# Validating and Testing an Agent-Based Model for the Spread of COVID-19 in Ireland
## 4 Discussion
This method would allow for variation in the 1 agent for X number of people scaling, such that 1 agent might represent 75 teenagers with one sibling in Dublin, but 1 agent might also represent 115 people who are 80 plus and living on their own in Leitrim. This clustered scaling would allow for a better representation of behavioral patterns among agent types and their importance to the course of the pandemic. For example, the 80 plus year old agents living in Leitrim might be greatly restricting their movements and thus not contributing as much to transmission, so their representation in the model would be down-weighted compared to the teenagers in Dublin who have higher levels of interactions and a greater contribution to transmission. A new method for scaling the results of the clustered model would need to be developed along with the model so as to not introduce artefactual results. The results from our school opening experiment with the model shows how the agent-based model allows us to look at different scenarios and gain a deeper understanding of how changes in movements or interventions can impact an outbreak. With the agent-based model we can hold all other factors in the model constant and see how an increase in agent community mixing when schools reopen in the autumn impacts the number of cases. The agent-based model allows us to learn additional information about what might happen when schools open. When we do not have an increase in community mixing, we do not see a rapid increase of cases when schools open; as the model output when we do have increased community mixing does not show a large difference in cases originating within schools, this might suggest that opening schools might be relatively safe, and the resulting increase in cases around school opening might be more impacted by the actions outside of schools than within schools. This is likely because in Ireland during 2020 and 2021, schools were a controlled environment where students were required to wear masks and interact with pods of other students. Outside of school, students do not have to restrict their interactions with those within their school pod, leading to more contacts and increased chances of infection and are not required to wear masks. However, in both scenarios, we see an increase in cases in the over 65 population, which is one of the most vulnerable populations. This might suggest that in such a scenario, with schools reopening after summer holidays, it might be worthwhile to include some preventative measures to reduce cases in the older age groups. We can also compare the output of the test on school openings and background mixing to what really occurred in Ireland in September 2020. Real cases went up very gradually in the first 30 days after schools re-opened but then there was a large increase in cases by the end of October 2020. Based on our modeling results, this might suggest that there was an increase in mixing but the increase was between the two levels tested. Another possible explanation could be that initially when schools re-opened, the rest of the population continued to restrict their movements out of concern that cases would increase but when cases did not immediately increase in September, community mixing increased, leading to a rise in cases later. The results of our validation and test experiment show that the model is both validated and useful. This gives a level of confidence in the model output, showing that the model results can be used in a pandemic or outbreak situation to help understand the spread of the disease. The agent-based model is not only able to provide information on the numbers infected, but also on the location of infection and the age groups infected. This additional information may be helpful in shaping policies or implementing restrictions. There are a number of limitations of our model. No model is an exact replica of real life, and all models make assumptions. Some of the assumptions we have made should be considered when analyzing the results of the model.