Abstract
Robot Dance is a computational optimization platform developed in response to the COVID-19 outbreak, to support the decision-making on public policies at a regional level. The tool is suitable for understanding and suggesting levels of intervention needed to contain the spread of infectious diseases when the mobility of inhabitants through a regional network is a concern. Such is the case for the SARS-CoV-2 virus that is highly contagious and, therefore, makes it crucial to incorporate the circulation of people in the epidemiological compartmental models. Robot Dance anticipates the spread of an epidemic in a complex regional network, helping to identify fragile links where applying differentiated measures of containment, testing, and vaccination is important. Based on stochastic optimization, the model determines efficient strategies on the basis of commuting of individuals and the situation of hospitals in each district. Uncertainty in the capacity of intensive care beds is handled by a chance-constraint approach. Some functionalities of Robot Dance are illustrated in the state of São Paulo in Brazil, using real data for a region with more than forty million inhabitants.
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