气象因素影响下中国手足口病时空演化特征研究

doi:10.12082/dqxxkx.2021.200024

地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (3): 431-442.doi: 10.12082/dqxxkx.2021.200024

• 地理空间分析综合应用 • 上一篇下一篇

气象因素影响下中国手足口病时空演化特征研究

谢玲¹^,²(), 王宏卫¹^,^*(), 刘素红¹^,³^,^*(), 高一薄¹, 玛丽亚木·玛木提¹, 伊素燕¹, 马晨¹

1.新疆大学资源与环境科学学院,乌鲁木齐 830046
2.广西师范大学环境与资源学院,桂林 541004
3.北京师范大学地理学部,北京 100875

收稿日期:2020-01-08 修回日期:2020-03-02 出版日期:2021-03-25 发布日期:2021-05-25
通讯作者: 王宏卫,刘素红 E-mail:1428375964 @qq.com;wanghw@xju.edu.cn;liush@bnu.edu.cn
作者简介:谢玲（1990- ）,新疆库尔勒人,博士生,讲师,主要从事环境健康研究。E-mail: 1428375964 @qq.com
基金资助:
国家自然科学基金项目(4186010245)

Study on Spatiotemporal Evolution of Hand, Foot and Mouth Disease（HFMD）in China under the Influence of Meteorological Factors

XIE Ling¹^,²(), WANG Hongwei¹^,^*(), LIU Suhong¹^,³^,^*(), GAO Yibo¹, Mariam Mamuti¹, YI Suyan¹, MA Chen¹

1. College of resources and environmental sciences, Xinjiang University, Urumqi 830046, China
2. College of environment and resources, Guangxi Normal University, Guilin 541004, China
3. Department of geography, Beijing Normal University, Beijing 100875, China

Received:2020-01-08 Revised:2020-03-02 Online:2021-03-25 Published:2021-05-25
Contact: WANG Hongwei,LIU Suhong E-mail:1428375964 @qq.com;wanghw@xju.edu.cn;liush@bnu.edu.cn
Supported by:
National Natural Science Foundation of China(4186010245)

摘要/Abstract

摘要：

近年来,手足口病在我国感染者的数量仍然呈现逐渐增加的趋势,对公共健康造成很大的威胁,也对疾病防控提出严峻的挑战。为探讨气象因素（气温、降水）对我国手足口病（Hand Foot and Mouth Disease, HFMD）发病的时空影响特征及规律,本文以我国手足口病疫情平发年2017年为例,利用分地区、分月份疫情数据,采用地理探测器、空间自相关等分析方法分析各地气象（气温、降水）因素对手足口病发病影响及其时空分异。结果表明：① 在时间上,2017年我国各地中心城市手足口病发病有明显的季节差异,年内有单峰发病模式和双峰（高低峰、双高峰）发病模式,且2017年2、4、12月各地中心城市手足口病发病率有显著的空间相关;② 在空间上,2017年我国各省、市手足口病发病在空间上表现为东南各省市发病率高,西北各省市发病率低的特点,并随降水量由东南向西北呈现递减趋势;③ 2017年省、自治区、直辖市和地级市手足口病爆发热点时段（4—8月）时空演化分析,先由东南各省向西北各省蔓延,后又表现为由西向东退缩;④ 2017年我国各地中心城市手足口病月发病率分别与年均降水量、年均温,呈二次函数关系（R²=0.6623）和指数函数关系（R²=0.6469）;⑤ 气温和降水对手足口病交互作用结果表现为双因子非线性增强,气温和降水的交互作用对手足口病传播的影响更为显著。气象因素对我国手足口病发病存在影响,我国手足口病发病在时间和空间上均存在显著差异,分析结果在宏观尺度上可为我国手足口病防控提供参考。

关键词: 手足口病, 降水, 气温, 地理探测器, 空间相关分析, 时空演化, 中国

Abstract:

