Abstract

The COVID-19 outbreak has caused two waves and spread to more than 90% of Canada’s provinces since it was first reported more than a year ago. During the COVID-19 epidemic, Canadian provinces have implemented many Non-Pharmaceutical Interventions (NPIs). However, the spread of the COVID-19 epidemic continues due to the complex dynamics of human mobility. We develop a meta-population network model to study the transmission dynamics of COVID-19. The model takes into account the heterogeneity of mitigation strategies in different provinces of Canada, such as the timing of implementing NPIs, the human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences due to work and recreation. To determine which activity is most closely related to the dynamics of COVID-19, we use the cross-correlation analysis to find that the positive correlation is the highest between the mobility data of parks and the weekly number of confirmed COVID-19 from February 15 to December 13, 2020. The average effective reproduction numbers in nine Canadian provinces are all greater than one during the time period, and NPIs have little impact on the dynamics of COVID-19 epidemics in Ontario and Saskatchewan. After November 20, 2020, the average infection probability in Alberta became the highest since the start of the COVID-19 epidemic in Canada. We also observe that human activities around residences do not contribute much to the spread of the COVID-19 epidemic. The simulation results indicate that social distancing and constricting human mobility is effective in mitigating COVID-19 transmission in Canada. Our findings can provide guidance for public health authorities in projecting the effectiveness of future NPIs.

Highlights

  • Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused coronavirus disease 2019 (COVID-19)

  • We fit the number of confirmed COVID-19 cases and deaths to the model, and estimate the average effective reproduction numbers, the transmission rate and the probability of a susceptible individual being infected in Alberta (AB), British Columbia (BC), Manitoba (MB), New Brunswick (NB), Newfoundland and Labrador (NL), Nova Scotia (NS), Ontario (ON), Quebec (QC), and Saskatchewan (SK) from February 15 to December 13, 2020

  • Mobility in Canada dropped sharply in March 2020: e.g., in March and April, 2020, the average percentage of retail and recreation visits changed from the baseline by -37.5%, the average percentage of grocery and pharmacy visits changed from the baseline by -12.6%, the average percentage of park visits changed from the baseline by -2.3%, the average percentage of transit station visits changed from the baseline by -49.0%, the average percentage of workplace visits changed from the baseline by -39.8%, and the average percentage of human mobility in residential areas changed from the baseline by 15.8%

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Summary

Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused coronavirus disease 2019 (COVID-19). Many mathematical models investigated the impacts of human mobility and NPIs on the spread of the COVID-19 epidemic. To evaluate the impacts of human mobility and NPIs on the spread of the COVID-19 epidemic in Canada, we develop a network model coupled with human mobilities in six categories of places, namely, retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences, and the timing and levels of implementing NPIs. We fit the number of confirmed COVID-19 cases and deaths to the model, and estimate the average effective reproduction numbers, the transmission rate and the probability of a susceptible individual being infected in Alberta (AB), British Columbia (BC), Manitoba (MB), New Brunswick (NB), Newfoundland and Labrador (NL), Nova Scotia (NS), Ontario (ON), Quebec (QC), and Saskatchewan (SK) from February 15 to December 13, 2020

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