This expert summary is for the peer-reviewed article linked above. We also summarized this paper before it underwent peer-review. You can find the original review of the preprint by clicking here.
Study population and setting
A semi-mechanistic Bayesian hierarchical model was fit to observed COVID-19 deaths in 11 European countries, and was used to estimate the number of cases and the reproduction number (Rt) of the infection. The model used partially pooled data across countries, along with the timing of country-specific non-pharmaceutical interventions, to estimate the impact of these interventions on Rt (with particular attention to whether Rt has been driven below 1) and on the number of infections and deaths in these countries up to May 4, 2020.
Summary of Main Findings
The reproduction number of the virus is estimated to have been reduced from 3.8 (95% credible interval: 2.4 to 5.6) to below 1 in all countries. Many times more people are estimated to have been infected by SARS-CoV-2 than have been confirmed: across all 11 countries, estimated cases totaled 12 to 15 million for an overall attack rate of 3.2% to 4.0%. Estimates of country-specific attack rates ranged from 0.46% (0.34% to 0.61%) in Norway to 8.0% (6.1% to 11.0%) in Belgium. 3.1 million deaths (2.8 million to 3.5 million) are estimated to have been averted by all non-pharmaceutical interventions by May 4. Of the categories of intervention, only lockdown had an identifiable impact.
The model is fit to observed deaths, which are likely to be more reliable than case counts or hospitalizations. Estimates of case counts are supported by evidence from serologic surveys. The model reproduces observed data up to May 4th, 2020 very well. Uncertainty from various sources is appropriately handled by the model explicitly and by the discussion implicitly. Prior distributions and parameter values are chosen based on current, best available data.
The model did not allow for other factors, such as changes in individual risk-avoiding behavior, to affect Rt. The infection fatality ratio, which is key to estimation of the number of infections, is treated as a fixed value by the model; there remains considerable uncertainty about the true value of this parameter. The timing of country-specific interventions makes it difficult to distinguish between the effects of specific interventions. Interventions are assumed to have the same impact across countries and time. Effect estimates in the model are heavily influenced by countries with a high number of deaths that implemented interventions earlier.
This study is the most thorough model-based estimate of the impact of European country-wide non-pharmaceutical interventions so far.