Modeling COVID-19 Transmission using IDSIM, an Epidemiological-Modelling Desktop App with Multi-Level Immunization Capabilities
Eleodor Nichita, Mary-Anne Pietrusiak, Fangli Xie, Peter Schwanke and, Anjali Pandya

TL;DR
This paper introduces IDSIM, a desktop epidemiological modeling app for COVID-19 that simulates transmission dynamics considering variants, vaccination, and public health measures, aiding local health decision-making.
Contribution
The paper presents a novel multi-stratified compartmental model implemented in a user-friendly desktop app for COVID-19 transmission simulation.
Findings
Vaccination and natural immunity are crucial for herd immunity.
Waning immunity extends the time to herd immunity.
Omicron wave could peak in 2-3 months without additional measures.
Abstract
The 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. To address this need, Ontario Tech University and the Durham Region Health Department developed a native Windows desktop app that performs epidemiological modelling of infectious diseases. The 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. This article presents the epidemiological model and epidemiological-simulation results obtained using the developed app. The simulations investigate the effects of different factors on COVID-19 transmission in Durham Region,…
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Taxonomy
TopicsCOVID-19 epidemiological studies · COVID-19 Digital Contact Tracing · SARS-CoV-2 and COVID-19 Research
