  Identifying the main environmental drivers of SARS-CoV-2 transmissibility in
the population is crucial for understanding current and potential future
outbursts of COVID-19 and other infectious diseases. To address this problem,
we concentrate on the basic reproduction number $R_0$, which is not sensitive
to testing coverage and represents transmissibility in an absence of social
distancing and in a completely susceptible population. While many variables may
potentially influence $R_0$, a high correlation between these variables may
obscure the result interpretation. Consequently, we combine Principal Component
Analysis with feature selection methods from several regression-based
approaches to identify the main demographic and meteorological drivers behind
$R_0$. We robustly obtain that country's wealth/development (GDP per capita or
Human Development Index) is the most important $R_0$ predictor at the global
level, probably being a good proxy for the overall contact frequency in a
population. This main effect is modulated by built-up area per capita
(crowdedness in indoor space), onset of infection (likely related to increased
awareness of infection risks), net migration, unhealthy living
lifestyle/conditions including pollution, seasonality, and possibly BCG
vaccination prevalence. Also, we argue that several variables that
significantly correlate with transmissibility do not directly influence $R_0$
or affect it differently than suggested by naive analysis.
