How did governmental interventions affect the spread of COVID-19 in European countries?
Abstract
Background
To reduce transmission of Coronavirus Disease 2019, European governments have implemented successive measures to encourage social distancing. However, it remained unclear how effectively measures reduced the spread of the virus, due to data complications. We examined how the effective-contact rate (ECR) among European citizens evolved over the period with implemented measures using a new data-oriented approach that is based on an extended Susceptible-Exposed-Infectious-Removed (SEIR) model.
Methods
Using the available data on the confirmed numbers of infections and hospitalizations, we first estimated the daily number of infectious-, exposed- and susceptible individuals and subsequently estimated the ECR with an iterative Poisson regression model, disregarding information on governmental measures. We then studied change points in the daily ECRs to the moments of the governmental measures.
Findings
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).
Interpretation
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.
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