A graph convolutional network for predicting COVID-19 dynamics in 190 regions/countries.

ABSTRACT:

Introduction

Coronavirus disease (COVID-19) rapidly spread from Wuhan, China to other parts of China and other regions/countries around the world, resulting in a pandemic due to large populations moving through the massive transport hubs connecting all regions of China via railways and a major international airport. COVID-19 will remain a threat until safe and effective vaccines and antiviral drugs have been developed, distributed, and administered on a global scale. Thus, there is urgent need to establish effective implementation of preemptive non-pharmaceutical interventions for appropriate prevention and control strategies, and predicting future COVID-19 cases is required to monitor and control the issue.

Methods

This study attempts to utilize a three-layer graph c

SUBMITTER: Anno S 

PROVIDER: S-EPMC9381970 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature