  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 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 by far the most important R0 predictor, 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 show that
several variables that significantly correlate with transmissibility do not
directly influence $R_0$ or affect it differently than suggested by naive
analysis.
