1. Effects of climate factors on hemorrhagic fever with renal syndrome in Changchun, 2013 to 2017
- Author
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Na Li, Xinwen Fan, Yixin Hu, Xiumin Zhang, Biao Huang, Laishun Yao, Meitian Liu, Wenjing Xiong, Meina Li, Ge Zhou, Ping Gong, Qi Wang, Yuan Yin, Qinglong Zhao, Xia Guo, Minfu He, Xiaodi Yang, Zheng Ren, Juan Ma, and Hongjian Liu
- Subjects
China ,Surveillance data ,Climate ,Observational Study ,Wind ,law.invention ,03 medical and health sciences ,0302 clinical medicine ,law ,Risk Factors ,Linear regression ,principal components regression model ,Medicine ,Humans ,030212 general & internal medicine ,climate factors ,Epidemics ,business.industry ,Incidence (epidemiology) ,Incidence ,Temperature ,virus diseases ,Humidity ,General Medicine ,Hantaan virus ,Transmission (mechanics) ,030220 oncology & carcinogenesis ,Hemorrhagic Fever with Renal Syndrome ,Population Surveillance ,Sunshine duration ,business ,Demography ,Research Article - Abstract
Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantaviruses (HVs). Climate factors have a significant impact on the transmission of HFRS. Here, we characterized the dynamic temporal trend of HFRS and identified the roles of climate factors in its transmission in Changchun, China. Surveillance data of HFRS cases and data on related environmental variables from 2013 to 2017 were collected. A principal components regression (PCR) model was used to quantify the relationship between climate factors and transmission of HFRS. During 2013 to 2017, a distinctly declining temporal trend of annual HFRS incidence was identified. Four principal components were extracted, with a cumulative contribution rate of 89.282%. The association between HFRS epidemics and climate factors was better explained by the PCR model (F = 10.050, P
- Published
- 2019