COVID-19 waves: intrinsic and extrinsic spatio-temporal dynamics over Italy

COVID-19 waves, mostly due to variants, still require timely efforts from governments based on real-time forecasts of the epidemics via dynamical and statistical models. Nevertheless, less attention has been paid in investigating and characterizing the intrinsic and extrinsic spatio-temporal dynamics of the epidemic spread. The large amount of data, both in terms of data points and observables, allows us to perform a detailed characteristic of the epidemic waves and their relation with different sources as testing capabilities, vaccination policies, and restriction measures.

By taking as a case-study the epidemic evolution of COVID-19 across Italian regions we perform the Hilbert-Huang Transform (HHT) analysis to investigate its spatio-temporal dynamics. We identified a similar number of temporal components within all Italian regions that can be linked to both intrisic and extrinsic source mechanisms as the efficiency of restriction measures, testing strategies and performances, and vaccination policies. We also identified mutual scale-dependent relations within different regions, thus suggesting an additional source mechanisms related to the delayed spread of the epidemics due to travels and movements of people. Our results are also extremely helpful for providing long term extrapolation of epidemics counts by taking into account both the intrinsically and the extrinsically non-linear nature of the underlying dynamics.