  The spread of COVID-19 has brought challenges to health, social and economic
systems around the world. With little to no prior immunity in the global
population transmission has been driven primarily by human interaction.
However, as with common respiratory illnesses such as the flu it's suggested
that COVID-19 may become seasonal as immunity grows. Yet the effects of
meteorological conditions on the spread of COVID-19 are poorly understood with
previous studies producing contrasting results, due at least in part to limited
and inconsistent study designs. This study investigates the effect of
meteorological conditions on COVID-19 infections in England using a
spatio-temporal model applied to case counts during the initial England
lockdown. By modelling spatial and temporal effects to account for the nature
of a human transmissible virus the model isolates meteorological effects.
Inference based on 95% highest posterior density intervals shows humidity is
negatively associated with COVID-19 spread. The lack of evidence for other
weather factors affecting COVID-19 transmission shows care should be taken with
respect to seasonality when designing COVID-19 policies and public
communications.
