This study examines the effectiveness of non-pharmaceutical interventions (NPIs) in controlling the spread of COVID-19 across 11 European countries from February 2020 to May 4, 2020. The authors use a Bayesian mechanistic model to estimate the reproduction number ($R_i$) and the number of infections, deaths, and averted deaths due to interventions. Key findings include: 1. **Estimation of Infections and $R_i$**: The model estimates that the number of infections was significantly higher than reported, with an attack rate of about 3.2% to 4.0% of the population across all countries. The initial $R_i$ was estimated to be around 3.8, but interventions have reduced it to below 1 in all countries, indicating control of the epidemic. 2. **Effectiveness of Interventions**: The model shows that major NPIs, particularly lockdowns, have had a substantial effect on reducing transmission. Lockdowns are estimated to have reduced $R_i$ by 81%, while other interventions had less identifiable effects due to their timing. 3. **Averted Deaths**: The study estimates that interventions have averted between 3.1 million and 3.5 million deaths across the 11 countries, highlighting the significant impact of these measures. 4. **Model Validation and Limitations**: The model is validated through cross-validation and sensitivity analyses, showing robustness to various assumptions. However, limitations include the reliance on mortality data, which may be underreported or biased, and the inability to capture fine-scale variations in intervention effects. 5. **Conclusion**: The study concludes that current interventions have been effective in controlling the epidemic, but continued intervention is necessary to maintain control. The findings are consistent with other studies from individual countries, providing confidence in the effectiveness of NPIs. Overall, the study provides a comprehensive analysis of the impact of NPIs on the spread of COVID-19 in Europe, emphasizing the importance of continued and appropriate interventions to manage the ongoing pandemic.This study examines the effectiveness of non-pharmaceutical interventions (NPIs) in controlling the spread of COVID-19 across 11 European countries from February 2020 to May 4, 2020. The authors use a Bayesian mechanistic model to estimate the reproduction number ($R_i$) and the number of infections, deaths, and averted deaths due to interventions. Key findings include: 1. **Estimation of Infections and $R_i$**: The model estimates that the number of infections was significantly higher than reported, with an attack rate of about 3.2% to 4.0% of the population across all countries. The initial $R_i$ was estimated to be around 3.8, but interventions have reduced it to below 1 in all countries, indicating control of the epidemic. 2. **Effectiveness of Interventions**: The model shows that major NPIs, particularly lockdowns, have had a substantial effect on reducing transmission. Lockdowns are estimated to have reduced $R_i$ by 81%, while other interventions had less identifiable effects due to their timing. 3. **Averted Deaths**: The study estimates that interventions have averted between 3.1 million and 3.5 million deaths across the 11 countries, highlighting the significant impact of these measures. 4. **Model Validation and Limitations**: The model is validated through cross-validation and sensitivity analyses, showing robustness to various assumptions. However, limitations include the reliance on mortality data, which may be underreported or biased, and the inability to capture fine-scale variations in intervention effects. 5. **Conclusion**: The study concludes that current interventions have been effective in controlling the epidemic, but continued intervention is necessary to maintain control. The findings are consistent with other studies from individual countries, providing confidence in the effectiveness of NPIs. Overall, the study provides a comprehensive analysis of the impact of NPIs on the spread of COVID-19 in Europe, emphasizing the importance of continued and appropriate interventions to manage the ongoing pandemic.