The rising number of people infected by Hand-Foot-Mouth Disease (HFMD) in China poses a great threat to public health and a critical challenge to disease prevention and control in recent years. This paper used regional monthly statistics of HFMD in 2017 when HFMD was common in China. The GeoDetector, spatial autocorrelation, and other analysis methods were adopted to analyze the influence of meteorological factors (i.e., temperature, precipitation) on the prevalence of HFMD and its spatial and temporal differentiation. The results show that: (1) Temporally, the prevalence of HFMD had significant seasonal differences in major cities of China in 2017, with a single prevalence peak or double prevalence peaks (i.e., high-low peak, double high peak). Moreover, the prevalence of HFMD in those cities had a significant spatial correlation in February, April, and December; (2) Spatially, the HFMD in China was characterized by high prevalence level in southeast provinces or cities and low prevalence level in northwest provinces or cities, showing a decreasing trend from southeast to northwest along precipitation gradient; (3) According to the spatial and temporal distribution of HFMD outbreak period (from April to August) at provincial and city level in 2017, HFMD spread from southeast to northwest, and then retreated from west to east; (4) The prevalence of HFMD in major cities in China was correlated with the average annual precipitation and average annual temperature, which were fitted by a quadratic function (R²=0.6623) and an exponential function (R²=0.6469), respectively; and (5) The interaction effect between temperature and precipitation on HFMD resulted in a double-factor nonlinear enhancement and was more significant than a single factor during the spread of HFMD. The prevalence of HFMD in China is influenced by meteorological factors and is significantly different at spatial and temporal scales. Our results can provide reference for the prevention and control of HFMD at national level.

Key words: Hand-foot-mouth Disease, precipitation, air remperature, GeoDetector, spatial correlation analysis, spatio-temporal evolution, China

谢玲, 王宏卫, 刘素红, 高一薄, 玛丽亚木·玛木提, 伊素燕, 马晨. 气象因素影响下中国手足口病时空演化特征研究[J]. 地球信息科学学报, 2021, 23(3): 431-442.DOI:10.12082/dqxxkx.2021.200024

XIE Ling, WANG Hongwei, LIU Suhong, GAO Yibo, Mariam Mamuti, YI Suyan, MA Chen. Study on Spatiotemporal Evolution of Hand, Foot and Mouth Disease（HFMD）in China under the Influence of Meteorological Factors[J]. Journal of Geo-information Science, 2021, 23(3): 431-442.DOI:10.12082/dqxxkx.2021.200024

