IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v303y2022i3p1372-1391.html
   My bibliography  Save this article

Designing an optimal sequence of non‐pharmaceutical interventions for controlling COVID-19

Author

Listed:
  • Biswas, Debajyoti
  • Alfandari, Laurent

Abstract

The COVID-19 pandemic has had an unprecedented impact on global health and the economy since its inception in December, 2019 in Wuhan, China. Non-pharmaceutical interventions (NPI) like lockdowns and curfews have been deployed by affected countries for controlling the spread of infections. In this paper, we develop a Mixed Integer Non-Linear Programming (MINLP) epidemic model for computing the optimal sequence of NPIs over a planning horizon, considering shortages in doctors and hospital beds, under three different lockdown scenarios. We analyse two strategies - centralised (homogeneous decisions at the national level) and decentralised (decisions differentiated across regions), for two objectives separately - minimization of infections and deaths, using actual pandemic data of France. We linearize the quadratic constraints and objective functions in the MINLP model and convert it to a Mixed Integer Linear Programming (MILP) model. A major result that we show analytically is that under the epidemic model used, the optimal sequence of NPIs always follows a decreasing severity pattern. Using this property, we further simplify the MILP model into an Integer Linear Programming (ILP) model, reducing computational time up to 99%. Our numerical results show that a decentralised strategy is more effective in controlling infections for a given severity budget, yielding up to 20% lesser infections, 15% lesser deaths and 60% lesser shortages in healthcare resources. These results hold without considering logistics aspects and for a given level of compliance of the population.

