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Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance

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 worldwide pandemic in a matter of weeks (Plato et al., 2021). Apart from vaccines and post-infection treatment options, stra...

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Autores principales: Najar, Fares Z, Linde, Evan, Murphy, Chelsea L, Borin, Veniamin A, Wang, Huan, Haider, Shozeb, Agarwal, Pratul K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894583/
https://www.ncbi.nlm.nih.gov/pubmed/36655992
http://dx.doi.org/10.7554/eLife.82980
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author Najar, Fares Z
Linde, Evan
Murphy, Chelsea L
Borin, Veniamin A
Wang, Huan
Haider, Shozeb
Agarwal, Pratul K
author_facet Najar, Fares Z
Linde, Evan
Murphy, Chelsea L
Borin, Veniamin A
Wang, Huan
Haider, Shozeb
Agarwal, Pratul K
author_sort Najar, Fares Z
collection PubMed
description 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 worldwide pandemic in a matter of weeks (Plato et al., 2021). 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.
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spelling pubmed-98945832023-02-03 Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance Najar, Fares Z Linde, Evan Murphy, Chelsea L Borin, Veniamin A Wang, Huan Haider, Shozeb Agarwal, Pratul K eLife Epidemiology and Global Health 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 worldwide pandemic in a matter of weeks (Plato et al., 2021). 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. eLife Sciences Publications, Ltd 2023-01-19 /pmc/articles/PMC9894583/ /pubmed/36655992 http://dx.doi.org/10.7554/eLife.82980 Text en © 2023, Najar et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Epidemiology and Global Health
Najar, Fares Z
Linde, Evan
Murphy, Chelsea L
Borin, Veniamin A
Wang, Huan
Haider, Shozeb
Agarwal, Pratul K
Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
title Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
title_full Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
title_fullStr Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
title_full_unstemmed Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
title_short Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance
title_sort future covid19 surges prediction based on sars-cov-2 mutations surveillance
topic Epidemiology and Global Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894583/
https://www.ncbi.nlm.nih.gov/pubmed/36655992
http://dx.doi.org/10.7554/eLife.82980
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