Genomic epidemiology of SARS-CoV-2 virus with a bioinformatics platform

Abstract

Introduction: viral epidemics have presented a risk to human health since they can turn into pandemics and affect a large part of the population, especially for poor developing countries. In 2020, the worldwide pandemic of COVID-19 is underway. Research is currently being carried out showing data that combines genetic and social information that can change our understanding of the dynamics of the epidemic. Objective: to describe data science-based technology tool called Nextstrain that allows epidemics to be visualized with data as up to date as possible using academic databases. Development: there are currently viral sequences from 57 countries on 6 continents. The common ancestor of the virus circulating in the world emerged in Wuhan, China, in late November or early December 2019, and from where it is supposed to have mutated towards humans, from bats and pangolins. Regarding monitoring, research work is already being carried out using this tool, such as in Taiwan, France, and Finland, which were able to determine where the SARS-CoV-2 strains that were causing outbreaks in their respective country originated. Besides, Nextstrain allows to freely share the phylogenetic analyzes of various authors from different countries and allows us to see the great work in the epidemiology of the virus. Conclusions: Nextstrain is a tool based on big data that gives us a better view of the worldwide epidemiology of pathogens of interest. Its use is based on bioinformatic tools and it shows us this information through a pleasant and understandable ecosystem.

Keywords

• coronavirus infections, severe acute respiratory syndrome, betacoronavirus
• genome, viral
• semantic web