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Publication . Conference object . Preprint . Article . 2021 . Embargo end date: 01 Jan 2021

Effective Testing Policies for Controlling an Epidemic Outbreak

Muhammad Umar B Niazi; Kibangou A; Canudas-de-Wit C; Nikitin D; Tumash L; Bliman P;
Open Access
Published: 13 Dec 2021
Publisher: arXiv
Country: France
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.

Comment: arXiv admin note: substantial text overlap with arXiv:2010.15438

Subjects

Optimization and Control (math.OC), Systems and Control (eess.SY), FOS: Mathematics, FOS: Electrical engineering, electronic engineering, information engineering, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], [INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY], [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Mathematics - Optimization and Control, Electrical Engineering and Systems Science - Systems and Control

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Funded by
EC| Scale-FreeBack
Project
Scale-FreeBack
Scale-Free Control for Complex Physical Network Systems
  • Funder: European Commission (EC)
  • Project Code: 694209
  • Funding stream: H2020 | ERC | ERC-ADG
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