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Optimal lockdowns: Analysing the efficiency of sanitary policies in Europe during the first wave

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Abstract

Uprising in China, the global COVID-19 epidemic soon started to spread out in Europe. As no medical treatment was available, it became urgent to design optimal non-pharmaceutical policies. With the help of a SIR model, we contrast two policies, one based on herd immunity (adopted by Sweden and the Netherlands), the other based on ICU capacity shortage. Both policies led to the danger of a second wave. Policy efficiency corresponds to the absence or limitation of a second wave. The aim of the paper is to measure the efficiency of these policies using statistical models and data. As a measure of efficiency, we propose the ratio of the size of two observed waves using a double sigmoid model coming from the biological growth literature. The Oxford data set provides a policy severity index together with observed number of cases and deaths. This severity index is used to illustrate the key features of national policies for ten European countries and to help for statistical inference. We estimate basic reproduction numbers, identify key moments of the epidemic and provide an instrument for comparing the two reported waves between January and October 2020. We reached the following conclusions. With a soft but long lasting policy, Sweden managed to master the first wave for cases thanks to a low R 0 , but at the cost of a large number of deaths compared to other Nordic countries and Denmark is taken as an example. We predict the failure of herd immunity policy for the Netherlands. We could not identify a clear sanitary policy for large European countries. What we observed was a lack of control for observed cases, but not for deaths.

Suggested Citation

  • Ewen Gallic & Michel Lubrano & Pierre Michel, 2021. "Optimal lockdowns: Analysing the efficiency of sanitary policies in Europe during the first wave," AMSE Working Papers 2111, Aix-Marseille School of Economics, France.
  • Handle: RePEc:aim:wpaimx:2111
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    References listed on IDEAS

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    1. Alexis Akira Toda, 2020. "Susceptible-Infected-Recovered (SIR) Dynamics of COVID-19 and Economic Impact," Papers 2003.11221, arXiv.org, revised Mar 2020.
    2. Christian M. Hafner, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," IJERPH, MDPI, vol. 17(11), pages 1-13, May.
    3. 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.
    4. Łukasz Rachel, 2020. "An Analytical Model of Covid-19 Lockdowns," Discussion Papers 2029, Centre for Macroeconomics (CFM).
    5. Stan Lipovetsky, 2010. "Double logistic curve in regression modeling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1785-1793.
    6. Sean L. Wu & Andrew N. Mertens & Yoshika S. Crider & Anna Nguyen & Nolan N. Pokpongkiat & Stephanie Djajadi & Anmol Seth & Michelle S. Hsiang & John M. Colford & Art Reingold & Benjamin F. Arnold & Al, 2020. "Substantial underestimation of SARS-CoV-2 infection in the United States," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
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    More about this item

    Keywords

    SIR models; phenomenological models; double sigmoid models; sanitary policies; herd immunity; ICU capacity constraint;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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