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

The impact of modelling choices on modelling outcomes: a spatio-temporal  study of the association between COVID-19 spread and environmental conditions  in Catalonia (Spain)