Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions

Tomas Gavenciak, Joshua Teperowski Monrad, Gavin Leech, Mrinank Sharma, Sören Mindermann, Samir Bhatt, Jan Markus Brauner, Jan Kulveit

Abstract: Author Summary Building on two state-of-the-art observational models and datasets, we adapt a fully Bayesian method for estimating the association between seasonality and SARS-CoV-2 transmission in 143 temperate European regions. This approach overcomes limitations of previous analyses that do not account for the implementation of non-pharmaceutical interventions (NPIs) or mobility during the first year of the pandemic and hence may yield biased estimates of seasonal effects. We find that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions. Our findings provide valuable insights for long-term modelling and policy planning. As seasons change, it is vital that policymakers employ accurate estimates of seasonal effects. In the summer, reductions in transmission that owe to seasonality should not be misattributed to population immunity. In the winter, policymakers must avoid anticipating a greater reduction due to seasonality than will actually occur.