图/表 11

表1

图1

表2

表3

图2

图3

图4

表4

图5

表5

图6

参考文献 2

[1]	吴北平, 杨典, 王劲峰, 等. 利用贝叶斯时空模型分析山东省手足口病时空变化及影响因素[J]. 地球信息科学学报, 2016,18(12):1645-1652.
	[ Wu B P, Yang D, Wang J F, et al. Space-time variability and determinants of Hand, foot and mouth in Shandong province: A Bayesian Spatio-temporal Modeling approach[J]. Journal of Geo-information Science, 2016,18(12):1645-1652. ]
[6]	Munderloh U G, B. I. Kim, H. Ki, et al. Effect of climatic factors on hand, foot, and mouth disease in South Korea, 2010-2013[J]. Plos One, 2016,11(6):e0157500. pmid: 27285850
[7]	Samphutthanon R, Tripathi NK, Ninsawat S, et al. Spatio-temporal distribution and hotspots of hand, foot and mouth disease (HFMD) in northern Thailand[J]. International Journal Environmental Research Public Health, 2014,11(1):312-336.
[8]	Nguyen H X, Chu C, Tran Q D, et al. Temporal relationships between climate variables andHand, Foot and Mouth Disease: A multi-province study in the Mekong Delta Region, Vietnam[J]. International Journal of Biometeorology, 2019,3(21):1156-1169.
[9]	NikNadia N, Sam I C, Rampal S, et al. Cyclical patterns of hand, foot and mouth disease caused by enterovirus A7 in Malaysia[J]. PLoS Neglected Tropical Disease, 2016,10:e0004562.
[10]	Yien L H, Joacim R. Nawi Ng Short term effects of Weather on Hand, Foot and Mouth Disease[J]. PLoS One, 2011,6(2):e16796 doi: 10.1371/journal.pone.0016796 pmid: 21347303
[11]	丘文洋, 李连发, 张杰昊, 等. 利用空间聚集的贝叶斯网络评估手足口病发病风险[J]. 地球信息科学学报, 2017,19(8):1036-1048.
	[ Qiu W Y, Li L F, Zhang J H, et al. A Bayesian Network Method considering spatial cluster to evaluate health risk of Hand, Foot and Mouth Disease[J]. Journal of Geo-information Science, 2017,19(8):1036-1048. ]
[12]	Levins S, Measroch V, Pech W, et al. Hand-foot-and-mouth disease[J]. South African Medical Journal, 1962,36:502-504
[13]	Seddon J H, Duff M F. Hand, Foot and Mouth Disease: Coxsackie virus types A 5, A 10, and A 16 infections[J]. The New Zealand Medical Journal, 1971,74(475):368-373. pmid: 5291880
[14]	许一玲, 李栋. 淄博市张店区手足口病流行与气象因素的关系研究[J]. 热带医学杂志, 2010,10(10):1237-1239.
	[ Xu Y L, Li D, et al. Relationship between climatic factors and HFMD in Zhangdian District of Zibo[J]. Journal of Tropical Medicine, 2010,10(10):1237-1239. ]
[15]	Xu Z C, Hu W Q, Jiao K D, et al. The effect of temperature on childhood Hand, Foot and Mouth Disease in Guangdong Province, China, 2010-2013: A multicity study[J]. BMC Infectious Diseases , 2019,19(1):969-979. pmid: 31718560
[16]	Zhang Q, Zhou M M, Yang Y W, et al. Short-term effects of extreme meteorological factors on childhood hand, foot, and mouth disease reinfection in Hefei, China: A distributed lag non-linear analysis[J]. Science of the Total Environment, 2019,653:839-848
[17]	Xu C D, Zhang X X, Xiao G X. Spatiotemporal decomposition and risk determinants of Hand, Foot and Mouth Disease in Henan, China[J]. Science of the Total Environment, 2019,657:509-516.
[18]	Phung D, Nguyen H X, Nguyen H L T, et al. Spatiotemporal variation of Hand, Foot and Mouth Disease in relation to socio-ecological factors: A multiple-province analysis in Vietnam[J]. Science of the Total Environment, 2018,610-611:983-991.
[19]	Fu T, Chen T, Dong Z B, et al. Development and comparison of forecast models of Hand, Foot and Mouth Disease with meteorological factors[J]. Scientific Reports, 2019,9(1):15691-15706. doi: 10.1038/s41598-019-52044-5 pmid: 31666565
[23]	张湘雪, 王丽, 尹礼唱, 等. 京津唐地区HFMD时空变异分析与影响因子探测[J]. 地球信息科学学报, 2019,21(3):398-406.
	[ Zhang X X, Wang L, Yin L C, et al. Spatiotemporal variation analysis and risk determinants of Hand, Foot and Mouth Disease in Beijing-Tianjin-Tangshan, China[J]. Journal of Geo-information Science, 2019,21(3):398-406. ]
[24]	公共卫生科学数据中心. 全国分地区手足口病全年统计数据[DB/OL]. http://www.phsciencedata.cn.
	[ Public Health Science Data Center. The annual statistics of hand, foot and mouth disease in different regions of China [DB/OL]. http://www.phsciencedata.cn]
[25]	国家气象信息中心. 中国地面气候资料日值数据集[DB/OL]. http://data.cma.cn.
	[ National Meteorological Information Center. Daily data sets of Chinese surface climatological data[DB/OL]. http://data.cma.cn]
