Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
- Oklahoma State University, United States
- University College London, United Kingdom
Abstract
COVID19 has aptly revealed that airborne viruses such as SARS-CoV-2 with the ability to rapidly mutate, combined with high rates of transmission and fatality can cause a deadly world-wide pandemic in a matter of weeks.1 Apart from vaccines and post-infection treatment options, strategies for preparedness will be vital in responding to the current and future pandemics. Therefore, there is wide interest in approaches that allow predictions of increase in infections ('surges') before they occur. We describe here real time genomic surveillance particularly based on mutation analysis, of viral proteins as a methodology for a priori determination of surge in number of infection cases. The full results are available for SARS-CoV-2 at http://pandemics.okstate.edu/covid19/, and are updated daily as new virus sequences become available. This approach is generic and will also be applicable to other pathogens.
Data availability
All sequences used in this work are available from GenBank. The protocol used for analysis are described in the supporting information.
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Funding
No external funding was received for this work.
Copyright
© 2023, Najar et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
eLife 12:e82980.
https://doi.org/10.7554/eLife.82980