Suggested Citation

  • Biswas, Debajyoti & Alfandari, Laurent, 2022. "Designing an optimal sequence of non‐pharmaceutical interventions for controlling COVID-19," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1372-1391.
    • Handle: RePEc:eee:ejores:v:303:y:2022:i:3:p:1372-1391
    DOI: 10.1016/j.ejor.2022.03.052
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722002752
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2022.03.052?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Haiyan Wang & Xinping Wang & Amy Z. Zeng, 2009. "Optimal material distribution decisions based on epidemic diffusion rule and stochastic latent period for emergency rescue," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 1(1/2), pages 76-96.
    2. Reza Yaesoubi & Ted Cohen, 2011. "Dynamic Health Policies for Controlling the Spread of Emerging Infections: Influenza as an Example," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-11, September.
    3. Fernando Alvarez & David Argente, 2020. "A Simple Planning Problem for COVID-19 Lockdown," Working Papers 2020-34, Becker Friedman Institute for Research In Economics.
    4. Martin S Eichenbaum & Sergio Rebelo & Mathias Trabandt, 2021. "The Macroeconomics of Epidemics [Economic activity and the spread of viral diseases: Evidence from high frequency data]," Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    5. Daron Acemoglu & Victor Chernozhukov & Iván Werning & Michael D. Whinston, 2021. "Optimal Targeted Lockdowns in a Multigroup SIR Model," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 487-502, December.
    6. Fred Glover, 1975. "Improved Linear Integer Programming Formulations of Nonlinear Integer Problems," Management Science, INFORMS, vol. 22(4), pages 455-460, December.
    7. David L. Craft & Lawrence M. Wein & Alexander H. Wilkins, 2005. "Analyzing Bioterror Response Logistics: The Case of Anthrax," Management Science, INFORMS, vol. 51(5), pages 679-694, May.
    8. Charles Reveller & Walter Lynn & Floyd Feldmann, 1969. "An Optimization Model of Tuberculosis Epidemiology," Management Science, INFORMS, vol. 16(4), pages 190-211, December.
    9. Alessio Andronico & Cécile Tran Kiem & Juliette Paireau & Tiphanie Succo & Paolo Bosetti & Noémie Lefrancq & Mathieu Nacher & Félix Djossou & Alice Sanna & Claude Flamand & Henrik Salje & Cyril Rousse, 2021. "Evaluating the impact of curfews and other measures on SARS-CoV-2 transmission in French Guiana," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    10. Alain, Guinet & Angel, Ruiz, 2016. "Modeling the logistics response to a bioterrorist anthrax attackAuthor-Name: Wanying, Chen," European Journal of Operational Research, Elsevier, vol. 254(2), pages 458-471.
    11. Ming Liu & Ding Zhang, 2016. "A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(6), pages 841-852, June.
    12. Azrah Anparasan & Miguel Lejeune, 2019. "Resource deployment and donation allocation for epidemic outbreaks," Annals of Operations Research, Springer, vol. 283(1), pages 9-32, December.
    13. Loayza,Norman V. & Pennings,Steven Michael, 2020. "Macroeconomic Policy in the Time of COVID-19 : A Primer for Developing Countries," Research and Policy Briefs 147291, The World Bank.
    14. Joshua Bernstein & Alexander W. Richter & Nathaniel A. Throckmorton, 2020. "COVID-19: A View from the Labor Market," Working Papers 2010, Federal Reserve Bank of Dallas.
    15. Nina Haug & Lukas Geyrhofer & Alessandro Londei & Elma Dervic & Amélie Desvars-Larrive & Vittorio Loreto & Beate Pinior & Stefan Thurner & Peter Klimek, 2020. "Ranking the effectiveness of worldwide COVID-19 government interventions," Nature Human Behaviour, Nature, vol. 4(12), pages 1303-1312, December.
    16. He, Yuxuan & Liu, Nan, 2015. "Methodology of emergency medical logistics for public health emergencies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 178-200.
    17. Loayza,Norman V., 2020. "Costs and Trade-Offs in the Fight Against the COVID-19 Pandemic : A Developing Country Perspective," Research and Policy Briefs 148535, The World Bank.
    18. Caulkins, Jonathan P. & Grass, Dieter & Feichtinger, Gustav & Hartl, Richard F. & Kort, Peter M. & Prskawetz, Alexia & Seidl, Andrea & Wrzaczek, Stefan, 2021. "The optimal lockdown intensity for COVID-19," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    19. Ming Liu & Peiyong Zhang, 2013. "Three-Level and Dynamic Optimization Model for Allocating Medical Resources Based on Epidemic Diffusion Model," Springer Books, in: Zhenji Zhang & Runtong Zhang & Juliang Zhang (ed.), Liss 2012, edition 127, pages 241-246, Springer.
    20. Ali Ekici & Pınar Keskinocak & Julie L. Swann, 2014. "Modeling Influenza Pandemic and Planning Food Distribution," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 11-27, February.
    21. Ming Liu & Xifen Xu & Jie Cao & Ding Zhang, 2020. "Integrated planning for public health emergencies: A modified model for controlling H1N1 pandemic," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(5), pages 748-761, May.
    22. Adam Brzezinski & David Van Dijcke & Valentin Kecht, 2020. "The Cost of Staying Open: Voluntary Social Distancing and Lockdowns in the US," Economics Series Working Papers 910, University of Oxford, Department of Economics.
    23. Xuecheng Yin & İ. E. Büyüktahtakın, 2021. "A multi-stage stochastic programming approach to epidemic resource allocation with equity considerations," Health Care Management Science, Springer, vol. 24(3), pages 597-622, September.
    24. 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.
    25. Norman V. Loayza, 2020. "Costs and Trade-Offs in the Fight Against the COVID-19 Pandemic," World Bank Publications - Reports 33764, The World Bank Group.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mario Coccia, 2023. "COVID-19 Vaccination is not a Sufficient Public Policy to face Crisis Management of next Pandemic Threats," Public Organization Review, Springer, vol. 23(4), pages 1353-1367, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Linus Nyiwul, 2021. "Epidemic Control and Resource Allocation: Approaches and Implications for the Management of COVID-19," Studies in Microeconomics, , vol. 9(2), pages 283-305, December.
    2. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    3. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2023. "Design of control strategies to help prevent the spread of COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 219-238.
    4. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    5. Xiaoyan Xu & Suresh P. Sethi & Sai‐Ho Chung & Tsan‐Ming Choi, 2023. "Reforming global supply chain management under pandemics: The GREAT‐3Rs framework," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 524-546, February.
    6. Pan, Yuqing & Cheng, T.C.E. & He, Yuxuan & Ng, Chi To & Sethi, Suresh P., 2022. "Foresighted medical resources allocation during an epidemic outbreak," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    7. Emanuele Colombo Azimonti & Luca Portoghese & Patrizio Tirelli, 2022. "Covid-19 supply-side fiscal policies to escape the health-vs-economy dilemma," DEM Working Papers Series 208, University of Pavia, Department of Economics and Management.
    8. Gustavo Leyva & Carlos Urrutia, 2023. "Informal Labor Markets in Times of Pandemic," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 47, pages 158-185, January.
    9. Janssen, Aljoscha & Shapiro, Matthew, 2020. "Does Precise Case Information Limit Precautionary Behavior? Evidence from COVID-19 in Singapore," Working Paper Series 1344, Research Institute of Industrial Economics.
    10. Pragyan Deb & Davide Furceri & Jonathan D. Ostry & Nour Tawk, 2022. "The Economic Effects of COVID-19 Containment Measures," Open Economies Review, Springer, vol. 33(1), pages 1-32, February.
    11. Aspri, Andrea & Beretta, Elena & Gandolfi, Alberto & Wasmer, Etienne, 2021. "Mortality containment vs. Economics Opening: Optimal policies in a SEIARD model," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    12. Hausmann, Ricardo & Schetter, Ulrich, 2022. "Horrible trade-offs in a pandemic: Poverty, fiscal space, policy, and welfare," World Development, Elsevier, vol. 153(C).
    13. Janssen, Aljoscha & Shapiro, Matthew H., 2021. "Does precise case disclosure limit precautionary behavior? Evidence from COVID-19 in Singapore," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 700-714.
    14. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    15. Gutierrez, Emilio & Rubli, Adrian & Tavares, Tiago, 2022. "Information and behavioral responses during a pandemic: Evidence from delays in Covid-19 death reports," Journal of Development Economics, Elsevier, vol. 154(C).
    16. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    17. Leyva Gustavo & Urrutia Carlos, 2021. "Informal Labor Markets in Times of Pandemic: Evidence for Latin America and Policy Options," Working Papers 2021-21, Banco de México.
    18. Gopal K. Basak & Chandramauli Chakraborty & Pranab Kumar Das, 2021. "Optimal Lockdown Strategy in a Pandemic: An Exploratory Analysis for Covid-19," Papers 2109.02512, arXiv.org.
    19. Hakan Yilmazkuday, 2021. "Welfare costs of COVID‐19: Evidence from US counties," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 826-848, September.
    20. Zhen Zhu & Enzo Weber & Till Strohsal & Duaa Serhan, 2020. "Sustainable Border Control Policy in the COVID-19 Pandemic: A Math Modeling Study," Papers 2008.13561, arXiv.org, revised Feb 2021.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:303:y:2022:i:3:p:1372-1391. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.