A Review of COVID-19 Mathematical Models and an Implementation of Vaccination Policies

Abstract

Cellular automata (CA) models have been used to simulate the behaviour of infectious diseases and can offer valuable information concerning the spread of infection and population susceptibility to sickness. Furthermore, CA models can be used to evaluate various response strategies, such as herd immunization and vaccination. By assessing CA approaches for COVID-19, we identified a lack of an age-based symptom severity score and death probability (1-3). We used a Susceptible Infected Removed (SIR) model and distribution of population age groups from the Canadian government to determine the effect of vaccinating older (60+ years old) versus a younger population (30-59 years old). Our findings show a significant decrease in the total number of deaths and peak number of infections when the older population was vaccinated. This is a result of the higher probabilities of death and severe symptoms in older age groups. While this simulation is based on a small scale, the findings provide evidence to prioritize vaccination of the elderly.