Evaluating the Effectiveness of Mitigative and Preventative Actions on Viral Spread in a Small Community Using an Agent-Based Stochastic Simulation

To discover the effects of preventative and mitigative actions on the spread of a virus in a small community, we designed and created an agent-based simulation that incorporates real-world data to simulate agents to investigate how the disease propagates. The community itself is represented as a 2D grid, in which agents move through the simulation, interacting with other agents and transmitting the disease throughout. Locations within the community such as workplaces and homes are abstracted as labelled areas within this coordinate space. The pygame and pygame_menu packages were used to design a graphical interface for the simulation that displays and controls its progress in real-time. Based on different parameters, such as base infection, masked, quarantined, social distancing maintained, the simulation has been performed and graphical user interface shows the impacts. A detail analysis has been presented these different set up to show the variations in the simulation metrics, such as susceptible, incubating, infectious, symptomatic, recovered and deceased.