Modelling scenarios of the epidemic of COVID-19 in Canada
- DOI
- Language of the publication
- English
- Date
- 2020-06-04
- Type
- Article
- Author(s)
- Ogden, Nick H.
- Fazil, Aamir
- Arino, Julien
- Berthiaume, Philippe
- Fisman, David N.
- Greer, Amy L.
- Ludwig, Antoinette
- Ng, Victoria
- Tuite, Ashleigh R.
- Turgeon, Patricia
- Waddell, Lisa A.
- Wu, Jianhong
- Publisher
- Public Health Agency of Canada
Abstract
BACKGROUND: Severe acute respiratory syndrome virus 2 (SARS-CoV-2), likely a bat-origin coronavirus, spilled over from wildlife to humans in China in late 2019, manifesting as a respiratory disease. Coronavirus disease 2019 (COVID-19) spread initially within China and then globally, resulting in a pandemic. OBJECTIVE: This article describes predictive modelling of COVID-19 in general, and efforts within the Public Health Agency of Canada to model the effects of non-pharmaceutical interventions (NPIs) on transmission of SARS-CoV-2 in the Canadian population to support public health decisions. METHODS: The broad objectives of two modelling approaches, 1) an agent-based model and 2) a deterministic compartmental model, are described and a synopsis of studies is illustrated using a model developed in Analytica 5.3 software. RESULTS: Without intervention, more than 70% of the Canadian population may become infected. Non-pharmaceutical interventions, applied with an intensity insufficient to cause the epidemic to die out, reduce the attack rate to 50% or less, and the epidemic is longer with a lower peak. If NPIs are lifted early, the epidemic may rebound, resulting in high percentages (more than 70%) of the population affected. If NPIs are applied with intensity high enough to cause the epidemic to die out, the attack rate can be reduced to between 1% and 25% of the population. CONCLUSION: Applying NPIs with intensity high enough to cause the epidemic to die out would seem to be the preferred choice. Lifting disruptive NPIs such as shut-downs must be accompanied by enhancements to other NPIs to prevent new introductions and to identify and control any new transmission chains.
Plain language summary
This article describes predictive modelling of COVID-19 in general, and efforts within the Public Health Agency of Canada to model the effects of non-pharmaceutical interventions (NPIs) on transmission of SARS-CoV-2 in the Canadian population to support public health decisions. The broad objectives of two modelling approaches, 1) an agent-based model and 2) a deterministic compartmental model, are described and a synopsis of studies is illustrated. Without intervention, more than 70% of the Canadian population may become infected. Non-pharmaceutical interventions, applied with an intensity insufficient to cause the epidemic to die out, reduce the attack rate to 50% or less, and the epidemic is longer with a lower peak. If NPIs are lifted early, the epidemic may rebound, resulting in high percentages (more than 70%) of the population affected. If NPIs are applied with intensity high enough to cause the epidemic to die out, the attack rate can be reduced to between 1% and 25% of the population. Applying NPIs with intensity high enough to cause the epidemic to die out would seem to be the preferred choice.
Subject
- Health
Rights
Pagination
198-204
Peer review
Yes
Open access level
Gold
Identifiers
- PubMed ID
- 32673384
- ISSN
- 1481-8531
Article
- Journal title
- Canada Communicable Disease Report
- Journal volume
- 46
- Journal issue
- 6
Relation
- Is translation of:
- https://open-science.canada.ca/handle/123456789/3055