Abstract
Some studies have demonstrated that precipitation is an important risk factor of dengue epidemics. However, current studies mostly focused on a single precipitation variable, and few studies focused on the impact of precipitation patterns on dengue epidemics. This study aims to explore optimal precipitation patterns for dengue epidemics. Weekly dengue case counts and meteorological data from 2006 to 2018 in Guangzhou of China were collected. A generalized additive model with Poisson distribution was used to investigate the association between precipitation patterns and dengue. Precipitation patterns were defined as the combinations of three weekly precipitation variables: accumulative precipitation (Pre_A), the number of days with light or moderate precipitation (Pre_LMD), and the coefficient of precipitation variation (Pre_CV). We explored to identify optimal precipitation patterns for dengue epidemics. With a lead time of 10 weeks, minimum temperature, relative humidity, Pre_A, and Pre_LMD were positively associated with dengue, while Pre_CV was negatively associated with dengue. A precipitation pattern with Pre_A of 20.67–55.50 mm per week, Pre_LMD of 3–4 days per week, and Pre_CV less than 1.41 per week might be an optimal precipitation pattern for dengue epidemics in Guangzhou. The finding may be used for climate-smart early warning and decision-making of dengue prevention and control.
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Data availability
The dengue data that support the findings of this study are available from Chinese National Notifiable Infectious Disease Reporting Information System, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Chinese Center for Disease Control and Prevention. The meteorological datasets supporting the conclusions of this article are available in China Meteorological Data Service Center repository (http://data.cma.cn/).
Abbreviations
- DENV:
-
dengue virus
- GAM:
-
generalized additive models
- GCV:
-
generalized cross validation
- Log RR:
-
logarithmic value of relative risk
- NNIDRIS:
-
National Notifiable Infectious Disease Reporting Information System
- Pre_A:
-
accumulative precipitation
- Pre_CV:
-
the coefficient of precipitation variation
- Pre_LMD:
-
the number of days with light or moderate precipitation
- Rh:
-
relative humidity
- SD:
-
standard deviation
- Tmin:
-
minimum temperature
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Acknowledgements
We are grateful to all those involved in the dengue data collection and infectious disease surveillance systems, coupled with the funders of this study.
Funding
This study was supported by the National Key R&D Program of China (2018YFA0606200, 2018YFB0505500, 2018YFB0505503), the National Natural Science Foundation of China (81773497, 41701460), the Natural Science Foundation of Guangdong Province (2018A030313729), and the Science and Technology Planning Project of Guangdong Province (2018B020207006, 2019B020208005).
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Conceived and designed the study: Wenjun Ma, Jianpeng Xiao, Tao Liu
Collected the data: Min Kang, Tie Song, Zhiqiang Peng, Aiping Deng
Analyzed the data: Haorong Meng, Dexin Gong, Zhihua Zhu
Wrote the paper: Haorong Meng
Revised the manuscript: Wenjun Ma, Jianpeng Xiao
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Meng, H., Xiao, J., Liu, T. et al. The impacts of precipitation patterns on dengue epidemics in Guangzhou city. Int J Biometeorol 65, 1929–1937 (2021). https://doi.org/10.1007/s00484-021-02149-2
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DOI: https://doi.org/10.1007/s00484-021-02149-2