Prediction model for dengue fever based on interactive effects between multiple meteorological factors in Guangdong, China (2008-2016)

doi:10.1371/journal.pone.0225811

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 互联网大数据与安全信息学研究中心

	Prediction model for dengue fever based on interactive effects between multiple meteorological factors in Guangdong, China (2008-2016)
	Zhu, Binghua 4,5; Wang, Ligui 5; Wang, Haiying 3; Cao, Zhidong 2; Zha, Lei 5; Li, Ze 5; Ye, Zhongyang 5; Zhang, Jinping 4; Song, Hongbin 5; Sun, Yansong 1
刊名	PLOS ONE
	2019-12-09
卷号	14 期号:12 页码:12
ISSN号	1932-6203
DOI	10.1371/journal.pone.0225811
通讯作者	Zhang, Jinping(jinpingzhang305@126.com) ; Song, Hongbin(hongbinsong@263.net) ; Sun, Yansong(sunys1964@hotmail.com)
英文摘要	Introduction In order to improve the prediction accuracy of dengue fever incidence, we constructed a prediction model with interactive effects between meteorological factors, based on weekly dengue fever cases in Guangdong, China from 2008 to 2016. Methods Dengue fever data were derived from statistical data from the China National Notifiable Infectious Disease Reporting Information System. Daily meteorological data were obtained from the China Integrated Meteorological Information Sharing System. The minimum temperature for transmission was identified using data fitting and the Ross-Macdonald model. Correlations and interactive effects were examined using Spearman's rank correlation and multivariate analysis of variance. A probit regression model to describe the incidence of dengue fever from 2008 to 2016 and forecast the 2017 incidence was constructed, based on key meteorological factors, interactive effects, mosquito-vector factors, and other important factors. Results We found the minimum temperature suitable for dengue transmission was.18 degrees C, and as 97.91% of cases occurred when the minimum temperature was above 18 degrees C, the data were used for model training and construction. Epidemics of dengue are related to mean temperature, maximum/minimum and mean atmospheric pressure, and mean relative humidity. Moreover, interactions occur between mean temperature, minimum atmospheric pressure, and mean relative humidity. Our weekly probit regression prediction model is 0.72. Prediction of dengue cases for the first 41 weeks of 2017 exhibited goodness of fit of 0.60. Conclusion Our model was accurate and timely, with consideration of interactive effects between meteorological factors.
资助项目	Mega-projects of Science and Technology Research[2017ZX10303401] ; Beijing Nova Program[Z171100001117102] ; Military Medical Science and Technology Youth Cultivation Program[19QNP113] ; Military Logistics Research Program[BWS14C051]
WOS关键词	CLIMATE VARIABILITY ; AEDES-ALBOPICTUS ; TEMPERATURE ; VECTOR ; TRANSMISSION ; VARIABLES ; PROVINCE ; SURVIVAL ; AEGYPTI ; VIRUS
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	PUBLIC LIBRARY SCIENCE
WOS记录号	WOS:000534024700011
资助机构	Mega-projects of Science and Technology Research ; Beijing Nova Program ; Military Medical Science and Technology Youth Cultivation Program ; Military Logistics Research Program
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/39450]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心
通讯作者	Zhang, Jinping; Song, Hongbin; Sun, Yansong
作者单位	1.Acad Mil Med Sci, Coll Mil Med, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 3.Natl Def Univ PLA, Joint Serv Inst, Beijing, Peoples R China 4.305 Hosp PLA, Beijing, Peoples R China 5.Chinese PLA Ctr Dis Control & Prevent, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Binghua,Wang, Ligui,Wang, Haiying,et al. Prediction model for dengue fever based on interactive effects between multiple meteorological factors in Guangdong, China (2008-2016)[J]. PLOS ONE,2019,14(12):12.
APA	Zhu, Binghua.,Wang, Ligui.,Wang, Haiying.,Cao, Zhidong.,Zha, Lei.,...&Sun, Yansong.(2019).Prediction model for dengue fever based on interactive effects between multiple meteorological factors in Guangdong, China (2008-2016).PLOS ONE,14(12),12.
MLA	Zhu, Binghua,et al."Prediction model for dengue fever based on interactive effects between multiple meteorological factors in Guangdong, China (2008-2016)".PLOS ONE 14.12(2019):12.