The Agent-based modeling (ABM) is based on a set of autonomous agents who make decisions based on a series of rules we set [5]. Each agent-based model can simulate a real-world situation, which provides essential information. In this article, we are creating six public places with higher risks of interactions between people, including school, church, office, bus, café, and sub. In the program, the number of susceptible individuals in the initial population is 1,000 people compared to the approximately 5,000 who are living on campus. The ratio of parameters and the real population is 1:5. We set the two parameters, β and γ, constant which β equals to 0.602 and γ equals to 0.527. Three scenarios are created based on varying restrictions. The baseline scheme means that all restrictions will be enforced. The second scenario depends on the Phase 2 Reopening Rules, which were 50% of its regular indoor capacity. The third scenario follows the Phase 3 Reopen Rules by Sector in Connecticut, which has a maximum 50% capacity of religious gatherings, and 75% indoor capacity of restaurants [6].
3. Results
Figure 1 shows the number of cases changing from August 16 to September 7, with a total of 25,817 population in Mansfield. We also transform the y-axis scale to a log scale with base 10 to make the graph look better in Figure 2. Based on the data we collected, Figure 3 predicts S, I, and R changes in the next 30 days, from September 8 to October 7. However, this figure is not practical to see the changes because the susceptible and recovered lines are at the bottom. To improve it, we transform the y-axis to a log scale and get a more straightforward plot in Figure 4. We can see the red line, which is infectious, increases until September 23 and starts decreasing. The green line represents infectious, which is increasing at a relatively fast rate. Thus, in the long run, the infectious cases will decrease, and susceptible individuals are increasing at a slower rate. R0 = 1.1441 estimates the initial reproduction number, and β = 0.6024 and γ = 0.6265 estimate the infected rate and recovery rate.