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Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China

Human influenza infections display a strongly seasonal pattern. However, whether H7N9 and H5N1 infections correlate with climate factors has not been examined. Here, we analyzed 350 cases of H7N9 infection and 47 cases of H5N1 infection. The spatial characteristics of these cases revealed that H5N1...

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Autores principales: Li, Jing, Rao, Yuhan, Sun, Qinglan, Wu, Xiaoxu, Jin, Jiao, Bi, Yuhai, Chen, Jin, Lei, Fumin, Liu, Qiyong, Duan, Ziyuan, Ma, Juncai, Gao, George F., Liu, Di, Liu, Wenjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4676028/
https://www.ncbi.nlm.nih.gov/pubmed/26656876
http://dx.doi.org/10.1038/srep18094
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author Li, Jing
Rao, Yuhan
Sun, Qinglan
Wu, Xiaoxu
Jin, Jiao
Bi, Yuhai
Chen, Jin
Lei, Fumin
Liu, Qiyong
Duan, Ziyuan
Ma, Juncai
Gao, George F.
Liu, Di
Liu, Wenjun
author_facet Li, Jing
Rao, Yuhan
Sun, Qinglan
Wu, Xiaoxu
Jin, Jiao
Bi, Yuhai
Chen, Jin
Lei, Fumin
Liu, Qiyong
Duan, Ziyuan
Ma, Juncai
Gao, George F.
Liu, Di
Liu, Wenjun
author_sort Li, Jing
collection PubMed
description Human influenza infections display a strongly seasonal pattern. However, whether H7N9 and H5N1 infections correlate with climate factors has not been examined. Here, we analyzed 350 cases of H7N9 infection and 47 cases of H5N1 infection. The spatial characteristics of these cases revealed that H5N1 infections mainly occurred in the South, Middle, and Northwest of China, while the occurrence of H7N9 was concentrated in coastal areas of East and South of China. Aside from spatial-temporal characteristics, the most adaptive meteorological conditions for the occurrence of human infections by these two viral subtypes were different. We found that H7N9 infections correlate with climate factors, especially temperature (TEM) and relative humidity (RHU), while H5N1 infections correlate with TEM and atmospheric pressure (PRS). Hence, we propose a risky window (TEM 4–14 °C and RHU 65–95%) for H7N9 infection and (TEM 2–22 °C and PRS 980-1025 kPa) for H5N1 infection. Our results represent the first step in determining the effects of climate factors on two different virus infections in China and provide warning guidelines for the future when provinces fall into the risky windows. These findings revealed integrated predictive meteorological factors rooted in statistic data that enable the establishment of preventive actions and precautionary measures against future outbreaks.
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spelling pubmed-46760282015-12-16 Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China Li, Jing Rao, Yuhan Sun, Qinglan Wu, Xiaoxu Jin, Jiao Bi, Yuhai Chen, Jin Lei, Fumin Liu, Qiyong Duan, Ziyuan Ma, Juncai Gao, George F. Liu, Di Liu, Wenjun Sci Rep Article Human influenza infections display a strongly seasonal pattern. However, whether H7N9 and H5N1 infections correlate with climate factors has not been examined. Here, we analyzed 350 cases of H7N9 infection and 47 cases of H5N1 infection. The spatial characteristics of these cases revealed that H5N1 infections mainly occurred in the South, Middle, and Northwest of China, while the occurrence of H7N9 was concentrated in coastal areas of East and South of China. Aside from spatial-temporal characteristics, the most adaptive meteorological conditions for the occurrence of human infections by these two viral subtypes were different. We found that H7N9 infections correlate with climate factors, especially temperature (TEM) and relative humidity (RHU), while H5N1 infections correlate with TEM and atmospheric pressure (PRS). Hence, we propose a risky window (TEM 4–14 °C and RHU 65–95%) for H7N9 infection and (TEM 2–22 °C and PRS 980-1025 kPa) for H5N1 infection. Our results represent the first step in determining the effects of climate factors on two different virus infections in China and provide warning guidelines for the future when provinces fall into the risky windows. These findings revealed integrated predictive meteorological factors rooted in statistic data that enable the establishment of preventive actions and precautionary measures against future outbreaks. Nature Publishing Group 2015-12-11 /pmc/articles/PMC4676028/ /pubmed/26656876 http://dx.doi.org/10.1038/srep18094 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Li, Jing
Rao, Yuhan
Sun, Qinglan
Wu, Xiaoxu
Jin, Jiao
Bi, Yuhai
Chen, Jin
Lei, Fumin
Liu, Qiyong
Duan, Ziyuan
Ma, Juncai
Gao, George F.
Liu, Di
Liu, Wenjun
Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China
title Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China
title_full Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China
title_fullStr Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China
title_full_unstemmed Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China
title_short Identification of climate factors related to human infection with avian influenza A H7N9 and H5N1 viruses in China
title_sort identification of climate factors related to human infection with avian influenza a h7n9 and h5n1 viruses in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4676028/
https://www.ncbi.nlm.nih.gov/pubmed/26656876
http://dx.doi.org/10.1038/srep18094
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