TY - JOUR T1 - Estimated surge in hospital and intensive care admission because of the coronavirus disease 2019 pandemic in the Greater Toronto Area, Canada: a mathematical modelling study JF - CMAJ Open JO - CMAJ SP - E593 LP - E604 DO - 10.9778/cmajo.20200093 VL - 8 IS - 3 AU - Sharmistha Mishra AU - Linwei Wang AU - Huiting Ma AU - Kristy C.Y. Yiu AU - J. Michael Paterson AU - Eliane Kim AU - Michael J. Schull AU - Victoria Pequegnat AU - Anthea Lee AU - Lisa Ishiguro AU - Eric Coomes AU - Adrienne Chan AU - Mark Downing AU - David Landsman AU - Sharon Straus AU - Matthew Muller Y1 - 2020/07/01 UR - http://www.cmajopen.ca/content/8/3/E593.abstract N2 - Background: In pandemics, local hospitals need to anticipate a surge in health care needs. We examined the modelled surge because of the coronavirus disease 2019 (COVID-19) pandemic that was used to inform the early hospital-level response against cases as they transpired.Methods: To estimate hospital-level surge in March and April 2020, we simulated a range of scenarios of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread in the Greater Toronto Area (GTA), Canada, using the best available data at the time. We applied outputs to hospital-specific data to estimate surge over 6 weeks at 2 hospitals (St. Michael’s Hospital and St. Joseph’s Health Centre). We examined multiple scenarios, wherein the default (R0 = 2.4) resembled the early trajectory (to Mar. 25, 2020), and compared the default model projections with observed COVID-19 admissions in each hospital from Mar. 25 to May 6, 2020.Results: For the hospitals to remain below non-ICU bed capacity, the default pessimistic scenario required a reduction in non-COVID-19 inpatient care by 38% and 28%, respectively, with St. Michael’s Hospital requiring 40 new ICU beds and St. Joseph’s Health Centre reducing its ICU beds for non-COVID-19 care by 6%. The absolute difference between default-projected and observed census of inpatients with COVID-19 at each hospital was less than 20 from Mar. 25 to Apr. 11; projected and observed cases diverged widely thereafter. Uncertainty in local epidemiological features was more influential than uncertainty in clinical severity.Interpretation: Scenario-based analyses were reliable in estimating short-term cases, but would require frequent re-analyses. Distribution of the city’s surge was expected to vary across hospitals, and community-level strategies were key to mitigating each hospital’s surge. ER -