A Topological Data Analysis Approach to the COVID-19

ABSTRACT

Topological data analysis (TDA) has emerged as a method for understanding data clouds by extracting and comparing the structure of datasets. This paper applies one of the TDA instruments available which is called the Mapper algorithm to analyze the COVID-19 data in China. The Mapper graphs generated by the algorithm successfully reflect the development of COVID-19 across China and provide a relatively complete visualization of the pandemic. Experimental results indicate that the proposed method may have the potential to become a robust predictive tool for the spread of the coronavirus. © 2022 IEEE.