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Safety-Critical Control of Active Interventions for COVID-19 Mitigation

Ames, Aaron D. and Molnár, Tamás G. and Singletary, Andrew W. and Orosz, Gábor (2020) Safety-Critical Control of Active Interventions for COVID-19 Mitigation. IEEE Access, 8 . pp. 188454-188474. ISSN 2169-3536. PMCID PMC8545284. doi:10.1109/ACCESS.2020.3029558.

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The world has recently undergone the most ambitious mitigation effort in a century, consisting of wide-spread quarantines aimed at preventing the spread of COVID-19. The use of influential epidemiological models of COVID-19 helped to encourage decision makers to take drastic non-pharmaceutical interventions. Yet, inherent in these models are often assumptions that the active interventions are static, e.g., that social distancing is enforced until infections are minimized, which can lead to inaccurate predictions that are ever evolving as new data is assimilated. We present a methodology to dynamically guide the active intervention by shifting the focus from viewing epidemiological models as systems that evolve in autonomous fashion to control systems with an “input” that can be varied in time in order to change the evolution of the system. We show that a safety-critical control approach to COVID-19 mitigation gives active intervention policies that formally guarantee the safe evolution of compartmental epidemiological models. This perspective is applied to current US data on cases while taking into account reduction of mobility, and we find that it accurately describes the current trends when time delays associated with incubation and testing are incorporated. Optimal active intervention policies are synthesized to determine future mitigations necessary to bound infections, hospitalizations, and death, both at national and state levels. We therefore provide means in which to model and modulate active interventions with a view toward the phased reopenings that are currently beginning across the US and the world in a decentralized fashion. This framework can be converted into public policies, accounting for the fractured landscape of COVID-19 mitigation in a safety-critical fashion.

Item Type:Article
Related URLs:
URLURL TypeDescription CentralArticle Paper Paper
Ames, Aaron D.0000-0003-0848-3177
Molnár, Tamás G.0000-0002-9379-7121
Singletary, Andrew W.0000-0001-6635-4256
Orosz, Gábor0000-0002-9000-3736
Alternate Title:Safety-Critical Control of Compartmental Epidemiological Models with Measurement Delays
Additional Information:© 2020 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. This work was supported in part by the National Science Foundation, Cyber-Physical Systems (CPS) Award 1932091. The authors would like to thank Franca Hoffmann for her insights into compartmental epidemiological models and Gábor Stépán for discussions regarding non-pharmaceutical interventions in Europe.
Funding AgencyGrant Number
Subject Keywords:Safety-Critical Control, Epidemiology, Non-Pharmaceutical Intervention, COVID-19
PubMed Central ID:PMC8545284
Record Number:CaltechAUTHORS:20200706-130358309
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Official Citation:A. D. Ames, T. G. Molnár, A. W. Singletary and G. Orosz, "Safety-Critical Control of Active Interventions for COVID-19 Mitigation," in IEEE Access, vol. 8, pp. 188454-188474, 2020, doi: 10.1109/ACCESS.2020.3029558
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104225
Deposited By: Tony Diaz
Deposited On:06 Jul 2020 20:50
Last Modified:01 Jun 2023 23:29

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