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Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19

OBJECTIVES: Reporting of COVID-19 cases, deaths and testing has often lacked context for appropriate assessment of disease burden within risk groups. The research considers how routine surveillance data might provide initial insights and identify risk factors, setting COVID-19 deaths early in the pa...

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Autores principales: Clough, Helen E, McIntyre, K Marie, Patterson, Grace E, Harris, John P, Rushton, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7871230/
https://www.ncbi.nlm.nih.gov/pubmed/33558359
http://dx.doi.org/10.1136/bmjopen-2020-044707
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author Clough, Helen E
McIntyre, K Marie
Patterson, Grace E
Harris, John P
Rushton, Jonathan
author_facet Clough, Helen E
McIntyre, K Marie
Patterson, Grace E
Harris, John P
Rushton, Jonathan
author_sort Clough, Helen E
collection PubMed
description OBJECTIVES: Reporting of COVID-19 cases, deaths and testing has often lacked context for appropriate assessment of disease burden within risk groups. The research considers how routine surveillance data might provide initial insights and identify risk factors, setting COVID-19 deaths early in the pandemic into context. This will facilitate the understanding of wider consequences of a pandemic from the earliest stage, reducing fear, aiding in accurately assessing disease burden and ensuring appropriate disease mitigation. SETTING: UK, 2020. PARTICIPANTS: The study is a secondary analysis of routine, public domain, surveillance data and information from Office for National Statistics (ONS), National Health Service (NHS) 111 and Public Health England (PHE) on deaths and disease. PRIMARY AND SECONDARY OUTCOME MEASURES: Our principal focus is ONS data on deaths mentioning COVID-19 on the death certificate. We also consider information provided in NHS 111 and PHE data summaries. RESULTS: Deaths with COVID-19 significantly contributed to, yet do not entirely explain, abnormally elevated all-cause mortality in the UK from weeks 12–18 of 2020. Early in the UK epidemic, COVID-19 was the greatest threat to those with underlying illness, rarely endangering people aged under 40 years. COVID-19-related death rates differed by region, possibly reflecting underlying population structure. Risk of COVID-19-related death was greater for healthcare and social care staff and black, Asian and minority ethnic individuals, having allowed for documented risk factors. CONCLUSION: Early contextualisation of public health data is critical to recognising who gets sick, when and why. Understanding at-risk groups facilitates a targeted response considering indirect consequences of society’s reaction to a pandemic alongside disease-related impacts. COVID-19-related deaths mainly mirror historical patterns, and excess non-COVID-19-related deaths partly reflect reduced access to and uptake of healthcare during lockdown. Future outbreak response will improve through better understanding of connectivity between disease monitoring systems to aid interpretation of disease risk patterns, facilitating nuanced mitigation measures.
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spelling pubmed-78712302021-02-09 Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19 Clough, Helen E McIntyre, K Marie Patterson, Grace E Harris, John P Rushton, Jonathan BMJ Open Epidemiology OBJECTIVES: Reporting of COVID-19 cases, deaths and testing has often lacked context for appropriate assessment of disease burden within risk groups. The research considers how routine surveillance data might provide initial insights and identify risk factors, setting COVID-19 deaths early in the pandemic into context. This will facilitate the understanding of wider consequences of a pandemic from the earliest stage, reducing fear, aiding in accurately assessing disease burden and ensuring appropriate disease mitigation. SETTING: UK, 2020. PARTICIPANTS: The study is a secondary analysis of routine, public domain, surveillance data and information from Office for National Statistics (ONS), National Health Service (NHS) 111 and Public Health England (PHE) on deaths and disease. PRIMARY AND SECONDARY OUTCOME MEASURES: Our principal focus is ONS data on deaths mentioning COVID-19 on the death certificate. We also consider information provided in NHS 111 and PHE data summaries. RESULTS: Deaths with COVID-19 significantly contributed to, yet do not entirely explain, abnormally elevated all-cause mortality in the UK from weeks 12–18 of 2020. Early in the UK epidemic, COVID-19 was the greatest threat to those with underlying illness, rarely endangering people aged under 40 years. COVID-19-related death rates differed by region, possibly reflecting underlying population structure. Risk of COVID-19-related death was greater for healthcare and social care staff and black, Asian and minority ethnic individuals, having allowed for documented risk factors. CONCLUSION: Early contextualisation of public health data is critical to recognising who gets sick, when and why. Understanding at-risk groups facilitates a targeted response considering indirect consequences of society’s reaction to a pandemic alongside disease-related impacts. COVID-19-related deaths mainly mirror historical patterns, and excess non-COVID-19-related deaths partly reflect reduced access to and uptake of healthcare during lockdown. Future outbreak response will improve through better understanding of connectivity between disease monitoring systems to aid interpretation of disease risk patterns, facilitating nuanced mitigation measures. BMJ Publishing Group 2021-02-08 /pmc/articles/PMC7871230/ /pubmed/33558359 http://dx.doi.org/10.1136/bmjopen-2020-044707 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Epidemiology
Clough, Helen E
McIntyre, K Marie
Patterson, Grace E
Harris, John P
Rushton, Jonathan
Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19
title Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19
title_full Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19
title_fullStr Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19
title_full_unstemmed Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19
title_short Use of routine death and illness surveillance data to provide insight for UK pandemic planning: lessons from COVID-19
title_sort use of routine death and illness surveillance data to provide insight for uk pandemic planning: lessons from covid-19
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7871230/
https://www.ncbi.nlm.nih.gov/pubmed/33558359
http://dx.doi.org/10.1136/bmjopen-2020-044707
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