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An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)

BACKGROUND: Most COVID-19 vulnerability indices rely on measures that are biased by rates of exposure or are retrospective like mortality rates that offer little opportunity for intervention. The Moore-Hill Vulnerability Index (MHVI) is a precision public health early warning alternative to traditio...

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Autores principales: Moore, Harriet, Hill, Bartholomew, Emery, Jay, Gussy, Mark, Siriwardena, Aloysius Niroshan, Spaight, Robert, Tanser, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623819/
https://www.ncbi.nlm.nih.gov/pubmed/37919728
http://dx.doi.org/10.1186/s12889-023-17092-7
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author Moore, Harriet
Hill, Bartholomew
Emery, Jay
Gussy, Mark
Siriwardena, Aloysius Niroshan
Spaight, Robert
Tanser, Frank
author_facet Moore, Harriet
Hill, Bartholomew
Emery, Jay
Gussy, Mark
Siriwardena, Aloysius Niroshan
Spaight, Robert
Tanser, Frank
author_sort Moore, Harriet
collection PubMed
description BACKGROUND: Most COVID-19 vulnerability indices rely on measures that are biased by rates of exposure or are retrospective like mortality rates that offer little opportunity for intervention. The Moore-Hill Vulnerability Index (MHVI) is a precision public health early warning alternative to traditional infection fatality rates that presents avenues for mortality prevention. METHODS: We produced an infection-severity vulnerability index by calculating the proportion of all recorded positive cases that were severe and attended by ambulances at small area scale for the East Midlands of the UK between May 2020 and April 2022. We produced maps identifying regions with high and low vulnerability, investigated the accuracy of the index over shorter and longer time periods, and explored the utility of the MHVI compared to other common proxy measures and indices. Analysis included exploring the correlation between our novel index and the Index of Multiple Deprivation (IMD). RESULTS: The MHVI captures geospatial dynamics that single metrics alone often overlook, including the compound health challenges associated with disadvantaged and declining coastal towns inhabited by communities with post-industrial health legacies. A moderate negative correlation between MHVI and IMD reflects spatial analysis which suggests that high vulnerability occurs in affluent rural as well as deprived coastal and urban communities. Further, the MHVI estimates of severity rates are comparable to infection fatality rates for COVID-19. CONCLUSIONS: The MHVI identifies regions with known high rates of poor health outcomes prior to the pandemic that case rates or mortality rates alone fail to identify. Pre-hospital early warning measures could be utilised to prevent mortality during a novel pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-17092-7.
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spelling pubmed-106238192023-11-04 An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI) Moore, Harriet Hill, Bartholomew Emery, Jay Gussy, Mark Siriwardena, Aloysius Niroshan Spaight, Robert Tanser, Frank BMC Public Health Research BACKGROUND: Most COVID-19 vulnerability indices rely on measures that are biased by rates of exposure or are retrospective like mortality rates that offer little opportunity for intervention. The Moore-Hill Vulnerability Index (MHVI) is a precision public health early warning alternative to traditional infection fatality rates that presents avenues for mortality prevention. METHODS: We produced an infection-severity vulnerability index by calculating the proportion of all recorded positive cases that were severe and attended by ambulances at small area scale for the East Midlands of the UK between May 2020 and April 2022. We produced maps identifying regions with high and low vulnerability, investigated the accuracy of the index over shorter and longer time periods, and explored the utility of the MHVI compared to other common proxy measures and indices. Analysis included exploring the correlation between our novel index and the Index of Multiple Deprivation (IMD). RESULTS: The MHVI captures geospatial dynamics that single metrics alone often overlook, including the compound health challenges associated with disadvantaged and declining coastal towns inhabited by communities with post-industrial health legacies. A moderate negative correlation between MHVI and IMD reflects spatial analysis which suggests that high vulnerability occurs in affluent rural as well as deprived coastal and urban communities. Further, the MHVI estimates of severity rates are comparable to infection fatality rates for COVID-19. CONCLUSIONS: The MHVI identifies regions with known high rates of poor health outcomes prior to the pandemic that case rates or mortality rates alone fail to identify. Pre-hospital early warning measures could be utilised to prevent mortality during a novel pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-17092-7. BioMed Central 2023-11-02 /pmc/articles/PMC10623819/ /pubmed/37919728 http://dx.doi.org/10.1186/s12889-023-17092-7 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 Research
Moore, Harriet
Hill, Bartholomew
Emery, Jay
Gussy, Mark
Siriwardena, Aloysius Niroshan
Spaight, Robert
Tanser, Frank
An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)
title An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)
title_full An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)
title_fullStr An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)
title_full_unstemmed An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)
title_short An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)
title_sort early warning precision public health approach for assessing covid-19 vulnerability in the uk: the moore-hill vulnerability index (mhvi)
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623819/
https://www.ncbi.nlm.nih.gov/pubmed/37919728
http://dx.doi.org/10.1186/s12889-023-17092-7
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