Age-dependence of healthcare interventions for COVID-19 in Ontario, Canada.


Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
12 04 2021
Historique:
received: 30 11 2020
accepted: 08 03 2021
entrez: 13 4 2021
pubmed: 14 4 2021
medline: 16 4 2021
Statut: epublish

Résumé

Patient age is one of the most salient clinical indicators of risk from COVID-19. Age-specific distributions of known SARS-CoV-2 infections and COVID-19-related deaths are available for many regions. Less attention has been given to the age distributions of serious medical interventions administered to COVID-19 patients, which could reveal sources of potential pressure on the healthcare system should SARS-CoV-2 prevalence increase, and could inform mass vaccination strategies. The aim of this study is to quantify the relationship between COVID-19 patient age and serious outcomes of the disease, beyond fatalities alone. We analysed 277,555 known SARS-CoV-2 infection records for Ontario, Canada, from 23 January 2020 to 16 February 2021 and estimated the age distributions of hospitalizations, Intensive Care Unit admissions, intubations, and ventilations. We quantified the probability of hospitalization given known SARS-CoV-2 infection, and of survival given COVID-19-related hospitalization. The distribution of hospitalizations peaks with a wide plateau covering ages 60-90, whereas deaths are concentrated in ages 80+. The estimated probability of hospitalization given known infection reaches a maximum of 27.8% at age 80 (95% CI 26.0%-29.7%). The probability of survival given hospitalization is nearly 100% for adults younger than 40, but declines substantially after this age; for example, a hospitalized 54-year-old patient has a 91.7% chance of surviving COVID-19 (95% CI 88.3%-94.4%). Our study demonstrates a significant need for hospitalization in middle-aged individuals and young seniors. This need is not captured by the distribution of deaths, which is heavily concentrated in very old ages. The probability of survival given hospitalization for COVID-19 is lower than is generally perceived for patients over 40. If acute care capacity is exceeded due to an increase in COVID-19 prevalence, the distribution of deaths could expand toward younger ages. These results suggest that vaccine programs should aim to prevent infection not only in old seniors, but also in young seniors and middle-aged individuals, to protect them from serious illness and to limit stress on the healthcare system.

Sections du résumé

BACKGROUND
Patient age is one of the most salient clinical indicators of risk from COVID-19. Age-specific distributions of known SARS-CoV-2 infections and COVID-19-related deaths are available for many regions. Less attention has been given to the age distributions of serious medical interventions administered to COVID-19 patients, which could reveal sources of potential pressure on the healthcare system should SARS-CoV-2 prevalence increase, and could inform mass vaccination strategies. The aim of this study is to quantify the relationship between COVID-19 patient age and serious outcomes of the disease, beyond fatalities alone.
METHODS
We analysed 277,555 known SARS-CoV-2 infection records for Ontario, Canada, from 23 January 2020 to 16 February 2021 and estimated the age distributions of hospitalizations, Intensive Care Unit admissions, intubations, and ventilations. We quantified the probability of hospitalization given known SARS-CoV-2 infection, and of survival given COVID-19-related hospitalization.
RESULTS
The distribution of hospitalizations peaks with a wide plateau covering ages 60-90, whereas deaths are concentrated in ages 80+. The estimated probability of hospitalization given known infection reaches a maximum of 27.8% at age 80 (95% CI 26.0%-29.7%). The probability of survival given hospitalization is nearly 100% for adults younger than 40, but declines substantially after this age; for example, a hospitalized 54-year-old patient has a 91.7% chance of surviving COVID-19 (95% CI 88.3%-94.4%).
CONCLUSIONS
Our study demonstrates a significant need for hospitalization in middle-aged individuals and young seniors. This need is not captured by the distribution of deaths, which is heavily concentrated in very old ages. The probability of survival given hospitalization for COVID-19 is lower than is generally perceived for patients over 40. If acute care capacity is exceeded due to an increase in COVID-19 prevalence, the distribution of deaths could expand toward younger ages. These results suggest that vaccine programs should aim to prevent infection not only in old seniors, but also in young seniors and middle-aged individuals, to protect them from serious illness and to limit stress on the healthcare system.

Identifiants

pubmed: 33845807
doi: 10.1186/s12889-021-10611-4
pii: 10.1186/s12889-021-10611-4
pmc: PMC8040357
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

706

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Auteurs

Irena Papst (I)

Center for Applied Mathematics, Cornell University, Ithaca, USA. ip98@cornell.edu.

Michael Li (M)

Department of Biology, McMaster University, Hamilton, Canada.
South African Centre for Epidemiological Modelling and Analysis, University of Stellenbosch, Stellenbosch, South Africa.

David Champredon (D)

Department of Pathology and Laboratory Medicine, Western University, London, Canada.

Benjamin M Bolker (BM)

Department of Biology, McMaster University, Hamilton, Canada.
Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Canada.
Department of Mathematics & Statistics, McMaster University, Hamilton, Canada.

Jonathan Dushoff (J)

Department of Biology, McMaster University, Hamilton, Canada.
South African Centre for Epidemiological Modelling and Analysis, University of Stellenbosch, Stellenbosch, South Africa.
Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Canada.

David J D Earn (DJ)

Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Canada.
Department of Mathematics & Statistics, McMaster University, Hamilton, Canada.
Department of Mathematics, University of Toronto, Toronto, Canada.

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