Novel methods for estimating the instantaneous and overall COVID-19 case fatality risk among care home residents in England

The COVID-19 pandemic has had high mortality rates in the elderly and frail worldwide, particularly in care homes. This is driven by the difficulty of isolating care homes from the wider community, the large population sizes within care facilities (relative to typical households), and the age/frailt...

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Published in:	PLoS computational biology Vol. 18; no. 10; p. e1010554
Main Authors:	Overton, Christopher E., Webb, Luke, Datta, Uma, Fursman, Mike, Hardstaff, Jo, Hiironen, Iina, Paranthaman, Karthik, Riley, Heather, Sedgwick, James, Verne, Julia, Willner, Steve, Pellis, Lorenzo, Hall, Ian
Format:	Journal Article
Language:	English
Published:	San Francisco Public Library of Science 24.10.2022 Public Library of Science (PLoS)
Subjects:	Age Analysis Biology and Life Sciences Casualties China Coronaviruses COVID-19 Epidemics Estimates Fatalities Health risks Households Infections Medicine and Health Sciences Mortality Mortality risk Nursing homes Pandemics People and Places Public health Regions Risk Statistical methods Time series Trends United Kingdom Viral diseases United Kingdom China United Kingdom > UK England
ISSN:	1553-7358, 1553-734X, 1553-7358
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Abstract	The COVID-19 pandemic has had high mortality rates in the elderly and frail worldwide, particularly in care homes. This is driven by the difficulty of isolating care homes from the wider community, the large population sizes within care facilities (relative to typical households), and the age/frailty of the residents. To quantify the mortality risk posed by disease, the case fatality risk (CFR) is an important tool. This quantifies the proportion of cases that result in death. Throughout the pandemic, CFR amongst care home residents in England has been monitored closely. To estimate CFR, we apply both novel and existing methods to data on deaths in care homes, collected by Public Health England and the Care Quality Commission. We compare these different methods, evaluating their relative strengths and weaknesses. Using these methods, we estimate temporal trends in the instantaneous CFR (at both daily and weekly resolutions) and the overall CFR across the whole of England, and dis-aggregated at regional level. We also investigate how the CFR varies based on age and on the type of care required, dis-aggregating by whether care homes include nursing staff and by age of residents. This work has contributed to the summary of measures used for monitoring the UK epidemic.
AbstractList	The COVID-19 pandemic has had high mortality rates in the elderly and frail worldwide, particularly in care homes. This is driven by the difficulty of isolating care homes from the wider community, the large population sizes within care facilities (relative to typical households), and the age/frailty of the residents. To quantify the mortality risk posed by disease, the case fatality risk (CFR) is an important tool. This quantifies the proportion of cases that result in death. Throughout the pandemic, CFR amongst care home residents in England has been monitored closely. To estimate CFR, we apply both novel and existing methods to data on deaths in care homes, collected by Public Health England and the Care Quality Commission. We compare these different methods, evaluating their relative strengths and weaknesses. Using these methods, we estimate temporal trends in the instantaneous CFR (at both daily and weekly resolutions) and the overall CFR across the whole of England, and dis-aggregated at regional level. We also investigate how the CFR varies based on age and on the type of care required, dis-aggregating by whether care homes include nursing staff and by age of residents. This work has contributed to the summary of measures used for monitoring the UK epidemic. During an epidemic, the case fatality risk (CFR), i.e. the probability that an individual dies after testing positive for a disease, is a key parameter informing the public health response. However, calculating the CFR is not trivial, since there are cases who may die in the future but have not died yet. Therefore, statistical methods are required to correct for the distribution of times between testing positive and dying. In this paper, we derive multiple methods, some existing and some novel, within a consistent methodological framework. This allows us to understand how these different approaches are related and their relative strengths and weaknesses. During the COVID-19 pandemic, care homes have been particularly affected, due to the high risk of COVID-19-associated mortality in the frail and elderly. We apply our CFR methods to data from English care homes to analyse changes in the care home CFR throughout the pandemic. The COVID-19 pandemic has had high mortality rates in the elderly and frail worldwide, particularly in care homes. This is driven by the difficulty of isolating care homes from the wider community, the large population sizes within care facilities (relative to typical households), and the age/frailty of the residents. To quantify the mortality risk posed by disease, the case fatality risk (CFR) is an important tool. This quantifies the proportion of cases that result in death. Throughout the pandemic, CFR amongst care home residents in England has been monitored closely. To estimate CFR, we apply both novel and existing methods to data on deaths in care homes, collected by Public Health England and the Care Quality Commission. We compare these different methods, evaluating their relative strengths and weaknesses. Using these methods, we estimate temporal trends in the instantaneous