An Agent-based Simulation of the SIRD model of COVID-19 Spread

The COVID-19 pandemic has resulted in more than a million deaths worldwide and wreaked havoc on world economies. SARS-CoV-2, the virus that causes COVID-19, belongs to a family of coronaviruses that have appeared in the past; however, this virus has been proven to be more lethal and have a much higher infection rate than coronaviruses that have previously emerged. Vaccines for COVID-19 are still in development phases, with limited deployment, and the most effective response to the pandemic has been to adopt social distancing and, in extreme cases, complete lockdown. This paper adopts a modified SIRD (Susceptible, Infectious, Recovered, Deaths) disease spread model for COVID-19 and utilizes agent-based simulation to obtain the number of infections in four different scenarios. The simulated scenarios utilized different contact rates in order to identify their effects on disease spread. Our results confirmed that not taking strict precautionary procedures to prohibit human interactions will lead to increased infections and deaths, adversely affecting countries’ healthcare infrastructure. The model is flexible, and other studies can use it to measure other parameters discovered in the future.