Exploring spatiotemporal nonstationary effects of climate factors on hand, foot, and mouth disease using Bayesian Spatiotemporally Varying Coefficients (STVC) model in Sichuan, China

doi:10.1016/j.scitotenv.2018.08.114

	Exploring spatiotemporal nonstationary effects of climate factors on hand, foot, and mouth disease using Bayesian Spatiotemporally Varying Coefficients (STVC) model in Sichuan, China
	Song, Chao 1,2,3; Shi, Xun 2; Bo, Yanchen 4; Wang, Jinfeng 3,5; Wang, Yong 3; Huang, Dacang 3
刊名	SCIENCE OF THE TOTAL ENVIRONMENT
	2019-01-15
卷号	648 页码:550-560
关键词	HFMD epidemics Disease-climate associations Bayesian STVC model Spatiotemporal nonstationarity OR spatiatization and mapping Local regression
ISSN号	0048-9697
DOI	10.1016/j.scitotenv.2018.08.114
通讯作者	Shi, Xun(xun.shi@dartmouth.edu)
英文摘要	Background: Pediatric hand, foot, and mouth disease (HFMD) has generally been found to be associated with climate. However, knowledge about how this association varies spatiotemporally is very limited, especially when considering the influence of local socioeconomic conditions. This study aims to identify multi-sourced HFMD environmental factors and further quantify the spatiotemporal nonstationary effects of various climate factors on HFMD occurrence. Methods: We propose an innovative method, named spatiotemporally varying coefficients (STVC) model, under the Bayesian hierarchical modeling framework, for exploring both spatial and temporal nonstationary effects in climate covariates, after controlling for socioeconomic effects. We use data of monthly county-level HFMD occurrence and data of related climate and socioeconomic variables in Sichuan. China from 2009 to 2011 for our experiments. Results: Cross-validation experiments showed that the STVC model achieved the best average prediction accuracy (81.98%), compared with ordinary (6827%), temporal (72.34%), spatial (75.99%) and spatiotemporal (77.60%) ecological models. The STVC model also outperformed these models in the Bayesian model evaluation. In this study, the STVC model was able to spatialize the risk indicator odds ratio (OR) into local ORs to represent spatial and temporal varying disease-climate relationships. We detected local temporal nonlinear seasonal trends and spatial hot spots for both disease occurrence and disease-climate associations over 36 months in Sichuan. China. Among the six representative climate variables, temperature (OR = 259), relative humidity (OR = 1.35), and wind speed (OR = 0.65) were not only overall related to the increase of HFMD occurrence, but also demonstrated spatiotemporal variations in their local associations with HFMD. Conclusion: Our findings show that county-level HFMD interventions may need to consider varying local-scale spatial and temporal disease-climate relationships. Our proposed Bayesian STVC model can capture spatiotemporal nonstationary exposure-response relationships for detailed exposure assessments and advanced risk mapping, and offers new insights to broader environmental science and spatial statistics. (C) 2018 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[41701448] ; Southwest Petroleum University[201699010064] ; State Key Laboratory of Resources and Environmental Information System ; State Key Laboratory of Remote Sensing Science
WOS关键词	METEOROLOGICAL FACTORS ; AMBIENT-TEMPERATURE ; MAINLAND CHINA ; PROVINCE ; REGRESSION ; MORTALITY ; HFMD ; EPIDEMIOLOGY ; GUANGDONG ; INFERENCE
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000447805500052
资助机构	National Natural Science Foundation of China ; Southwest Petroleum University ; State Key Laboratory of Resources and Environmental Information System ; State Key Laboratory of Remote Sensing Science
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/52681]
专题	中国科学院地理科学与资源研究所
通讯作者	Shi, Xun
作者单位	1.Southwest Petr Univ, Sch Geosci & Technol, Chengdu 610500, Sichuan, Peoples R China 2.Dartmouth Coll, Dept Geog, Hanover, NH 03755 USA 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Song, Chao,Shi, Xun,Bo, Yanchen,et al. Exploring spatiotemporal nonstationary effects of climate factors on hand, foot, and mouth disease using Bayesian Spatiotemporally Varying Coefficients (STVC) model in Sichuan, China[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2019,648:550-560.
APA	Song, Chao,Shi, Xun,Bo, Yanchen,Wang, Jinfeng,Wang, Yong,&Huang, Dacang.(2019).Exploring spatiotemporal nonstationary effects of climate factors on hand, foot, and mouth disease using Bayesian Spatiotemporally Varying Coefficients (STVC) model in Sichuan, China.SCIENCE OF THE TOTAL ENVIRONMENT,648,550-560.
MLA	Song, Chao,et al."Exploring spatiotemporal nonstationary effects of climate factors on hand, foot, and mouth disease using Bayesian Spatiotemporally Varying Coefficients (STVC) model in Sichuan, China".SCIENCE OF THE TOTAL ENVIRONMENT 648(2019):550-560.