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Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales

BACKGROUND: COVID-19 poses one of the most profound public health crises for a hundred years. As of mid-May 2020, across the world, almost 300,000 deaths and over 4 million confirmed cases were registered. Reaching over 30,000 deaths by early May, the UK had the highest number of recorded deaths in...

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Autores principales: Verhagen, Mark D., Brazel, David M., Dowd, Jennifer Beam, Kashnitsky, Ilya, Mills, Melinda C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7321716/
https://www.ncbi.nlm.nih.gov/pubmed/32594909
http://dx.doi.org/10.1186/s12916-020-01646-2
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author Verhagen, Mark D.
Brazel, David M.
Dowd, Jennifer Beam
Kashnitsky, Ilya
Mills, Melinda C.
author_facet Verhagen, Mark D.
Brazel, David M.
Dowd, Jennifer Beam
Kashnitsky, Ilya
Mills, Melinda C.
author_sort Verhagen, Mark D.
collection PubMed
description BACKGROUND: COVID-19 poses one of the most profound public health crises for a hundred years. As of mid-May 2020, across the world, almost 300,000 deaths and over 4 million confirmed cases were registered. Reaching over 30,000 deaths by early May, the UK had the highest number of recorded deaths in Europe, second in the world only to the USA. Hospitalization and death from COVID-19 have been linked to demographic and socioeconomic variation. Since this varies strongly by location, there is an urgent need to analyse the mismatch between health care demand and supply at the local level. As lockdown measures ease, reinfection may vary by area, necessitating a real-time tool for local and regional authorities to anticipate demand. METHODS: Combining census estimates and hospital capacity data from ONS and NHS at the Administrative Region, Ceremonial County (CC), Clinical Commissioning Group (CCG) and Lower Layer Super Output Area (LSOA) level from England and Wales, we calculate the number of individuals at risk of COVID-19 hospitalization. Combining multiple sources, we produce geospatial risk maps on an online dashboard that dynamically illustrate how the pre-crisis health system capacity matches local variations in hospitalization risk related to age, social deprivation, population density and ethnicity, also adjusting for the overall infection rate and hospital capacity. RESULTS: By providing fine-grained estimates of expected hospitalization, we identify areas that face higher disproportionate health care burdens due to COVID-19, with respect to pre-crisis levels of hospital bed capacity. Including additional risks beyond age-composition of the area such as social deprivation, race/ethnic composition and population density offers a further nuanced identification of areas with disproportionate health care demands. CONCLUSIONS: Areas face disproportionate risks for COVID-19 hospitalization pressures due to their socioeconomic differences and the demographic composition of their populations. Our flexible online dashboard allows policy-makers and health officials to monitor and evaluate potential health care demand at a granular level as the infection rate and hospital capacity changes throughout the course of this pandemic. This agile knowledge is invaluable to tackle the enormous logistical challenges to re-allocate resources and target susceptible areas for aggressive testing and tracing to mitigate transmission.
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spelling pubmed-73217162020-06-29 Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales Verhagen, Mark D. Brazel, David M. Dowd, Jennifer Beam Kashnitsky, Ilya Mills, Melinda C. BMC Med Research Article BACKGROUND: COVID-19 poses one of the most profound public health crises for a hundred years. As of mid-May 2020, across the world, almost 300,000 deaths and over 4 million confirmed cases were registered. Reaching over 30,000 deaths by early May, the UK had the highest number of recorded deaths in Europe, second in the world only to the USA. Hospitalization and death from COVID-19 have been linked to demographic and socioeconomic variation. Since this varies strongly by location, there is an urgent need to analyse the mismatch between health care demand and supply at the local level. As lockdown measures ease, reinfection may vary by area, necessitating a real-time tool for local and regional authorities to anticipate demand. METHODS: Combining census estimates and hospital capacity data from ONS and NHS at the Administrative Region, Ceremonial County (CC), Clinical Commissioning Group (CCG) and Lower Layer Super Output Area (LSOA) level from England and Wales, we calculate the number of individuals at risk of COVID-19 hospitalization. Combining multiple sources, we produce geospatial risk maps on an online dashboard that dynamically illustrate how the pre-crisis health system capacity matches local variations in hospitalization risk related to age, social deprivation, population density and ethnicity, also adjusting for the overall infection rate and hospital capacity. RESULTS: By providing fine-grained estimates of expected hospitalization, we identify areas that face higher disproportionate health care burdens due to COVID-19, with respect to pre-crisis levels of hospital bed capacity. Including additional risks beyond age-composition of the area such as social deprivation, race/ethnic composition and population density offers a further nuanced identification of areas with disproportionate health care demands. CONCLUSIONS: Areas face disproportionate risks for COVID-19 hospitalization pressures due to their socioeconomic differences and the demographic composition of their populations. Our flexible online dashboard allows policy-makers and health officials to monitor and evaluate potential health care demand at a granular level as the infection rate and hospital capacity changes throughout the course of this pandemic. This agile knowledge is invaluable to tackle the enormous logistical challenges to re-allocate resources and target susceptible areas for aggressive testing and tracing to mitigate transmission. BioMed Central 2020-06-29 /pmc/articles/PMC7321716/ /pubmed/32594909 http://dx.doi.org/10.1186/s12916-020-01646-2 Text en © The Author(s) 2020 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://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 Article
Verhagen, Mark D.
Brazel, David M.
Dowd, Jennifer Beam
Kashnitsky, Ilya
Mills, Melinda C.
Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales
title Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales
title_full Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales
title_fullStr Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales
title_full_unstemmed Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales
title_short Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales
title_sort forecasting spatial, socioeconomic and demographic variation in covid-19 health care demand in england and wales
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7321716/
https://www.ncbi.nlm.nih.gov/pubmed/32594909
http://dx.doi.org/10.1186/s12916-020-01646-2
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