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This repository contains the code for the course final project of AMATH 383: Introduction to Mathematical Biology at the University of Waterloo

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Investigating and Predicting the Future Trajectory of COVID-19 in the Region of Waterloo

This repository contains the code for the course final project of AMATH 383: Introduction to Mathematical Biology at the University of Waterloo

Abstract

The COVID-19 pandemic has caused drastic chaos in the society and burdens on the global health systems in the past three years. Now with cases settling down and economy reopening, it is worth the effort to ask how the future trajectory of the disease looks like so preparations can be made beforehand. In this study, we developed an ODE based compartmental model as an attempt to investigate the future dynamic of COVID-19 in the Region of Waterloo. It was found that increasing vaccination rate can significantly help to delay and lower the major peaks of cases initially, while increasing vaccine effectiveness has no significant effect. As a result, it is hoped that public health agencies can focus on increasing vaccination coverage even with older vaccines that are less effective against the new variants so that future big resurgence of cases can be prevented.

Keywords: COVID-19; Mathematical model; Epidemiology; Vaccination

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This repository contains the code for the course final project of AMATH 383: Introduction to Mathematical Biology at the University of Waterloo

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