Sharmistha Mishra1, Linwei Wang2, Huiting Ma2, Kristy C Y Yiu2, J Michael Paterson2, Eliane Kim2, Michael J Schull2, Victoria Pequegnat2, Anthea Lee2, Lisa Ishiguro2, Eric Coomes2, Adrienne Chan2, Mark Downing2, David Landsman2, Sharon Straus2, Matthew Muller2. 1. Division of Infectious Diseases, Department of Medicine (Mishra, Coomes, Chan, Muller); MAP Centre for Urban Health Solutions (Mishra, Wang, Ma, Yiu, Landsman), Li Ka Shing Knowledge Institute, St. Michael's Hospital; Institute of Health Policy, Management and Evaluation (Paterson, Schull), University of Toronto; ICES (Paterson, Kim, Schull, Ishiguro); Decision Support (Pequegnat, Lee), Unity Health Toronto; Division of Infectious Diseases (Chan), Sunnybrook Health Sciences, University of Toronto; Infection Prevention and Control (Downing), St. Joseph's Health Centre, Unity Health Toronto; Department of Medicine (Straus), St. Michael's Hospital, University of Toronto; Infection Prevention and Control (Muller), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont. sharmistha.mishra@utoronto.ca. 2. Division of Infectious Diseases, Department of Medicine (Mishra, Coomes, Chan, Muller); MAP Centre for Urban Health Solutions (Mishra, Wang, Ma, Yiu, Landsman), Li Ka Shing Knowledge Institute, St. Michael's Hospital; Institute of Health Policy, Management and Evaluation (Paterson, Schull), University of Toronto; ICES (Paterson, Kim, Schull, Ishiguro); Decision Support (Pequegnat, Lee), Unity Health Toronto; Division of Infectious Diseases (Chan), Sunnybrook Health Sciences, University of Toronto; Infection Prevention and Control (Downing), St. Joseph's Health Centre, Unity Health Toronto; Department of Medicine (Straus), St. Michael's Hospital, University of Toronto; Infection Prevention and Control (Muller), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.
Abstract
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. Copyright 2020, Joule Inc. or its licensors.
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. Copyright 2020, Joule Inc. or its licensors.
Authors: Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng Journal: N Engl J Med Date: 2020-01-29 Impact factor: 176.079
Authors: Stephen A Lauer; Kyra H Grantz; Qifang Bi; Forrest K Jones; Qulu Zheng; Hannah R Meredith; Andrew S Azman; Nicholas G Reich; Justin Lessler Journal: Ann Intern Med Date: 2020-03-10 Impact factor: 25.391
Authors: Costase Ndayishimiye; Christoph Sowada; Patrycja Dyjach; Agnieszka Stasiak; John Middleton; Henrique Lopes; Katarzyna Dubas-Jakóbczyk Journal: Int J Environ Res Public Health Date: 2022-07-04 Impact factor: 4.614
Authors: Hannah Chung; Mahmoud Azimaee; Susan E Bronskill; Rosario Cartagena; Astrid Guttmann; Minnie M Ho; Lisa Ishiguro; Jeffrey C Kwong; J Michael Paterson; Sujitha Ratnasingham; Laura C Rosella; Michael J Schull; Marian J Vermeulen; J Charles Victor Journal: Int J Popul Data Sci Date: 2022-01-18
Authors: Terry Lee; Matthew P Cheng; Donald C Vinh; Todd C Lee; Karen C Tran; Brent W Winston; David Sweet; John H Boyd; Keith R Walley; Greg Haljan; Allison McGeer; François Lamontagne; Robert Fowler; David Maslove; Joel Singer; David M Patrick; John C Marshall; Kevin D Burns; Srinivas Murthy; Puneet K Mann; Geraldine Hernandez; Kathryn Donohoe; Genevieve Rocheleau; James A Russell Journal: CMAJ Open Date: 2022-04-19
Authors: Ekin Soydan; Gokhan Ceylan; Sevgi Topal; Pinar Hepduman; Gulhan Atakul; Mustafa Colak; Ozlem Sandal; Ferhat Sari; Utku Karaarslan; Dominik Novotni; Marcus J Schultz; Hasan Agin Journal: Front Med (Lausanne) Date: 2022-08-25