CFR (at both daily and weekly resolutions) and the overall CFR across the whole of England, and dis-aggregated at regional level. We also investigate how the CFR varies based on age and on the type of care required, dis-aggregating by whether care homes include nursing staff and by age of residents. This work has contributed to the summary of measures used for monitoring the UK epidemic. The COVID-19 pandemic has had high mortality rates in the elderly and frail worldwide, particularly in care homes. This is driven by the difficulty of isolating care homes from the wider community, the large population sizes within care facilities (relative to typical households), and the age/frailty of the residents. To quantify the mortality risk posed by disease, the case fatality risk (CFR) is an important tool. This quantifies the proportion of cases that result in death. Throughout the pandemic, CFR amongst care home residents in England has been monitored closely. To estimate CFR, we apply both novel and existing methods to data on deaths in care homes, collected by Public Health England and the Care Quality Commission. We compare these different methods, evaluating their relative strengths and weaknesses. Using these methods, we estimate temporal trends in the instantaneous CFR (at both daily and weekly resolutions) and the overall CFR across the whole of England, and dis-aggregated at regional level. We also investigate how the CFR varies based on age and on the type of care required, dis-aggregating by whether care homes include nursing staff and by age of residents. This work has contributed to the summary of measures used for monitoring the UK epidemic.The COVID-19 pandemic has had high mortality rates in the elderly and frail worldwide, particularly in care homes. This is driven by the difficulty of isolating care homes from the wider community, the large population sizes within care facilities (relative to typical households), and the age/frailty of the residents. To quantify the mortality risk posed by disease, the case fatality risk (CFR) is an important tool. This quantifies the proportion of cases that result in death. Throughout the pandemic, CFR amongst care home residents in England has been monitored closely. To estimate CFR, we apply both novel and existing methods to data on deaths in care homes, collected by Public Health England and the Care Quality Commission. We compare these different methods, evaluating their relative strengths and weaknesses. Using these methods, we estimate temporal trends in the instantaneous CFR (at both daily and weekly resolutions) and the overall CFR across the whole of England, and dis-aggregated at regional level. We also investigate how the CFR varies based on age and on the type of care required, dis-aggregating by whether care homes include nursing staff and by age of residents. This work has contributed to the summary of measures used for monitoring the UK epidemic.
Audience	Academic
Author	Webb, Luke Paranthaman, Karthik Willner, Steve Hiironen, Iina Fursman, Mike Pellis, Lorenzo Hall, Ian Overton, Christopher E. Riley, Heather Hardstaff, Jo Verne, Julia Datta, Uma Sedgwick, James
AuthorAffiliation	10 Emergency Preparedness, Health Protection Division, Public Health England, London, United Kingdom 2 Clinical data science unit, Manchester University NHS Foundation Trust, Manchester, United Kingdom 11 Alan Turing Institute, London, United Kingdom 9 Office for Health Improvement and Disparities, Department of Health and Social Care, London, United Kingdom University of Zurich, SWITZERLAND 3 Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/, Cambridge, United Kingdom 1 Department of Mathematics, University of Manchester, Manchester, United Kingdom 4 Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom 8 Adult Social Care Team, Public Health England, London, United Kingdom 6 Care Quality Commission, London, United Kingdom 7 Field Service, National Infection Service, Public Health England, London, United Kingdom 5 Data, Analytics and Surveillance, UK Health Security Agency, London, United Kingdom
AuthorAffiliation_xml	– name: 2 Clinical data science unit, Manchester University NHS Foundation Trust, Manchester, United Kingdom – name: 5 Data, Analytics and Surveillance, UK Health Security Agency, London, United Kingdom – name: 3 Joint UNIversities Pandemic and Epidemiological Research, https://maths.org/juniper/, Cambridge, United Kingdom – name: 6 Care Quality Commission, London, United Kingdom – name: 10 Emergency Preparedness, Health Protection Division, Public Health England, London, United Kingdom – name: 1 Department of Mathematics, University of Manchester, Manchester, United Kingdom – name: 4 Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom – name: 7 Field Service, National Infection Service, Public Health England, London, United Kingdom – name: 8 Adult Social Care Team, Public Health England, London, United Kingdom – name: University of Zurich, SWITZERLAND – name: 9 Office for Health Improvement and Disparities, Department of Health and Social Care, London, United Kingdom – name: 11 Alan Turing Institute, London, United Kingdom
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SubjectTerms	Age Analysis Biology and Life Sciences Casualties China Coronaviruses COVID-19 Epidemics Estimates Fatalities Health risks Households Infections Medicine and Health Sciences Mortality Mortality risk Nursing homes Pandemics People and Places Public health Regions Risk Statistical methods Time series Trends United Kingdom Viral diseases
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Title	Novel methods for estimating the instantaneous and overall COVID-19 case fatality risk among care home residents in England
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