globalchange  > 过去全球变化的重建
DOI: 10.1371/journal.pone.0117296
论文题名:
Time Series Analyses of Hand, Foot and Mouth Disease Integrating Weather Variables
作者: Yuanbin Song; Fan Wang; Bin Wang; Shaohua Tao; Huiping Zhang; Sai Liu; Oscar Ramirez; Qiyi Zeng
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2015
发表日期: 2015-3-2
卷: 10, 期:3
语种: 英语
英文关键词: Inpatients ; Hand ; foot and mouth disease ; Outpatients ; Meteorology ; Forecasting ; Humidity ; Seasons ; Weather
英文摘要: Background The past decade witnessed an increment in the incidence of hand foot mouth disease (HFMD) in the Pacific Asian region; specifically, in Guangzhou China. This emphasized the requirement of an early warning system designed to allow the medical community to better prepare for outbreaks and thus minimize the number of fatalities. Methods Samples from 1,556 inpatients (hospitalized) and 11,004 outpatients (non-admitted) diagnosed with HFMD were collected in this study from January 2009 to October 2013. Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied to establish high predictive model for inpatients and outpatient as well as three viral serotypes (EV71, Pan-EV and CA16). To integrate climate variables in the data analyses, data from eight climate variables were simultaneously obtained during this period. Significant climate variable identified by correlation analyses was executed to improve time series modeling as external repressors. Results Among inpatients with HFMD, 248 (15.9%) were affected by EV71, 137 (8.8%) were affected by Pan-EV+, and 436 (28.0%) were affected by CA16. Optimal Univariate SARIMA model was identified: (2,0,3)(1,0,0)52 for inpatients, (0,1,0)(0,0,2)52 for outpatients as well as three serotypes (EV71, (1,0,1)(0,0,1)52; CA16, (1,0,1)(0,0,0)52; Pan-EV, (1,0,1)(0,0,0)52). Using climate as our independent variable, precipitation (PP) was first identified to be associated with inpatients (r = 0.211, P = 0.001), CA16-serotype (r = 0.171, P = 0.007) and outpatients (r = 0.214, P = 0.01) in partial correlation analyses, and was then shown a significant lag in cross-autocorrelation analyses. However, inclusion of PP [lag -3 week] as external repressor showed a moderate impact on the predictive performance of the SARIMA model described here-in. Conclusion Climate patterns and HFMD incidences have been shown to be strongly correlated. The SARIMA model developed here can be a helpful tool in developing an early warning system for HFMD.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0117296&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/20254
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Pediatric Center of Zhujiang Hospital, Southern Medical University, Guangzhou, China;Dept. of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, United States of America;Pediatric Center of Zhujiang Hospital, Southern Medical University, Guangzhou, China;Pediatric Center of Zhujiang Hospital, Southern Medical University, Guangzhou, China;Dept. of Psychiatry, Yale University School of Medicine, New Haven, CT, United States of America;Dept. of Psychology, Yale University, New Haven, CT, United States of America;Yale Cancer Center, Yale University School of Medicine, New Haven, CT, United States of America;Pediatric Center of Zhujiang Hospital, Southern Medical University, Guangzhou, China

Recommended Citation:
Yuanbin Song,Fan Wang,Bin Wang,et al. Time Series Analyses of Hand, Foot and Mouth Disease Integrating Weather Variables[J]. PLOS ONE,2015-01-01,10(3)
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