Modeling the Effect of Population-Wide Vaccination on the Evolution of COVID-19 Epidemic in Canada
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Abstract
Population-wide vaccination is critical for containing the COVID-19 pandemic when combined with effective testing and prevention measures. Since the beginning of the COVID-19 outbreak, several companies worked tirelessly for the development of an efficient vaccine that would put an end to this pandemic. Today, a number of COVID-19 vaccines have been approved for use by a number of national regulatory organizations. Vaccination campaigns have already started in several countries with different daily-vaccination rates depending on the country’s vaccination capacity. Therefore, we find it timely and extremely important to conduct a study on the effect of population-wide vaccination campaigns on the evolution of the COVID-19 epidemic. To this end, we propose a new deterministic mathematical model to forecast the COVID-19 epidemic evolution under the effect of vaccination and vaccine efficacy. This model, referred to as SIRV, consists of a compartmental SIR (susceptible, infectious and removed) model augmented with an additional state V representing the effectively vaccinated population as well as two inputs representing the daily-vaccination rate and the vaccine efficacy. Using our SIRV model, we predict the evolution of the COVID-19 epidemic in Canada and its most affected provinces (Ontario, Quebec, British Columbia, Alberta, Saskatchewan, and Manitoba), for different daily vaccination rates and vaccine efficacy. Projections suggest that, without vaccination, 219, 000 lives could be lost across Canada by the end of 2021 due to COVID-19. The ongoing vaccination campaign across Canada seems to unfold relatively slowly at an average daily rate close to 1 / 2 vaccine per 1, 000 population. At this pace, we could be saving more than 77, 496 lives by the end of the year. Doubling the current vaccination efforts (1 vaccine per day per 1, 000 population) could be sufficient to save 125, 839 lives in Canada during the current year 2021. We would like to point out that our study assumes that the vaccine is perfectly safe without any short or long term side-effects. This study has been conducted independently at arm’s length from vaccine manufacturers, using the available data from Canada health services. This study can be easily adapted to other places in the world.
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SciScore for 10.1101/2021.02.05.21250572: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank…
SciScore for 10.1101/2021.02.05.21250572: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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