# Validating and Testing an Agent-Based Model for the Spread of COVID-19 in Ireland
## 3 Results
### Testing  
The previous sections discuss the scaled agent-based model for COVID-19 spread in Ireland and the validation of the model [33]. To show how the agent-based model is useful and can be used to better understand the pandemic we run an experiment that looks at opening schools after a period of closure, such as summer break, and the impact different levels of community mixing and return to work have on case numbers. During any infectious disease outbreak it is important to understand how changes to the current mixing and movement patterns will impact the number of cases. Re-opening schools post summer holidays is an important period of time with countries wanting to safely open the schools. This reopening will likely lead to an increase in cases but the size of the increase will be dependent on the movements of the other agents in the model. It is possible that as students go back to school, adults will see this as a return to normality and increase their movements as well. To analyze the results of our model testing experiment, we first look at traditional output for infectious disease models, the number of new infectious cases per day, and then look at the output in more detail, analyzing the location where agents were infected and the age groups of the infected. Figure 6 shows the individual runs for the two scenarios and the average number of new infectious agents per day across the 30 runs in bold. In both plots the vertical lines indicate the day when schools reopen for the autumn term. Looking at both plots, it can be seen that the increase in cases when schools reopen is much greater when the reopening coincides with an increase in agent movement in the community. The increased movement also appears to lead to a greater variation in individual runs as seen in Figure 6.  
Figure 5: Plot showing the average simulated new cases per day across 30 runs in blue and the real Irish case counts in yellow. Upper and lower bounds of confidence intervals for the average simulated new cases are represented in blue dashed lines. This difference in increase in movement leads to a number of questions that the new cases per day metric cannot provide. While it is important to know that this increase in movement combined with the opening of schools leads to a greater number of cases, it might be important to understand where those cases are being infected. Are they all cases in the community? Or as community cases increase do cases that originate within the schools and home increase as well? Additionally, are certain age groups impacted more than others? These questions can help better understand the drivers of the spread of COVID-19 when schools reopen and can be better understood using the agent-based model. In the model agents keep track of if they were infected at home, school, work or in the community. Figure 7 shows the average number of infectious agents at a given time by their location of infection. When schools open but mixing does not increase, there is a slow, gradual increase in cases in schools, home and the community. There is little increase in the work setting, this is because in the model there are only a small percentage of agents who have returned to work in this scenario. An increase in agents returning to work may result in a larger increase in work cases. When school openings occur with an increase in community mixing, we still see little increase in cases at work, but the increased community mixing leads to a rapid increase in cases originating in the community and in homes. While there is a greater increase in cases originating in schools compared to when mixing does not increase, the greater levels of cases originating in schools only occur about 20 days after schools are open (the red lines for cases originating in schools only start to diverge at day 40). This suggests that there might be a delay in the impact of increased community mixing on cases in schools. There may be a threshold of cases that occur outside of schools before the higher cases spill over into the school setting.