Author: Dias, Samaherni; Queiroz, Kurios; Araujo, Aldayr
Title: Controlling Epidemic Diseases Based only on Social Distancing Level Cord-id: zv3t6gr0 Document date: 2021_6_8
ID: zv3t6gr0
Snippet: On March 11, 2020, the world health organization (WHO) characterized COVID-19 as a pandemic. When the COVID-19 outbreak began to spread, there was no vaccination and no treatment. To epidemic diseases without vaccines or other pharmaceutical intervention, the only way to control them is a sustained physical distancing. In this work, we propose a simple control law to keep the epidemic outbreak controlled. A sustained physical distancing level is adjusted to guarantee the fastest way to finish th
Document: On March 11, 2020, the world health organization (WHO) characterized COVID-19 as a pandemic. When the COVID-19 outbreak began to spread, there was no vaccination and no treatment. To epidemic diseases without vaccines or other pharmaceutical intervention, the only way to control them is a sustained physical distancing. In this work, we propose a simple control law to keep the epidemic outbreak controlled. A sustained physical distancing level is adjusted to guarantee the fastest way to finish the outbreak with the number of hospitalized individuals below the desired value. This technique can reduce the economic problems of social distancing and keeps the health care system working. The proposed controller is a closed-loop approach that uses the number of hospitalized individuals as the feedback signal. It also does not need massive swab tests, which simplify the application of the technique. We do stability analyses of the proposed controller to prove the robustness to uncertainties in the parameters and unmodeled dynamics. We present a version of the proposed controller to operate using steps to reopen, which is relevant to help the decision-makers. The proposed controller is so simple that we can use a spreadsheet to calculate the physical distancing level. In the end, we present a set of numerical simulations to highlight the behavior of the number of hospitalized individuals during an epidemic disease when using the proposed control law. We simulate the proposed controller applied to the ideal case, considering uncertainties, unmodeled dynamics, a 10 days latent period, and different values of the desired number of hospitalized individuals. In all cases, the proposed controller ensures the number of hospitalized individuals lower than the upper limit of a predefined range.
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