Can the COVID-19 Epidemic Be Controlled on the Basis of Daily Test Reports?
Francesco Casella
- Vol. 5, Iss: 3, pp 1079-1084
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TLDR
The analysis shows that suppression strategies can be effective if strong enough and enacted early on and how mitigation strategies can fail because of the combination of delay, unstable dynamics, and uncertainty in the feedback loop.Abstract:
This letter studies if and to which extent COVID-19 epidemics can be controlled by authorities taking decisions on public health measures on the basis of daily reports of swab test results, active cases and total cases. A suitably simplified process model is derived to support the controllability analysis, highlighting the presence of very significant time delay; the model is validated with data from several outbreaks. The analysis shows that suppression strategies can be effective if strong enough and enacted early on. It also shows how mitigation strategies can fail because of the combination of delay, unstable dynamics, and uncertainty in the feedback loop; approximate conditions based on the theory of limitation of linear control are given for feedback control to be feasible.read more
Citations
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A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic
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TL;DR: This work confirms the effectiveness at the regional level of the national lockdown strategy and proposes coordinated regional interventions to prevent future national lockdowns, while avoiding saturation of the regional health systems and mitigating impact on costs.
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Robust and optimal predictive control of the COVID-19 outbreak.
TL;DR: In this article, the authors investigate adaptive strategies to robustly and optimally control the COVID-19 pandemic via social distancing measures based on the example of Germany and propose a robust MPC-based feedback policy using interval arithmetic.
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Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario.
TL;DR: An optimal control approach is proposed that supports governments in defining the most effective strategies to be adopted during post-lockdown mitigation phases in a multi-region scenario and supports policy makers in taking targeted intervention decisions on different regions by an integrated and structured model.
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Robust and optimal predictive control of the COVID-19 outbreak
TL;DR: The theoretical findings support various recent studies by showing that adaptive feedback strategies are required to reliably contain the COVID-19 outbreak, and well-designed policies can significantly reduce the number of fatalities compared to simpler policies while keeping the amount of social distancing measures on the same level.
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Post-lockdown abatement of COVID-19 by fast periodic switching.
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TL;DR: In this paper, the authors show that periodic, high-frequency alternation of into, and out-of, lockdown effectively mitigates second-wave effects, while allowing continued, albeit reduced, economic activity.
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Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
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