Optimal Adaptive Testing for Epidemic Control: Combining Molecular and Serology Tests

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ABSTRACT: This research studies optimal lockdown and testing policies for the containment of disease spread in networked environments. Our motivation comes from three peculiar aspects of the COVID-19 pandemic. First, since a vaccine is not yet available, one needs to rely on virus containment strategies (such as lockdowns) as intervention tools, which have serious economic repercussions. Our first objective is to develop lockdown models that consider epidemic and economic aspects simultaneously. Since individuals in the population may have different risks and different productivity levels, this requires models that explicitly account for the heterogeneity of different groups and their network of interactions. Our second objective is to exploit these network models to study targeted interventions. In particular we aim at understanding what is the best policy to gradually reopen the economy by taking into account the role of the different groups in terms of their productivity and their risk level. Finally, since COVID-19 is a pandemic, it is important to note that interventions actuated by local governments will have ripple effects on neighboring states, hence coordination of efforts from different governments is of paramount importance. As the third objective, we aim at studying how state interconnections and mobility patterns affect the optimal response to an epidemic in networked environments. Results from the proposed research will help leaders and decision makers in understanding how to optimally unlock the economy within a state and how to optimally coordinate efforts between states.

SPEAKER: Francesca Parise joined the School of Electrical and Computer Engineering at Cornell University as an assistant professor in July 2020. Before then, she was a postdoctoral researcher at the Laboratory for Information and Decision Systems at MIT. She defended her PhD at the Automatic Control Laboratory, ETH Zurich, Switzerland in 2016 and she received the B.Sc. and M.Sc. degrees in Information and Automation Engineering in 2010 and 2012, from the University of Padova, Italy, where she simultaneously attended the Galilean School of Excellence. Francesca was recognized as an EECS rising star in 2017 and is the recipient of the Guglielmo Marin Award from the “Istituto Veneto di Scienze, Lettere ed Arti,” the SNSF Early Postdoc Fellowship, the SNSF Advanced Postdoc Fellowship, and the ETH Medal for her doctoral work.
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