Modeling, state estimation, and optimal control for the US COVID-19 outbreak

The novel coronavirus SARS-CoV-2 and resulting COVID-19 disease have had an unprecedented spread and continue to cause an increasing number of fatalities worldwide. While vaccines are still under development, social distancing, extensive testing, and quarantining of confirmed infected subjects remai...

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Bibliographic Details
Published in:Scientific reports 2020-07, Vol.10 (1), p.10711-10711, Article 10711
Main Authors: Tsay, Calvin, Lejarza, Fernando, Stadtherr, Mark A., Baldea, Michael
Format: Article
Language:English
Subjects:
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Betacoronavirus
Computer applications
Coronavirus Infections - epidemiology
Coronavirus Infections - prevention & control
Coronavirus Infections - virology
Coronaviruses
COVID-19
Decision making
Epidemiological Monitoring
Humanities and Social Sciences
Humans
Models, Theoretical
multidisciplinary
Outbreaks
Pandemics
Pandemics - prevention & control
Pneumonia, Viral - epidemiology
Pneumonia, Viral - prevention & control
Pneumonia, Viral - virology
Quarantine - economics
Quarantine - methods
SARS-CoV-2
Science
Science (multidisciplinary)
Severe acute respiratory syndrome coronavirus 2
Social distancing
United States - epidemiology
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Summary:The novel coronavirus SARS-CoV-2 and resulting COVID-19 disease have had an unprecedented spread and continue to cause an increasing number of fatalities worldwide. While vaccines are still under development, social distancing, extensive testing, and quarantining of confirmed infected subjects remain the most effective measures to contain the pandemic. These measures carry a significant socioeconomic cost. In this work, we introduce a novel optimization-based decision-making framework for managing the COVID-19 outbreak in the US. This includes modeling the dynamics of affected populations, estimating the model parameters and hidden states from data, and an optimal control strategy for sequencing social distancing and testing events such that the number of infections is minimized. The analysis of our extensive computational efforts reveals that social distancing and quarantining are most effective when implemented early, with quarantining of confirmed infected subjects having a much higher impact. Further, we find that “on-off” policies alternating between strict social distancing and relaxing such restrictions can be effective at “flattening” the curve while likely minimizing social and economic cost.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-67459-8