For well over a year, the current COVID-19 pandemic has transformed the way we live, resulting in over one hundred million infections and two million deaths [1]. In a world where free thought and individual choices are encouraged, the outcome of a pandemic can either be forgiving or devastating.
To counteract the negative ramifications that contagious diseases bring to society, such as the flooding of the healthcare system with a rapid influx of infected patients, the government enforces interventions that minimises the interaction of individuals through various forms of social media. Government interventions possess the main objective of reducing the basic reproduction number of a disease and the effectiveness of certain interventions, such as social distancing, proper hand hygiene, and mandatory cotton masks, are analysed. The basic reproduction number is more likely to be greater than one when interventions are disobeyed by individuals, meaning the disease exponentially increases and self-propagates itself. The basic reproduction number is more likely to be less than one when interventions are obeyed by individuals, meaning the disease eventually dies out.
In relation to the COVID-19 pandemic, population heterogeneity refers to the idea that differences in choices made by different groups of individuals result in different outcomes [2], where these outcomes can either be forgiving or devastating. With regards to epidemiological modelling, the SIR model was relied upon in this research report as it is renowned for its ability to model the transition rates between susceptible, infectious and recovered individuals within a closed population both simplistically and concisely. Coupled with MATLAB simulations, specific quantities including the maximum number of infections, time to maximum infections, eradication time of the disease, and the total number of recovered individuals, were calculated. Through the use of MATLAB integration periods, changes in these quantities were investigated, where these changes depended on the type of intervention introduced, the time at which an intervention is introduced, and the level of compliance with interventions among the population.
[1] Worldometer (2021). Coronavirus Toll Update: Cases & Deaths by Country of Wuhan, China Virus – Worldometer.
[2] iiasa.ac.at. (n.d.). Identifying common sources of population heterogeneity – Population heterogeneity – IIASA.
Tianze Wei
University of Wollongong
