Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe, model fit for Bayesian model 2020

DOI

Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions such as closure of schools and national lock downs. We study the impact of major interventions across 11 European countries for the period from the start of COVID-19 until the 4th of May 2020 when lock downs started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. We use partial pooling of information between countries with both individual and shared effects on the reproduction number. Pooling allows more information to be used, helps overcome data idiosyncrasies, and enables more timely estimates. Our model relies on fixed estimates of some epidemiological parameters such as the infection fatality rate, does not include importation or sub-national variation and assumes that changes in the reproduction number are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that is incomplete, with systematic biases in reporting, and subject to future consolidation. We estimate that, for all the countries we consider, current interventions have been sufficient to drive the reproduction number R_t below 1 (probability R_t < 1.0 is 99.9%) and achieve epidemic control. We estimate that, across all 11 countries between 12 and 15 million individuals have been infected with SARS-CoV-2 up to 4th May, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions and lock down in particular have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.

Data comes from the European Centre for Disease Control for 11 countries. Reported daily death counts were used for the period covered by the study (February 2020-May 2020). In addition to this data, we provide the posterior draws from our statistical model giving estimates of the number of infections and the time-varying reproduction number R(t) of the disease for each of the 11 countries during the time period covered by the study.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-854380
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=bde7d11761a8881b19fa105e74baffab294d1d334c035106395dddecba52f547
Provenance
Creator Flaxman, S, Imperial College London
Publisher UK Data Service
Publication Year 2020
Funding Reference Centre funding from the UK Medical Research Council under a concordat with the UK Department for International Development; NIHR Health Protection Research Unit in Modelling Methodology; Community Jameel
Rights Seth Flaxman, Imperial College London; The Data Collection is available to any user without the requirement for registration for download/access.
OpenAccess true
Representation
Language English
Resource Type Numeric
Discipline Social Sciences
Spatial Coverage Denmark; Italy; Spain; United Kingdom; France; Norway; Belgium; Austria; Sweden; Germany; Switzerland