[26]	徐慧, 汪权方, 李家永, 等. 1980年以来中国大宗作物空间格局变化分析[J]. 长江流域资源与环境, 2017,26(1):55-66.
	[ Xu H, Wang Q F, Li J Y, et al. Variation of staple crops' spatial pattern in China since 1980a[J]. Resources and Environment in the Yangtze Basin, 2017,26(1):55-66. ]
[27]	马慧强, 廉倩文, 论宇超, 等. 基于BP 神经网络的旅游经济系统脆弱性省际空间分异[J]. 资源科学, 2019,41(12):2248-2261.
	[ Ma H Q, Lian Q W, Lun Y C, et al. Spatial differentiation of tourism economic system vulnerability based on BP neural network in different provinces of China[J]. Resources Science, 2019,41(12):2248-2261. ]
[28]	牛丽楠, 邵全琴, 刘国波, 等. 六盘水市土壤侵蚀时空特征及影响因素分析[J]. 地球信息科学学报, 2019,21(11):755-1767.
[31]	[ Sun H Q, Xiao G X, Guo Y, et al. Spatial clustering and changing trend of hepatitis C prevalence during 2008-2012 in China[J]. Chinese Journal of Public Health, 2014,30(3):286-289. ]
[32]	Wang J F, Hu Y. Environmental health risk detection with GeoDetector[J]. Environmental Modelling & Software, 2012,33(1):14-15.
[33]	李媛媛, 徐成东, 肖革新. 京津唐地区细菌性痢疾社会经济影响时空分析[J]. 地球信息科学学报, 2016,18(12):1615-1623.
	[ Li Y Y, Xu C D, Xiao G X. Spatial-temporal analysis of social-economic factors of bacillary dysentery in Beijing-Tianjin-Tang[J]. Journal of Geo-information Science, 2016,18(12):1615-1623. ]
[34]	魏建军, 曹磊, 陈飒, 等. 2014—2017年陕西汉中市气象因素对手足口病的发病影响[J]. 公共卫生与预防学, 2019,30(3):25-29.
	[ Wei J J, Cao L, Chen S, et al. Influence of meteorological factors on the incidence of Hand, Foot and Mouth Disease in Hanzhong city 2014-2017[J]. Journal of Public Health and Preventive Medicine, 2019,30(3):25-29. ]
[35]	杜志成, 张王剑, 郝元涛. 中国大陆气象因素与手足口病发病相关关系的meta分析[J]. 中国卫生统计, 2016,33(5):803-805, 808.
	[ Du Z C, Zhang W J, Hao Y T. Meta-analysis of the relationship between meteorological factors and the incidence of Hand, Foot and Mouth Disease in mainland China[J]. Chinese Journal of Health Statistics, 2016,33(5):803-805,808. ]
[36]	李洁, 朱麟, 姜宝法, 等. 济南市手足口病与极端降水事件的关系研究[J]. 环境与健康杂志, 2015,32(4):311-314.
	[ Li H, Zhu L, Jiang B F, et al. Association between incidence of hand, foot and mouth disease and extreme precipitation events in Jinan[J]. Journal of Environment and Health, 2015,32(4):311-314. ]
[31]	孙海泉, 肖革新, 郭莹, 等. 中国2008—2012年丙肝流行规律及空间聚集性分析[J]. 中国公共卫生, 2014,30(3):286-289.
[30]	Wang J F, Xu C D. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017,72(1):116-134.
[29]	Wang J F, Li X H, Christakos G, et al. Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region, China[J]. International Journal of Geographical Information Science, 2010,24(1):107-127.
[28]	[ Niu L N, Shao Q Q, Liu G B, et al. Analysis on spatiotemporal characteristics and effects of soil erosion in Liupanshui City[J]. Journal of Geo-information Science, 2019,21(11):1755-1767. ]
[22]	[ Bie Q Q, Qiu D S, Hu H, et al. Spatial and temporal distribution characteristics of Hand-Foot-Mouth Disease in China[J]. Journal of Geo-information Science, 2010,12(3):380-384. ]
	别芹芹, 邱冬生, 胡辉, 等. 我国手足口病时空分布特征的GIS分析[J]. 地球信息科学学报, 2010,12(3):380-384.
[21]	Liao J Z, Qin Z, Zuo Z, et al. Spatial-temporal mapping of hand foot and mouth disease and the long-term effects associated with climate and socio-economic variables in Sichuan Province, China from 2009 to 2013[J]. Science of the Total Environment, 2019,563-564:152-159.
[20]	Liu H, Song G X, He N, et al. Spatial-temporal variation and risk factor analysis of hand, foot, and mouth disease in children under 5 years old in Guangxi, China[J]. BMC Public Health, 2019,19(1):1491-1503. pmid: 31703735
[5]	Onouzuka D, Hashizume M. The influence of temperature and humidity on the incidence of Hand, Foot and Mouth Disease in Japan[J]. Science of the Total Environment, 2011,410-411:119-125.
[4]	Chan T C, Hwang J S, Chen R H, et al. Spatio-temporal analysis on enterovirus cases through integrated surveillance in Taiwan[J]. BMC Public Health, 2014,14(1):11-20.
[3]	Ma E, Lam T, Wong C, et al. Is Hand, Foot and Mouth Disease associated with meteorological parameters[J]. Epidemiol Infectious, 2010,138(9):1779-1788.
[2]	Zhao J, Jiang F, Zhong L, et al. Age patterns and transmission characteristics of Hand, Foot and Mouth Disease in China[J]. BMC Infectious Diseases, 2016,16(11):691-689.

