Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease

Abstract

Social distancing is a healthcare practice that helps to keep sick individuals apart from healthy individuals to reduce the risk of disease transmission. This study uses simulation to deliver a realistic representation of a real-life situation. Anyone who is unaware of the realities of a pandemic or how speedily a disease could spread will benefit through a simulation. The objectives of this study are to simulate disease spread using the GAMA platform for two situations that are with and without social distancing and to display the disease spread, graph/chart and the rate of infection within the simulation. People, primarily adults, have been observed to be negligent and perplexed by contemporary discussions, prompting them to second-guess their choices. Most people are unaware of the importance of maintaining social distance everywhere they go. GAMA Platform is used to develop and test the simulation. The simulation contains a calculation for the infection rate as well as a graph to display the changes in population. Through this simulation, the audience get a complete picture and comprehend how being protected impacts the infection rate. As a result, individuals are able to distinguish between how quickly diseases spread with and without social distancing. After testing, the results show that the average number of cycles for the people to get fully infected in a room of 500 people is approximately 28,329 cycles while it took only 8069 cycles with a room of 2500 people. To conclude, when social distancing is enabled, the rate of infection is slower.