In this paper, we compare the inference regarding the effectiveness of the various non-pharmaceutical interventions (NPIs) for COVID-19 obtained from two SIR models, both produced by the Imperial College COVID-19 Response Team. One model was applied to European countries and published in Nature, concluding that complete lockdown was by far the most effective measure and 3 million deaths were avoided in the examined countries. The Imperial College team applied a different model to the USA states. Here, we show that inference is not robust to model specification and indeed changes substantially with the model used for the evolution of the time-varying reproduction number. Applying to European countries the model that the Imperial College team used for the USA states shows that complete lockdown has no or little impact, since it was introduced typically at a point when the time-varying reproduction number was already very low. We also show that results are not robust to the inclusion of additional follow-up data.
Collection : COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv