Modelling COVID-19 transmission using IDSIM, an epidemiological-modelling desktop app with multi-level immunization capabilities.

Abstract

Background: : The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented demands on local public health units in Ontario, Canada, one of which was the need for in-house epidemiological modelling capabilities. The objective of this study is to develop a native Windows desktop app for epidemiological modelling, to be used by public health unit epidemiologists to predict COVID-19 transmission in Durham Region.

Methods: : The developed app is an implementation of a multi-stratified compartmental epidemiological model that can accommodate multiple virus variants and levels of vaccination, as well as public health measures such as physical distancing, contact tracing followed by quarantine and testing followed by isolation. It was used to investigate the effects of different factors on COVID-19 transmission, including vaccination coverage, vaccine effectiveness, waning of vaccine-induced immunity and the advent of the Omicron variant. The simulation start date was November 22, 2021.

Results: : For the Delta variant, at least 90% of the population would need to be vaccinated to achieve herd immunity. A Delta-variant-only epidemiological curve would be flattened from the start in the absence of immunity waning and within six months in the presence of immunity waning. The percentage of infections caused by the Omicron variant was forecast to increase from 1% to 97% in the first month of the simulation. Total Omicron infections were forecasted to be reduced, respectively, by 26% or 41% if 3,000 or 5,000 booster doses were administered per day.

Conclusion: : For the Delta variant, both natural and vaccination-induced immunity are necessary to achieve herd immunity, and waning of vaccine-induced immunity lengthens the time necessary to reach herd immunity. In the absence of additional public health measures, a wave driven by the Omicron variant was predicted to pose significant public health challenges with infections predicted to peak in 2-3 months from the start of the simulation, depending on the rate of administration of booster doses.