  The choices that researchers make while conducting a statistical analysis
usually have a notable impact on the results. This fact has become evident in
the ongoing research of the association between the environment and the
evolution of the COVID-19 pandemic, in light of the hundreds of contradictory
studies that have already been published on this issue in just a few months. In
this paper, a COVID-19 dataset containing the number of daily cases registered
in the regions of Catalonia (Spain) since the start of the pandemic is
analysed. Specifically, the possible effect of several environmental variables
(solar exposure, mean temperature, and wind speed) on the number of cases is
assessed. Thus, the first objective of the paper is to show how the choice of a
certain type of statistical model to conduct the analysis can have a severe
impact on the associations that are inferred between the covariates and the
response variable. Secondly, it is shown how the use of spatio-temporal models
accounting for the nature of the data allows understanding the evolution of the
pandemic in space and time.