年份	2009	2010	2011	2012	2013	2014	2015	2016	2017
发病数/人	1 155 525	1 774 669	1 619 706	2 168 737	1 828 377	2 778 861	1 997 371	2 442 138	1 929 550
发病率/1/10⁴	87.0111	132.9599	120.7916	160.9632	135.0312	205.0565	146.5996	178.1562	139.8388

类型	交互作用	图示
q(X₁,X₂)<Min(q(X₁),q(X₂))	非线性减弱
Min(q(X₁),q(X₂))<q(X₁,X₂)<Max(q(X₁)),q(X₂))	单因子非线性减弱
q(X₁,X₂)> Max(q(X₁),q(X₂))	双因子增强
q(X₁,X₂)=q(X₁)+q(X₂)	独立
q(X₁,X₂)>q(X₁)+q(X₂)	非线性增强

	发病率	月均降水量	月均温
发病率 Pearson相关性	1	0.588^**	0.562^**
月均降水量 Pearson相关性	0.588^**	1	0.882^**
月均温 Pearson相关性	0.560^**	0.882^**	1

	降水	气温
q	0.6051	0.5519
p	0.0401	0.0448

气象因素影响下中国手足口病时空演化特征研究

Study on Spatiotemporal Evolution of Hand, Foot and Mouth Disease（HFMD）in China under the Influence of Meteorological Factors

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 2

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	张泽, 胡宝清, 丘海红, 邓雁菲. 桂西南喀斯特-北部湾海岸带生态环境脆弱性时空分异与驱动机制研究[J]. 地球信息科学学报, 2021, 23(3): 456-466.
[2]	郭紫甜, 王春梅, 刘欣, 庞国伟, 朱梦阳, 王晋卿. 基于小流域抽样单元的中国FROM-GLC30数据精度评价[J]. 地球信息科学学报, 2021, 23(3): 524-535.
[3]	金鑫, 金彦香. TRMM及GPM降水数据在高寒内陆河流域的准确性评估[J]. 地球信息科学学报, 2021, 23(3): 395-404.
[4]	蔡一乐, 曹诗颂, 杜明义, 李善飞, 陈姗姗. 中国地级市人为热总量的估算及驱动因素分析[J]. 地球信息科学学报, 2021, 23(3): 405-418.
[5]	李颉, 郑步云, 王劲峰. 2008—2018年中国手足口病时空分异特征[J]. 地球信息科学学报, 2021, 23(3): 419-430.
[6]	薛浩男, 张雪英, 吴明光, 曹天阳. 基于新闻数据的新冠疫情事件下“全球-中国”国际关系变化分析方法[J]. 地球信息科学学报, 2021, 23(2): 351-363.
[7]	高楹, 宋辞, 郭思慧, 裴韬. 接驳地铁站的共享单车源汇时空特征及其影响因素[J]. 地球信息科学学报, 2021, 23(1): 155-170.
[8]	张小东, 韩昊英, 陈宇. 2003—2018年中国地级城市土地出让交易状况及时空动态特征[J]. 地球信息科学学报, 2020, 22(9): 1823-1836.
[9]	刘新, 赵宁, 郭金运, 郭斌. 基于LSTM神经网络的青藏高原月降水量预测[J]. 地球信息科学学报, 2020, 22(8): 1617-1629.
[10]	宋荣, 胡业翠. 中国城市土地整治综合潜力分区与提升路径[J]. 地球信息科学学报, 2020, 22(7): 1522-1531.
[11]	朱伶俐, 任红艳, 丁凤, 鲁亮, 吴思佳, 崔成. 陕西省HFRS疫情时空分异特征及影响要素研究[J]. 地球信息科学学报, 2020, 22(5): 1142-1152.
[12]	刘纪远, 张增祥, 张树文, 颜长珍, 吴世新, 李仁东, 匡文慧, 史文娇, 黄麟, 宁佳, 董金玮. 中国土地利用变化遥感研究的回顾与展望——基于陈述彭学术思想的引领[J]. 地球信息科学学报, 2020, 22(4): 680-687.
[13]	杨艳昭, 郎婷婷, 张超, 贾琨. 基于GIS的“一带一路”地区气温插值方法比较研究[J]. 地球信息科学学报, 2020, 22(4): 867-876.
[14]	何飞, 刘兆飞, 姚治君. Jason-2测高卫星对湖泊水位的监测精度评价[J]. 地球信息科学学报, 2020, 22(3): 494-504.
[15]	张永树, 杨振凯, 訾璐, 曹一冰, 余航. 中国艾滋病空间格局和时空演化分析[J]. 地球信息科学学报, 2020, 22(2): 198-206.