Entropy-Based Informational Study of the COVID-19 Series of Data

Since the appearance in China of first cases, entire world has been deeply affected by flagellum Coronavirus Disease (COVID-19) pandemic. There have many mathematical approaches trying to characterize data collected about this serious issue. One most important aspects for attacking a problem is knowing what information really available. We investigate here contained COVID-19 infected and deceased people all countries, using informational quantifiers such as entropy statistical complexity. For evaluation these quantities, we use Bandt–Pompe permutation methodology, well wavelet transform, obtain corresponding probability distributions from available series data. The period analyzed covers disease up massive anti-COVID vaccines.