Forecasting the COVID-19 transmission in Italy based on the minimum spanning tree of dynamic region network.

ABSTRACT:

Background

Italy surpassed 1.5 million confirmed Coronavirus Disease 2019 (COVID-19) infections on November 26, as its death toll rose rapidly in the second wave of COVID-19 outbreak which is a heavy burden on hospitals. Therefore, it is necessary to forecast and early warn the potential outbreak of COVID-19 in the future, which facilitates the timely implementation of appropriate control measures. However, real-time prediction of COVID-19 transmission and outbreaks is usually challenging because of its complexity intertwining both biological systems and social systems.

Methods

By mining the dynamical information from region networks and the short-term time series data, we developed a data-driven model, the minimum-spanning-tree-based dynamical network marker (MST-DNM), to q

SUBMITTER: Dong M 

PROVIDER: S-EPMC8253113 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature