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Effective Testing Policies for Controlling an Epidemic Outbreak

Muhammad Umar Niazi 1 Alain Kibangou 1 Carlos Canudas de Wit 1 Denis Nikitin 1 Liudmila Tumash 1 Pierre-Alexandre Bliman 2
1 DANCE - Dynamics and Control of Networks
Inria Grenoble - Rhône-Alpes, GIPSA-PAD - GIPSA Pôle Automatique et Diagnostic
2 MAMBA - Modelling and Analysis for Medical and Biological Applications
Inria de Paris, LJLL (UMR_7598) - Laboratoire Jacques-Louis Lions
Abstract : Testing is a crucial control mechanism for an epidemic outbreak because it enables the health authority to detect and isolate the infected cases, thereby limiting the disease transmission to susceptible people, when no effective treatment or vaccine is available. In this paper, an epidemic model that incorporates the testing rate as a control input is presented. The proposed model distinguishes between the undetected infected and the detected infected cases with the latter assumed to be isolated from the disease spreading process in the population. Two testing policies, effective during the onset of an epidemic when no treatment or vaccine is available, are devised: (i) best-effort strategy for testing (BEST) and (ii) constant optimal strategy for testing (COST). The BEST is a suppression policy that provides a lower bound on the testing rate to stop the growth of the epidemic. The COST is a mitigation policy that minimizes the peak of the epidemic by providing a constant, optimal allocation of tests in a certain time interval when the total stockpile of tests is limited. Both testing policies are evaluated by their impact on the number of active intensive care unit (ICU) cases and the cumulative number of deaths due to COVID-19 in France.
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https://hal.archives-ouvertes.fr/hal-03185142
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Submitted on : Sunday, September 26, 2021 - 12:13:17 PM
Last modification on : Friday, December 3, 2021 - 11:43:52 AM

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  • HAL Id : hal-03185142, version 2

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Muhammad Umar Niazi, Alain Kibangou, Carlos Canudas de Wit, Denis Nikitin, Liudmila Tumash, et al.. Effective Testing Policies for Controlling an Epidemic Outbreak. CDC 2021 - 60th IEEE Conference on Decision and Control, Dec 2021, Austin, United States. ⟨hal-03185142v2⟩

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