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

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  • 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
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    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]," The 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.
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