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Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis
BACKGROUND: Scrub Typhus (ST) is a rickettsial disease caused by Orientia tsutsugamushi. The number of ST cases has been increasing in China during the past decades, which attracts great concerns of the public health. METHODS: We obtained monthly documented ST cases greater than 54 cases in 434 coun...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582591/ https://www.ncbi.nlm.nih.gov/pubmed/36277104 http://dx.doi.org/10.1016/j.onehlt.2022.100446 |
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author | He, Junyu Wang, Yong Liu, Ping Yin, Wenwu Wei, Xianyu Sun, Hailong Xu, Yuanyong Li, Shanshan Soares Magalhaes, Ricardo J. Guo, Yuming Zhang, Wenyi |
author_facet | He, Junyu Wang, Yong Liu, Ping Yin, Wenwu Wei, Xianyu Sun, Hailong Xu, Yuanyong Li, Shanshan Soares Magalhaes, Ricardo J. Guo, Yuming Zhang, Wenyi |
author_sort | He, Junyu |
collection | PubMed |
description | BACKGROUND: Scrub Typhus (ST) is a rickettsial disease caused by Orientia tsutsugamushi. The number of ST cases has been increasing in China during the past decades, which attracts great concerns of the public health. METHODS: We obtained monthly documented ST cases greater than 54 cases in 434 counties of China during 2012–2020. Spatiotemporal wavelet analysis was conducted to identify the ST clusters with similar pattern of the temporal variation and explore the association between ST variation and El Niño and La Niña events. Wavelet coherency analysis and partial wavelet coherency analysis was employed to further explore the co-effects of global and local climatic factors on ST. RESULTS: Wavelet cluster analysis detected seven clusters in China, three of which are mainly distributed in Eastern China, while the other four clusters are located in the Southern China. Among the seven clusters, summer and autumn-winter peak of ST are the two main outbreak periods; while stable and fluctuated periodic feature of ST series was found at 12-month and 4-(or 6-) month according to the wavelet power spectra. Similarly, the three-character bands were also found in the associations between ST and El Niño and La Niña events, among which the 12-month period band showed weakest climate-ST association and the other two bands owned stronger association, indicating that the global climate dynamics may have short-term effects on the ST variations. Meanwhile, 12-month period band with strong association was found between the four local climatic factors (precipitation, pressure, relative humidity and temperature) and the ST variations. Further, partial wavelet coherency analysis suggested that global climatic dynamics dominate annual ST variations, while local climatic factors dominate the small periods. CONCLUSION: The ST variations are not directly attributable to the change in large-scale climate. The existence of these plausible climatic determinants stimulates the interests for more insights into the epidemiology of ST, which is important for devising prevention and early warning strategies. |
format | Online Article Text |
id | pubmed-9582591 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-95825912022-10-21 Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis He, Junyu Wang, Yong Liu, Ping Yin, Wenwu Wei, Xianyu Sun, Hailong Xu, Yuanyong Li, Shanshan Soares Magalhaes, Ricardo J. Guo, Yuming Zhang, Wenyi One Health Research Paper BACKGROUND: Scrub Typhus (ST) is a rickettsial disease caused by Orientia tsutsugamushi. The number of ST cases has been increasing in China during the past decades, which attracts great concerns of the public health. METHODS: We obtained monthly documented ST cases greater than 54 cases in 434 counties of China during 2012–2020. Spatiotemporal wavelet analysis was conducted to identify the ST clusters with similar pattern of the temporal variation and explore the association between ST variation and El Niño and La Niña events. Wavelet coherency analysis and partial wavelet coherency analysis was employed to further explore the co-effects of global and local climatic factors on ST. RESULTS: Wavelet cluster analysis detected seven clusters in China, three of which are mainly distributed in Eastern China, while the other four clusters are located in the Southern China. Among the seven clusters, summer and autumn-winter peak of ST are the two main outbreak periods; while stable and fluctuated periodic feature of ST series was found at 12-month and 4-(or 6-) month according to the wavelet power spectra. Similarly, the three-character bands were also found in the associations between ST and El Niño and La Niña events, among which the 12-month period band showed weakest climate-ST association and the other two bands owned stronger association, indicating that the global climate dynamics may have short-term effects on the ST variations. Meanwhile, 12-month period band with strong association was found between the four local climatic factors (precipitation, pressure, relative humidity and temperature) and the ST variations. Further, partial wavelet coherency analysis suggested that global climatic dynamics dominate annual ST variations, while local climatic factors dominate the small periods. CONCLUSION: The ST variations are not directly attributable to the change in large-scale climate. The existence of these plausible climatic determinants stimulates the interests for more insights into the epidemiology of ST, which is important for devising prevention and early warning strategies. Elsevier 2022-10-13 /pmc/articles/PMC9582591/ /pubmed/36277104 http://dx.doi.org/10.1016/j.onehlt.2022.100446 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper He, Junyu Wang, Yong Liu, Ping Yin, Wenwu Wei, Xianyu Sun, Hailong Xu, Yuanyong Li, Shanshan Soares Magalhaes, Ricardo J. Guo, Yuming Zhang, Wenyi Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis |
title | Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis |
title_full | Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis |
title_fullStr | Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis |
title_full_unstemmed | Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis |
title_short | Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis |
title_sort | co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland china based on a nine-year time-frequency analysis |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582591/ https://www.ncbi.nlm.nih.gov/pubmed/36277104 http://dx.doi.org/10.1016/j.onehlt.2022.100446 |
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