Projecting demand for critical care beds during COVID-19 outbreaks in Canada

CMAJ. 2020 May 11;192(19):E489-E496. doi: 10.1503/cmaj.200457. Epub 2020 Apr 8.

Abstract

Background: Increasing numbers of coronavirus disease 2019 (COVID-19) cases in Canada may create substantial demand for hospital admission and critical care. We evaluated the extent to which self-isolation of mildly ill people delays the peak of outbreaks and reduces the need for this care in each Canadian province.

Methods: We developed a computational model and simulated scenarios for COVID-19 outbreaks within each province. Using estimates of COVID-19 characteristics, we projected the hospital and intensive care unit (ICU) bed requirements without self-isolation, assuming an average number of 2.5 secondary cases, and compared scenarios in which different proportions of mildly ill people practised self-isolation 24 hours after symptom onset.

Results: Without self-isolation, the peak of outbreaks would occur in the first half of June, and an average of 569 ICU bed days per 10 000 population would be needed. When 20% of cases practised self-isolation, the peak was delayed by 2-4 weeks, and ICU bed requirement was reduced by 23.5% compared with no self-isolation. Increasing self-isolation to 40% reduced ICU use by 53.6% and delayed the peak of infection by an additional 2-4 weeks. Assuming current ICU bed occupancy rates above 80% and self-isolation of 40%, demand would still exceed available (unoccupied) ICU bed capacity.

Interpretation: At the peak of COVID-19 outbreaks, the need for ICU beds will exceed the total number of ICU beds even with self-isolation at 40%. Our results show the coming challenge for the health care system in Canada and the potential role of self-isolation in reducing demand for hospital-based and ICU care.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bed Occupancy / statistics & numerical data*
  • COVID-19
  • Canada / epidemiology
  • Coronavirus Infections / epidemiology
  • Coronavirus Infections / therapy*
  • Critical Care / statistics & numerical data*
  • Disease Outbreaks
  • Health Services Needs and Demand / statistics & numerical data
  • Hospital Bed Capacity / statistics & numerical data*
  • Humans
  • Models, Statistical
  • Pandemics
  • Pneumonia, Viral / epidemiology
  • Pneumonia, Viral / therapy*