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IJERPH
Volume 16
Issue 18
10.3390/ijerph16183434
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Article

The Impacts of Climatic Factors and Vegetation on Hemorrhagic Fever with Renal Syndrome Transmission in China: A Study of 109 Counties

by
Junyu He
1,†,
Yong Wang
2,†,
Di Mu
3,†,
Zhiwei Xu
4,
Quan Qian
2,
Gongbo Chen
5,
Liang Wen
2,
Wenwu Yin
3,
Shanshan Li
5,
Wenyi Zhang
2,* and
Yuming Guo
5,*
1
Ocean College, Zhejiang University, Zhoushan 316021, China
2
Chinese PLA Center for Disease Control and Prevention, Beijing 100071, China
3
Division of Infectious Diseases, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
4
School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland 4059, Australia
5
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to the research.
Int. J. Environ. Res. Public Health 2019, 16(18), 3434; https://doi.org/10.3390/ijerph16183434
Received: 29 July 2019 / Revised: 11 September 2019 / Accepted: 12 September 2019 / Published: 16 September 2019
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Abstract

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne infectious disease caused by hantaviruses. About 90% of global cases were reported in China. We collected monthly data on counts of HFRS cases, climatic factors (mean temperature, rainfall, and relative humidity), and vegetation (normalized difference vegetation index (NDVI)) in 109 Chinese counties from January 2002 to December 2013. First, we used a quasi-Poisson regression with a distributed lag non-linear model to assess the impacts of these four factors on HFRS in 109 counties, separately. Then we conducted a multivariate meta-analysis to pool the results at the national level. The results of our study showed that there were non-linear associations between the four factors and HFRS. Specifically, the highest risks of HFRS occurred at the 45th, 30th, 20th, and 80th percentiles (with mean and standard deviations of 10.58 ± 4.52 °C, 18.81 ± 17.82 mm, 58.61 ± 6.33%, 198.20 ± 22.23 at the 109 counties, respectively) of mean temperature, rainfall, relative humidity, and NDVI, respectively. HFRS case estimates were most sensitive to mean temperature amongst the four factors, and the lag patterns of the impacts of these factors on HFRS were heterogeneous. Our findings provide rigorous scientific support to current HFRS monitoring and the development of early warning systems. View Full-Text
Keywords: orthohantavirus; hantavirus disease; risk map; distributed lag non-linear model; meta-analysis orthohantavirus; hantavirus disease; risk map; distributed lag non-linear model; meta-analysis
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MDPI and ACS Style

He, J.; Wang, Y.; Mu, D.; Xu, Z.; Qian, Q.; Chen, G.; Wen, L.; Yin, W.; Li, S.; Zhang, W.; Guo, Y. The Impacts of Climatic Factors and Vegetation on Hemorrhagic Fever with Renal Syndrome Transmission in China: A Study of 109 Counties. Int. J. Environ. Res. Public Health 2019, 16, 3434. https://doi.org/10.3390/ijerph16183434

AMA Style

He J, Wang Y, Mu D, Xu Z, Qian Q, Chen G, Wen L, Yin W, Li S, Zhang W, Guo Y. The Impacts of Climatic Factors and Vegetation on Hemorrhagic Fever with Renal Syndrome Transmission in China: A Study of 109 Counties. International Journal of Environmental Research and Public Health. 2019; 16(18):3434. https://doi.org/10.3390/ijerph16183434

Chicago/Turabian Style

He, Junyu, Yong Wang, Di Mu, Zhiwei Xu, Quan Qian, Gongbo Chen, Liang Wen, Wenwu Yin, Shanshan Li, Wenyi Zhang, and Yuming Guo. 2019. "The Impacts of Climatic Factors and Vegetation on Hemorrhagic Fever with Renal Syndrome Transmission in China: A Study of 109 Counties" International Journal of Environmental Research and Public Health 16, no. 18: 3434. https://doi.org/10.3390/ijerph16183434

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