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Fluid dynamics and epidemiology: Seasonality and transmission dynamics
Epidemic models do not account for the effects of climate conditions on the transmission dynamics of viruses. This study presents the vital relationship between weather seasonality, airborne virus transmission, and pandemic outbreaks over a whole year. Using the data obtained from high-fidelity mult...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AIP Publishing LLC
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7976049/ https://www.ncbi.nlm.nih.gov/pubmed/33746486 http://dx.doi.org/10.1063/5.0037640 |
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author | Dbouk, Talib Drikakis, Dimitris |
author_facet | Dbouk, Talib Drikakis, Dimitris |
author_sort | Dbouk, Talib |
collection | PubMed |
description | Epidemic models do not account for the effects of climate conditions on the transmission dynamics of viruses. This study presents the vital relationship between weather seasonality, airborne virus transmission, and pandemic outbreaks over a whole year. Using the data obtained from high-fidelity multi-phase, fluid dynamics simulations, we calculate the concentration rate of Coronavirus particles in contaminated saliva droplets and use it to derive a new Airborne Infection Rate (AIR) index. Combining the simplest form of an epidemiological model, the susceptible–infected–recovered, and the AIR index, we show through data evidence how weather seasonality induces two outbreaks per year, as it is observed with the COVID-19 pandemic worldwide. We present the results for the number of cases and transmission rates for three cities, New York, Paris, and Rio de Janeiro. The results suggest that two pandemic outbreaks per year are inevitable because they are directly linked to what we call weather seasonality. The pandemic outbreaks are associated with changes in temperature, relative humidity, and wind speed independently of the particular season. We propose that epidemiological models must incorporate climate effects through the AIR index. |
format | Online Article Text |
id | pubmed-7976049 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AIP Publishing LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-79760492021-03-19 Fluid dynamics and epidemiology: Seasonality and transmission dynamics Dbouk, Talib Drikakis, Dimitris Phys Fluids (1994) ARTICLES Epidemic models do not account for the effects of climate conditions on the transmission dynamics of viruses. This study presents the vital relationship between weather seasonality, airborne virus transmission, and pandemic outbreaks over a whole year. Using the data obtained from high-fidelity multi-phase, fluid dynamics simulations, we calculate the concentration rate of Coronavirus particles in contaminated saliva droplets and use it to derive a new Airborne Infection Rate (AIR) index. Combining the simplest form of an epidemiological model, the susceptible–infected–recovered, and the AIR index, we show through data evidence how weather seasonality induces two outbreaks per year, as it is observed with the COVID-19 pandemic worldwide. We present the results for the number of cases and transmission rates for three cities, New York, Paris, and Rio de Janeiro. The results suggest that two pandemic outbreaks per year are inevitable because they are directly linked to what we call weather seasonality. The pandemic outbreaks are associated with changes in temperature, relative humidity, and wind speed independently of the particular season. We propose that epidemiological models must incorporate climate effects through the AIR index. AIP Publishing LLC 2021-02-01 2021-02-02 /pmc/articles/PMC7976049/ /pubmed/33746486 http://dx.doi.org/10.1063/5.0037640 Text en © 2021 Author(s) Published under license by AIP Publishing. 1070-6631/2021/33(2)/021901/9/$30.00 All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | ARTICLES Dbouk, Talib Drikakis, Dimitris Fluid dynamics and epidemiology: Seasonality and transmission dynamics |
title | Fluid dynamics and epidemiology: Seasonality and transmission
dynamics |
title_full | Fluid dynamics and epidemiology: Seasonality and transmission
dynamics |
title_fullStr | Fluid dynamics and epidemiology: Seasonality and transmission
dynamics |
title_full_unstemmed | Fluid dynamics and epidemiology: Seasonality and transmission
dynamics |
title_short | Fluid dynamics and epidemiology: Seasonality and transmission
dynamics |
title_sort | fluid dynamics and epidemiology: seasonality and transmission
dynamics |
topic | ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7976049/ https://www.ncbi.nlm.nih.gov/pubmed/33746486 http://dx.doi.org/10.1063/5.0037640 |
work_keys_str_mv | AT dbouktalib fluiddynamicsandepidemiologyseasonalityandtransmissiondynamics AT drikakisdimitris fluiddynamicsandepidemiologyseasonalityandtransmissiondynamics |