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Efficacy of a "stay-at-home" policy on SARS-CoV-2 transmission in Toronto, Canada: a mathematical modelling study.
Yuan, Pei; Li, Juan; Aruffo, Elena; Gatov, Evgenia; Li, Qi; Zheng, Tingting; Ogden, Nicholas H; Sander, Beate; Heffernan, Jane; Collier, Sarah; Tan, Yi; Li, Jun; Arino, Julien; Bélair, Jacques; Watmough, James; Kong, Jude Dzevela; Moyles, Iain; Zhu, Huaiping.
  • Yuan P; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Li J; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Aruffo E; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Gatov E; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Li Q; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Zheng T; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Ogden NH; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Sander B; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Heffernan J; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Collier S; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Tan Y; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Li J; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Arino J; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Bélair J; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Watmough J; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Kong JD; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Moyles I; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
  • Zhu H; Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Cen
CMAJ Open ; 10(2): E367-E378, 2022.
Article in English | MEDLINE | ID: covidwho-1798680
ABSTRACT

BACKGROUND:

Globally, nonpharmaceutical interventions for COVID-19, including stay-at-home policies, limitations on gatherings and closure of public spaces, are being lifted. We explored the effect of lifting a stay-at-home policy on virus resurgence under different conditions.

METHODS:

Using confirmed case data from Toronto, Canada, between Feb. 24 and June 24, 2020, we ran a compartmental model with household structure to simulate the impact of the stay-at-home policy considering different levels of compliance. We estimated threshold values for the maximum number of contacts, probability of transmission and testing rates required for the safe reopening of the community.

RESULTS:

After the implementation of the stay-at-home policy, the contact rate outside the household fell by 39% (from 11.58 daily contacts to 7.11). The effective reproductive number decreased from 3.56 (95% confidence interval [CI] 3.02-4.14) on Mar. 12 to 0.84 (95% CI 0.79-0.89) on May 6. Strong adherence to stay-at-home policies appeared to prevent SARS-CoV-2 resurgence, but extending the duration of stay-at-home policies beyond 2 months had little added effect on cumulative cases (25 958 for 65 days of a stay-at-home policy and 23 461 for 95 days, by July 2, 2020) and deaths (1404 for 65 days and 1353 for 95 days). To avoid a resurgence, the average number of contacts per person per day should be kept below 9, with strict nonpharmaceutical interventions in place.

INTERPRETATION:

Our study demonstrates that the stay-at-home policy implemented in Toronto in March 2020 had a substantial impact on mitigating the spread of SARS-CoV-2. In the context of the early pandemic, before the emergence of variants of concern, reopening schools and workplaces was possible only with other nonpharmaceutical interventions in place.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study Topics: Variants Limits: Humans Country/Region as subject: North America Language: English Journal: CMAJ Open Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study Topics: Variants Limits: Humans Country/Region as subject: North America Language: English Journal: CMAJ Open Year: 2022 Document Type: Article