Dynamics of SARS-CoV-2 genetic mutations and their information entropy

Abstract

We report an investigation of the mutations dynamics of the SARS-CoV-2 virus using Shannons information theory. Our study includes seventeen RNA genetic sequences collected at different geographic locations and timeframes ranging from Dec. 2019 to Oct. 2021. The data shows a previously unobserved relationship between the information entropy of genomes and their mutation dynamics. The information entropy of the mutated variants decreases linearly with the number of genetic mutations with a negative slope of 1.52 x 10-5 bits / mutations, pointing to a possible deterministic approach to the dynamics of genetic mutations. The method proposed here could be used to develop a predictive algorithm of genetic mutations.