How did governmental interventions affect the spread of COVID-19 in European countries?

Abstract

Background To reduce the transmission of the severe acute respiratory syndrome coronavirus 2 in its first wave, European governments have implemented successive measures to encourage social distancing. However, it remained unclear how effectively measures reduced the spread of the virus. We examined how the effective-contact rate (ECR), the mean number of daily contacts for an infectious individual to transmit the virus, among European citizens evolved during this wave over the period with implemented measures, disregarding a priori information on governmental measures. Methods We developed a data-oriented approach that is based on an extended Susceptible-Exposed-Infectious-Removed (SEIR) model. Using the available data on the confirmed numbers of infections and hospitalizations, we first estimated the daily total number of infectious-, exposed- and susceptible individuals and subsequently estimated the ECR with an iterative Poisson regression model. We then compared change points in the daily ECRs to the moments of the governmental measures. Results The change points in the daily ECRs were found to align with the implementation of governmental interventions. At the end of the considered time-window, we found similar ECRs for Italy (0.29), Spain (0.24), and Germany (0.27), while the ECR in the Netherlands (0.34), Belgium (0.35) and the UK (0.37) were somewhat higher. The highest ECR was found for Sweden (0.45). Conclusions There seemed to be an immediate effect of banning events and closing schools, typically among the first measures taken by the governments. The effect of additionally closing bars and restaurants seemed limited. For most countries a somewhat delayed effect of the full lockdown was observed, and the ECR after a full lockdown was not necessarily lower than an ECR after (only) a gathering ban.

Sustained Effects of Government Response on the COVID-19 Infection Rate in China: A Multiple Mediation Analysis

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Systematic review of empirical studies comparing the effectiveness of non-pharmaceutical interventions against COVID-19

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A model based on cellular automata for investigating the impact of lockdown, migration and vaccination on COVID-19 dynamics

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“…Stringent implementation of healthcare advisories from WHO, strategies such as national lockdowns [2] , [3] and effective interventions by Governments in testing, isolating and treating the infected aided to control the spread of the virus in its first wave [4] , [5] , [6] . Nevertheless, the viral pandemic affected human life and the global economy in an adverse manner [7] .…”