Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis

被引:5
作者
He, Junyu [1 ,2 ]
Wang, Yong [3 ]
Liu, Ping [4 ]
Yin, Wenwu [5 ]
Wei, Xianyu [3 ]
Sun, Hailong [3 ]
Xu, Yuanyong [3 ]
Li, Shanshan [6 ]
Magalhaes, Ricardo J. Soares [7 ,8 ]
Guo, Yuming [6 ]
Zhang, Wenyi [3 ]
机构
[1] Zhejiang Univ, Ocean Coll, Zhoushan, Peoples R China
[2] Zhejiang Univ, Ocean Acad, Zhoushan, Peoples R China
[3] Chinese PLA Ctr Dis Control & Prevent, 20 Dong Da St, Beijing 100071, Peoples R China
[4] Chinese Peoples Liberat Army Gen Hosp, Dept Gen Practice, Med Ctr 6, Beijing, Peoples R China
[5] Chinese Ctr Dis Control & Prevent, Beijing, Peoples R China
[6] Monash Univ, Sch Publ Hlth & Prevent Med, Dept Epidemiol & Prevent Med, Melbourne, Vic, Australia
[7] Univ Queensland, Sch Vet Sci, Spatial Epidemiol Lab, Brisbane, Qld, Australia
[8] Univ Queensland, Child Hlth Res Ctr, Brisbane, Qld, Australia
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Scrub typhus; Clusters; Partial wavelet coherency; Climate; Wavelet power spectra; METEOROLOGICAL FACTORS; RAPID INCREASE; PRECIPITATION; OSCILLATION; ECOLOGY; INDEXES; SERIES; KOREA; RISK;
D O I
10.1016/j.onehlt.2022.100446
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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 Nin tilde o and La Nin tilde a 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 Nin tilde o and La Nin tilde a 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 co-herency 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.
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页数:26
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