The Efficacy of Lockdown Against COVID-19: A Cross-Country Panel Analysis

Vincenzo Alfano, Salvatore Ercolano, Vincenzo Alfano, Salvatore Ercolano

Abstract

Background: There has been much debate about the effectiveness of lockdown measures in containing COVID-19, and their appropriateness given the economic and social cost they entail. To the best of our knowledge, no existing contribution to the literature has attempted to gauge the effectiveness of lockdown measures over time in a longitudinal cross-country perspective.

Objectives: This paper aims to fill the gap in the literature by assessing, at an international level, the effect of lockdown measures (or the lack of such measures) on the numbers of new infections. Given this policy's expected change in effectiveness over time, we also measure the effect of having a lockdown implemented over a given number of days (from 7 to 20 days).

Methods: We pursue our objectives by means of a quantitative panel analysis, building a longitudinal dataset with observations from countries all over the world, and estimating the impact of lockdown via feasible generalized least squares fixed effect, random effects, generalized estimating equation, and hierarchical linear models.

Results: Our results show that lockdown is effective in reducing the number of new cases in the countries that implement it, compared with those countries that do not. This is especially true around 10 days after the implementation of the policy. Its efficacy continues to grow up to 20 days after implementation.

Conclusion: Results suggest that lockdown is effective in reducing the R0, i.e. the number of people infected by each infected person, and that, unlike what has been suggested in previous analyses, its efficacy continues to hold 20 days after the introduction of the policy.

Conflict of interest statement

Vincenzo Alfano and Salvatore Ercolano declare no conflicts of interest.

Figures

Fig. 1
Fig. 1
Betas of several lockdown dummies, computed at the date of implementation, 7 days after, 8 days after, etc., up to 20 days after. Lines and lighter colours represent the 95% and 90% confidence intervals. Betas are estimated through the FGLS-FE model. FGLS-FE feasible generalized least square–fixed effects

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Source: PubMed

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