimensional – both in the health outcomes and type and timing of interventions and policies – is too complex to represent with a single number. In addition, the comparability of mortality data over time and among jurisdictions is questionable due to highly variable completeness and representativeness. Furthermore, the analyses use a cross-sectional design, which is poorly suited for evaluating the impact of interventions, especially for COVID-19. Conceptually, a major reason that current preparedness measures fail to predict pandemic outcomes is that they do not adequately capture variations in the presence of effective political leadership needed to activate and implement existing system, instill confidence in the government’s response; or background levels of interpersonal trust and trust in government institutions and country ability needed to mount fast and adaptable responses. These factors are crucial; capacity alone is insufficient if that capacity is not effectively leveraged. However, preparedness metrics are intended to identify gaps that countries must fill. As important as effective political leadership and trust in institutions, countries cannot be held accountable to one another for having good political leadership or trust in institutions. Therefore, JEE scores, the GHSI, and similar metrics can be useful tools for identifying critical gaps in capacities and capabilities that are necessary but not sufficient for an effective pandemic response. BioMed Central 2023-09-23 /pmc/articles/PMC10517542/ /pubmed/37740185 http://dx.doi.org/10.1186/s12992-023-00973-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Commentary Stoto, Michael A. Nelson, Christopher D. Kraemer, John D. Does it matter that standard preparedness indices did not predict COVID-19 outcomes? |
title | Does it matter that standard preparedness indices did not predict COVID-19 outcomes? |
title_full | Does it matter that standard preparedness indices did not predict COVID-19 outcomes? |
title_fullStr | Does it matter that standard preparedness indices did not predict COVID-19 outcomes? |
title_full_unstemmed | Does it matter that standard preparedness indices did not predict COVID-19 outcomes? |
title_short | Does it matter that standard preparedness indices did not predict COVID-19 outcomes? |
title_sort | does it matter that standard preparedness indices did not predict covid-19 outcomes? |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517542/ https://www.ncbi.nlm.nih.gov/pubmed/37740185 http://dx.doi.org/10.1186/s12992-023-00973-2 |
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