COVID-19 Demographics, Acute Care Resource Use and Mortality by Age and Sex in Ontario, Canada: Population-based Retrospective Cohort Analysis

Author:

Mac StephenORCID,Barrett KaliORCID,Khan Yasin A.ORCID,Naimark David MJORCID,Rosella LauraORCID,Ximenes RaphaelORCID,Sander BeateORCID

Abstract

AbstractBackgroundUnderstanding resource use for COVID-19 is critical. We conducted a population-based cohort study using public health data to describe COVID-19 associated age- and sex-specific acute care use, length of stay (LOS), and mortality.MethodsWe used Ontario’s Case and Contact Management (CCM) Plus database of individuals who tested positive for COVID-19 in Ontario from March 1 to September 30, 2020 to determine age- and sex-specific hospitalizations, intensive care unit (ICU) admissions, invasive mechanical ventilation (IMV) use, LOS, and mortality. We stratified analyses by month of infection to study temporal trends and conducted subgroup analyses by long-term care residency.ResultsDuring the observation period, 56,476 COVID-19 cases were reported (72% < 60 years, 52% female). The proportion of cases shifted from older populations (> 60 years) to younger populations (10-39 years) over time. Overall, 10% of individuals were hospitalized, of those 22% were admitted to ICU, and 60% of those used IMV. Mean LOS for individuals in the ward, ICU without IMV, and ICU with IMV was 12.8, 8.5, 20.5 days, respectively. Mortality for individuals receiving care in the ward, ICU without IMV, and ICU with IMV was 24%, 30%, and 45%, respectively. All outcomes varied by age and decreased over time, overall and within age groups.InterpretationThis descriptive study shows acute care use and mortality varying by age, and decreasing between March and September in Ontario. Improvements in clinical practice and changing risk distributions among those infected may contribute to fewer severe outcomes among those infected with COVID-19.

Publisher

Cold Spring Harbor Laboratory

Reference22 articles.

1. Public Health Ontario. COVID-19 – What We Know So Far About… Social Determinants of Health [Internet]. 2020 May [cited 2020 Oct 9]. Available from: https://www.publichealthontario.ca/-/media/documents/ncov/covid-wwksf/2020/05/what-we-know-social-determinants-health.pdf?la=en

2. COVID-19 exacerbating inequalities in the US;Lancet [Internet],2020

3. Durrani T. COVID-19 disproportionately affects those living in poverty. And this impacts us all [Internet]. Healthy Debate. 2020 [cited 2020 Oct 9]. Available from: https://healthydebate.ca/2020/03/topic/covid-19-low-income-poverty

4. Sex□ and Age□Specific Differences in COVID□19 Testing, Cases, and Outcomes: A Population□Wide Study in Ontario, Canada;J Am Geriatr Soc [Internet],2020

5. Papst I , Li M , Champredon D , Bolker BM , Earn DJ . Age-dependence of healthcare interventions for SARS-CoV-2 1 infection in Ontario, Canada 2. medRxiv [Internet]. 2020 Sep 3 [cited 2020 Oct 25];2020–9. Available from: https://doi.org/10.1101/2020.09.01.20186395

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3