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Modeling influenza seasonality in the tropics and subtropics

Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist....

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Autores principales: Yuan, Haokun, Kramer, Sarah C., Lau, Eric H. Y., Cowling, Benjamin J., Yang, Wan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216520/
https://www.ncbi.nlm.nih.gov/pubmed/34106917
http://dx.doi.org/10.1371/journal.pcbi.1009050
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author Yuan, Haokun
Kramer, Sarah C.
Lau, Eric H. Y.
Cowling, Benjamin J.
Yang, Wan
author_facet Yuan, Haokun
Kramer, Sarah C.
Lau, Eric H. Y.
Cowling, Benjamin J.
Yang, Wan
author_sort Yuan, Haokun
collection PubMed
description Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist. In addition, multiple influenza viruses could cocirculate and shape epidemic dynamics. Here we construct seven mechanistic epidemic models to test the effect of two major climate drivers (humidity and temperature) and multi-strain co-circulation on influenza transmission in Hong Kong, an influenza epidemic center located in the subtropics. Based on model fit to long-term influenza surveillance data from 1998 to 2018, we found that a simple model incorporating the effect of both humidity and temperature best recreated the influenza epidemic patterns observed in Hong Kong. The model quantifies a bimodal effect of absolute humidity on influenza transmission where both low and very high humidity levels facilitate transmission quadratically; the model also quantifies the monotonic but nonlinear relationship with temperature. In addition, model results suggest that, at the population level, a shorter immunity period can approximate the co-circulation of influenza virus (sub)types. The basic reproductive number R(0) estimated by the best-fit model is also consistent with laboratory influenza survival and transmission studies under various combinations of humidity and temperature levels. Overall, our study has developed a simple mechanistic model capable of quantifying the impact of climate drivers on influenza transmission in (sub)tropical regions. This model can be applied to improve influenza forecasting in the (sub)tropics in the future.
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spelling pubmed-82165202021-07-01 Modeling influenza seasonality in the tropics and subtropics Yuan, Haokun Kramer, Sarah C. Lau, Eric H. Y. Cowling, Benjamin J. Yang, Wan PLoS Comput Biol Research Article Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist. In addition, multiple influenza viruses could cocirculate and shape epidemic dynamics. Here we construct seven mechanistic epidemic models to test the effect of two major climate drivers (humidity and temperature) and multi-strain co-circulation on influenza transmission in Hong Kong, an influenza epidemic center located in the subtropics. Based on model fit to long-term influenza surveillance data from 1998 to 2018, we found that a simple model incorporating the effect of both humidity and temperature best recreated the influenza epidemic patterns observed in Hong Kong. The model quantifies a bimodal effect of absolute humidity on influenza transmission where both low and very high humidity levels facilitate transmission quadratically; the model also quantifies the monotonic but nonlinear relationship with temperature. In addition, model results suggest that, at the population level, a shorter immunity period can approximate the co-circulation of influenza virus (sub)types. The basic reproductive number R(0) estimated by the best-fit model is also consistent with laboratory influenza survival and transmission studies under various combinations of humidity and temperature levels. Overall, our study has developed a simple mechanistic model capable of quantifying the impact of climate drivers on influenza transmission in (sub)tropical regions. This model can be applied to improve influenza forecasting in the (sub)tropics in the future. Public Library of Science 2021-06-09 /pmc/articles/PMC8216520/ /pubmed/34106917 http://dx.doi.org/10.1371/journal.pcbi.1009050 Text en © 2021 Yuan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yuan, Haokun
Kramer, Sarah C.
Lau, Eric H. Y.
Cowling, Benjamin J.
Yang, Wan
Modeling influenza seasonality in the tropics and subtropics
title Modeling influenza seasonality in the tropics and subtropics
title_full Modeling influenza seasonality in the tropics and subtropics
title_fullStr Modeling influenza seasonality in the tropics and subtropics
title_full_unstemmed Modeling influenza seasonality in the tropics and subtropics
title_short Modeling influenza seasonality in the tropics and subtropics
title_sort modeling influenza seasonality in the tropics and subtropics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216520/
https://www.ncbi.nlm.nih.gov/pubmed/34106917
http://dx.doi.org/10.1371/journal.pcbi.1009050
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