Modelling COVID-19 is a new and important area of research as COVID-19 was first reported in December, 2019 in Wuhan, China [15]. There are many factors to consider when developing a model including: intervention strategies implemented, how many people are initially infected, the mixing patterns of people, the population size etc. The classic SEIR model is very common, with many existing COVID-19 models being adaptations or extensions of this model.
The importance of the classic SEIR model is highlighted in the literature review. Initially, COVID-19 is considered in a small hypothetical town with fifteen infected people being introduced at t=0. Here the classic SEIR model is implemented in MATLAB and different scenarios are considered including: without intervention, household lockdown, social distancing and individual quarantine. A quarantine model is formulated and compared to the classic SEIR model.
Furthermore, the stress of COVID-19 on the hospital intensive care units (ICU) is considered with simulations run using equations derived from the paper: "Modelling the impact of COVID-19 upon intensive care services in New South Wales" [8]. A sensitivity analysis is implemented to determine which parameters of this model influence the time at which ICU beds reach capacity the most.
An Indian Lockdown model [20] is studied which splits infectious individuals into 2 compartments: Asymptomatic and Symptomatic. MATLAB simulations are run to compare the dynamics of COVID-19 for without lockdown and with lockdown models. The Indian model can be applied to the NSW ICU model by introducing counter measures against COVID-19 and by splitting the hospitalised infectious class into asymptomatic and symptomatic compartments.
Lastly, a literature review section documents key ideas from papers which are related to COVID-19 modelling.