The coronavirus disease 2019 (COVID-19) pandemic has dramatically increased the awareness of emerging infectious diseases. The advancement of multiomics analysis technology has resulted in the development of several databases containing virus information.
Several scientists have integrated existing data on viruses to construct phylogenetic trees and predict virus mutation and transmission in different ways, providing prospective technical support for epidemic prevention and control.
This article summarizes the databases of known emerging infectious viruses and techniques focusing on virus variant forecasting and early warning. It focuses on the multi-dimensional information integration and database construction of emerging infectious viruses, virus mutation spectrum construction and variant forecast model, analysis of the affinity between mutation antigen and the receptor, propagation model of virus dynamic evolution, and monitoring and early warning for variants.
The authors have focused on the research results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses to comprehensively review the latest virus research and provided a reference for future virus prevention and control research.
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Journal reference:
Haotian Ren, Yunchao Ling, Ruifang Cao, Zhen Wang, Yixue Li, Tao Huang, Early warning of emerging infectious diseases based on multimodal data, Biosafety and Health, 2023, ISSN 2590-0536, https://doi.org/10.1016/j.bsheal.2023.05.006
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