Optimal Testing Strategies in Long-term Care Facilities during Pandemics

Mansoor Davoodi (), Ana Batista (), Abhishek Senapati (), Weronika Schlechte-Welnicz (), Birgit Wagner () and Justin M. Calabrese ()
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Mansoor Davoodi: Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Ana Batista: Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Abhishek Senapati: Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Weronika Schlechte-Welnicz: Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Birgit Wagner: Diakonie Löbau-Zittau GmbH
Justin M. Calabrese: Helmholtz-Zentrum Dresden-Rossendorf (HZDR)

Journal of Optimization Theory and Applications, 2026, vol. 208, issue 1, No 38, 33 pages

Abstract: Abstract The COVID-19 pandemic has significantly impacted long-term care facilities, with retirement homes being particularly vulnerable due to the high mortality risk among infected elderly residents. Once an outbreak occurs, containing the virus is challenging due to frequent resident interactions and limited isolation measures. While regular testing has proven effective in preventing outbreaks, high-frequency testing can strain staff resources, creating a trade-off between testing efforts and essential care provision. This paper addresses this challenge by proposing two novel optimization models for testing schedules that minimize infection risk while balancing staff workload. Using a probabilistic approach, the models incorporate factors such as contact rates, incidence status, and infection probabilities among residents. To solve these models, we introduce an enhanced local search algorithm that leverages the symmetry property of optimal solutions. Experimental results demonstrate the effectiveness of the proposed approach, outperforming a genetic algorithm in deriving optimal testing strategies.

Keywords: Testing strategy; Scheduling; Long-term care; Retirement home; Symmetry property; COVID-19 pandemic (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/s10957-025-02843-w

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