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Open AccessArticle

De-Escalation by Reversing the Escalation with a Stronger Synergistic Package of Contact Tracing, Quarantine, Isolation and Personal Protection: Feasibility of Preventing a COVID-19 Rebound in Ontario, Canada, as a Case Study

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Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
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The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi’an Jiaotong University, Xi’an 710049, China
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CDLab—Computational Dynamics Laboratory, Department of Mathematics, Computer Science and Physics, University of Udine, 33100 Udine, Italy
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Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH 45221-0025, USA
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Modelling Infection and Immunity Lab, Centre for Disease Modelling, Department of Mathematics & Statistics, York University, Toronto, ON M3J 1P3, Canada
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Disaster & Emergency Management, School of Administrative Studies & Advanced Disaster & Emergency Rapid-response Simulation (ADERSIM), York University, Toronto, ON M3J 1P3, Canada
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Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St. Hyacinthe, QC J2S 2M2, Canada
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Author to whom correspondence should be addressed.
Equal contribution.
Biology 2020, 9(5), 100; https://doi.org/10.3390/biology9050100
Received: 1 May 2020 / Revised: 14 May 2020 / Accepted: 14 May 2020 / Published: 16 May 2020
(This article belongs to the Special Issue Theories and Models on COVID-19 Epidemics)
Since the beginning of the COVID-19 pandemic, most Canadian provinces have gone through four distinct phases of social distancing and enhanced testing. A transmission dynamics model fitted to the cumulative case time series data permits us to estimate the effectiveness of interventions implemented in terms of the contact rate, probability of transmission per contact, proportion of isolated contacts, and detection rate. This allows us to calculate the control reproduction number during different phases (which gradually decreased to less than one). From this, we derive the necessary conditions in terms of enhanced social distancing, personal protection, contact tracing, quarantine/isolation strength at each escalation phase for the disease control to avoid a rebound. From this, we quantify the conditions needed to prevent epidemic rebound during de-escalation by simply reversing the escalation process. View Full-Text
Keywords: COVID-19; pandemics; physical and social distancing relaxation; reopening; mathematical model COVID-19; pandemics; physical and social distancing relaxation; reopening; mathematical model
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Tang, B.; Scarabel, F.; Bragazzi, N.L.; McCarthy, Z.; Glazer, M.; Xiao, Y.; Heffernan, J.M.; Asgary, A.; Ogden, N.H.; Wu, J. De-Escalation by Reversing the Escalation with a Stronger Synergistic Package of Contact Tracing, Quarantine, Isolation and Personal Protection: Feasibility of Preventing a COVID-19 Rebound in Ontario, Canada, as a Case Study. Biology 2020, 9, 100.

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