A Mathematical Dashboard for the Analysis of Italian COVID-19 Epidemic Data

TL;DR

This paper introduces the epiMOX dashboard for analyzing Italian COVID-19 data and complements it with the SUIHTER model for epidemic forecasting, providing both descriptive and predictive insights.

Contribution

It presents a comprehensive dashboard for COVID-19 data analysis combined with a novel epidemiological model for short-term epidemic prediction.

Findings

The dashboard offers real-time epidemic trend visualization.

The SUIHTER model improves short-term forecast accuracy.

The approach enhances understanding of epidemic dynamics in Italy.

Abstract

An analysis of the COVID-19 epidemic is proposed on the basis of the epiMOX dashboard (publicly accessible at https://www.epimox.polimi.it) that deals with data of the epidemic trends and outbreaks in Italy from late February 2020. Our analysis provides an immediate appreciation of the past epidemic development, together with its current trends by fostering a deeper interpretation of available data through several critical epidemic indicators. In addition, we complement the epiMOX dashboard with a predictive tool based on an epidemiological compartmental model, named SUIHTER, for the forecast on the near future epidemic evolution.