Abstract

Daily activities and mobility dynamics play a central role in the spread of COVID-19. Close physical interactions involved by certain daily activities help transmit the virus. Travel required by the spatial distribution of activities contributes to the propagation of the virus. In order to control and limit this propagation, it is critical to understand the contribution of daily activities to the dynamics of COVID-19. This paper investigates the connection between daily activities, their distribution in space and time, the characteristics of the individuals performing them, and the transmission of the virus. A business-as-usual agent-based simulation scenario of Montreal, Canada is used. To address this research question, we use two agent-based models: MATSIM and EPISIM. MATSIM simulates daily activities and mobility dynamics of the population. EPISIM simulates the spread of the virus in the population using contact networks computed by MATSIM. A synthetic population of Montreal is defined to replicate the main observed sociodemographic characteristics of Montrealers as well as their activity and mobility patterns. The definition of the synthetic population relies on various data sources: household travel survey, census, real estate, car ownership, and housing data. In the business-as-usual scenario, findings underline the significant role of home, work, and school activities in community transmission of COVID-19. Secondary activities, including leisure and shopping, also help spread the virus, but to a lesser degree in comparison with primary activities. The risk of infection in the workplace depends on the economic sector. Healthcare workers are, by far, the most exposed workers to the virus. Workplace infections mirror the gender-biased job market of Montreal. Most infections in the healthcare and educational services are among women. Most infections in the manufacturing, construction, transportation, and warehousing industries are among men. In the business-as-usual scenario where community transmission is high, primary and secondary school-aged children are found to be a major transmission vector of the virus. Finally, simulation results suggest that the risk of infection in the public transportation system is low.

Highlights

  • Since its onset, the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), responsible for the COVID-19 disease1, has swept through the globe to ravage more than 200 countries

  • To fill this research gap, we investigate the following research question: how do daily activities, taken individually and in combination, their distribution in space and time, and the characteristics of the individuals involved in them contribute to the COVID-19 pandemic? We investigate this connection in the case of Montreal, Canada using an agentbased approach

  • For agents working in the health and social assistance sector, half of their work time is assumed in close interaction with patients and other colleagues

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Summary

INTRODUCTION

The severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), responsible for the COVID-19 disease, has swept through the globe to ravage more than 200 countries. Like leisure, social gatherings, and shopping, the lack of appropriate data limits the investigation of their specific contribution to community transmission, especially in contexts where non-essential activities are restricted (Baicker et al, 2020; Chang et al, 2020) In this context, general recommendations have been issued to limit social activities that involve close interactions (within 2 m, for example) for periods of time longer than a reference threshold (15 min daily, for example), especially in enclosed places (Centers for Disease Control and Prevention (CDC), 2020; Government of Canada, 2020). Findings of this research can help improve our understanding of the current pandemic, and help design efficient policy mitigation measures

METHODS AND MATERIALS
MATSIM
EPISIM
Materials
RESULTS
Do Activities Contribute Equally to the Spread of COVID-19?
Daily Plans and the Risk of Infection
Spatial Clusters of Infections
DISCUSSION AND POLICY
What Is More Riskier
Why do Most Infections in Secondary Activities Occur Late in the Day?
Business Closures
Infection in Public Transit
How Census Data Can Help Limit Infections?
CONCLUSION
LIMITATIONS AND FUTURE
DATA AVAILABILITY STATEMENT
Full Text
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