A multi-agent approach to simulate contamination with the new Coronavirus

Resumo

We are currently experiencing a severe Coronavirus pandemic. Understanding the movement of crowds is of
vital importance for planning and decision making, not only to define strategies for loosening or tightening the quarantine,
but also for the allocation of health professionals or funds to more impacted locations, the definition of new needs and the
necessity of hospital beds for each city, among others. As we have witnessed, modeling and empirical studies of crowd
behavior are critical to supporting governments and health agencies. To try to provide quality information, a mathematical
model was developed where a multi-agent system simulates the movement of people and the risk of contamination
according to some situations. In this work, we are simulating scenarios where there is loosening of the quarantine and more
people on the street, situations where there is stricter social isolation and the risk of contamination for these scenarios. A
system was developed where the interface shows the movement of people and the moment of contagion. The preliminary
results show the great difference in the time of contamination of the population in each scenario and the moment when the
health system is overloaded, that is, there are no more beds for the admission of new patients. The objective of this work is
to add to the studies already in progress, with more data and information that can help to improve the policies and actions
to combat the pandemic.