| Sumario: |
During the COVID-19 pandemic, many countries opted for strict public health measures,
including closing schools. After some time, they have started relaxing some of those restrictions.
To avoid overwhelming health systems, predictions for the number of new COVID-19
cases need to be considered when choosing a school reopening strategy. Using a computer simulation
based on a stochastic compartmental model that includes a heterogeneous and dynamic
network, we analyze different strategies to reopen schools in the São Paulo Metropolitan Area,
including one similar to the official reopening plan. Our model allows us to describe different
types of relations between people, each type with a different infectiousness. Based on our simulations
and model assumptions, our results indicate that reopening schools with all students at
once has a big impact on the number of new COVID-19 cases, which could cause a collapse of
the health system. On the other hand, our results also show that a controlled school reopening
could possibly avoid the collapse of the health system, depending on how people follow sanitary
measures. We estimate that postponing the schools’ return date for after a vaccine becomes
available may save tens of thousands of lives just in the São Paulo Metropolitan Area compared
to a controlled reopening considering a worst case scenario. We also discuss our model
constraints and the uncertainty of its parameters.
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