Agent models for disease propagation - Araújo, Juliano Genari de (2024)
As we experienced a major pandemic the necessity of smart interventions became very clear, but the decision for the best interventions to implement are usually based on educated guesses as each disease behaves differently and the macro behavior of the population can be very difficult to predict. Inappropriate interventions usually fail to consider heterogeneities in communities and can put the most susceptible part of the population at risk. To help in the evaluation of interventions, we developed highly modular and configurable software for stochastic agent model simulations: COMORBUSS, a software where the population is constructed in an organic way. Every person in the community is represented in the simulation and has an established routine, some actions are fixed (such as the time when that person goes and comes back from work), and some are randomly taken following probabilities to achieve a mean behavior. COMORBUSS can also be expanded in functionally with modules using some simple interface methods implemented in the main classes. With COMORBUSS and an airborne spread model for inside classrooms we tested different strategies for the return of schools after the first wave of the Covid-19 pandemic for the city of Maragogi-AL, in those simulations we arrived at the conclusion that for the safe opening of schools during a pandemic appropriate NPIs and behavioral protocols must be adopted, the vaccination of school teacher and other school staff is of paramount importance, as those workers are not only more susceptible than students, but they are also the main vectors of transmission. Uncontrolled school opening can be very dangerous as infection rates inside schools can explode leading to a significant increase in cases in the community.