Analysis of the Sars-COVID 19 trend: from time series to visibility graphs

Sars COVID-19 epidemic continues to represent a relevant and current topic, which is of concern mainly with respect to possible variants. Predictive monitoring can address the need to reduce the risk of spreading the virus, but it needs to rely on non-invasive, as well as effective and inexpensive strategies. Wastewater-Based Epidemiology (WBE) fits into this context, representing an approach to surveillance of diseases and early warning for any outbreaks of pathogenic viruses, which provides results relating to the trend of the epidemic in the form of time series. An innovative approach that allows to infer information on the spread of Sars COVID-19 is to transform the data of these time series into visibility graphs using the so-called visibility algorithms. The connective structure of the visibility graph inherits many properties of the starting time series and allows to extract nontrivial information on the behavior of the system using topological metrics of the Complex Network Theory (CNT). In this work, the time series of Sars COVID-19 corresponding to a 12-month period for a treatment plant serving a large size basin is analyzed in order to provide useful data on the spread of the epidemic.