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Optimising the assignment of swabs and reagent for PCR testing during a viral epidemic

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  • Santini, Alberto

Abstract

Early large-scale swab testing is a fundamental tool for health authorities to assess the prevalence of a virus and enact appropriate mitigation measures during an epidemic. The COVID-19 pandemic has shown that the availability of chemical reagent required to carry out the tests is often a bottleneck in increasing a country’s testing capacity. Further, demand is unevenly spread between more affected regions (which require more tests they can perform) and less affected ones (which have spare capacity). These issues hint at the opportunity of increasing test capacity via the optimal allocation of swabs and reagent to laboratories. We prove that this is the case, proposing an Integer Programming formulation to maximise the number of tests a country can perform and validating our approach on both real-life data from Italy and synthetic instances. Our results show that increased inter-regional collaboration and a steadier supply of reagent (i.e., coming from local production sites rather than international shipments) can dramatically increase testing capacity. Accordingly, we propose short-term and long-term recommendations for policy makers and health authorities.

Suggested Citation

  • Santini, Alberto, 2021. "Optimising the assignment of swabs and reagent for PCR testing during a viral epidemic," Omega, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:jomega:v:102:y:2021:i:c:s0305048320306952
    DOI: 10.1016/j.omega.2020.102341
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    1. Neriman Beste Kaygisiz & Yashna Shivdasani & Rena M. Conti & Ernst R. Berndt, 2019. "The Geography of Prescription Pharmaceuticals Supplied to the U.S.: Levels, Trends and Implications," NBER Working Papers 26524, National Bureau of Economic Research, Inc.
    2. Yisha Xiang & Jun Zhuang, 2016. "A medical resource allocation model for serving emergency victims with deteriorating health conditions," Annals of Operations Research, Springer, vol. 236(1), pages 177-196, January.
    3. Hui Cao & Simin Huang, 2012. "Principles of Scarce Medical Resource Allocation in Natural Disaster Relief," Medical Decision Making, , vol. 32(3), pages 470-476, May.
    4. George France & Francesco Taroni & Andrea Donatini, 2005. "The Italian health‐care system," Health Economics, John Wiley & Sons, Ltd., vol. 14(S1), pages 187-202, September.
    5. Adam Fleischhacker & Anh Ninh & Yao Zhao, 2015. "Positioning Inventory in Clinical Trial Supply Chains," Production and Operations Management, Production and Operations Management Society, vol. 24(6), pages 991-1011, June.
    6. Sanjay Mehrotra & Hamed Rahimian & Masoud Barah & Fengqiao Luo & Karolina Schantz, 2020. "A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(5), pages 303-320, August.
    7. Aleksander Banasik & Argyris Kanellopoulos & G. D. H. Claassen & Jacqueline M. Bloemhof-Ruwaard & Jack G. A. J. Vorst, 2017. "Assessing alternative production options for eco-efficient food supply chains using multi-objective optimization," Annals of Operations Research, Springer, vol. 250(2), pages 341-362, March.
    8. Mirzapour Al-e-hashem, S.M.J. & Malekly, H. & Aryanezhad, M.B., 2011. "A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty," International Journal of Production Economics, Elsevier, vol. 134(1), pages 28-42, November.
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    Cited by:

    1. Colajanni, Gabriella & Daniele, Patrizia & Sciacca, Daniele, 2022. "Reagents and swab tests during the COVID-19 Pandemic: An optimized supply chain management with UAVs," Operations Research Perspectives, Elsevier, vol. 9(C).
    2. Gilani, Hani & Sahebi, Hadi, 2022. "A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain," Omega, Elsevier, vol. 110(C).

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