山西省四城市其他感染性腹泻时空分布特征与气象因子的相关性研究
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摘要
目的探讨山西省4个主要城市的其他感染性腹泻时空分布特征及影响因素。方法运用ArcGIS10.0软件描述2008年1月1日至2013年12月31日山西省4个主要城市其他感染性腹泻的空间分布特征。采用SAS 9.2软件构建负二项回归模型分析其他感染性腹泻与气象因子的相关关系。结果 2008-2013年大同市、太原市、长治市和运城市均出现其他感染性腹泻病例,且同一城市不同区的发病数存在地区差异。其他感染性腹泻的发病有明显的季节性,7～8月发病最多,且报告病例数大多为5岁以下儿童(56.77%)。4个城市中其他感染性腹泻发病数与平均气温、平均相对湿度、日最低气温均呈正相关(P<0.05),与平均风速均呈负相关(大同市r=-0.067,P=0.005;太原市r=-0.103,P<0.01;长治市r=-0.066,P=0.006;运城市r=-0.083,P<0.01)。负二项回归模型显示:大同市、太原市、长治市、运城市分别滞后6、5、2、6d的拟和模型为最优模型。结论气象因素影响其他感染性腹泻的发病,且有滞后效应。
Objective To understand the spatial distribution characteristics of other infectious diarrhea and to explore the correlation with meterological factor in four major cities of Shanxi Province. Methods The spatial distribution characteristics of other infectious diarrhea from Jan.1, 2008 to Dec.31, 2013 in four major cities of Shanxi was described by ArcGIS 10.0 software.The negative binomial regression model was constructed by SAS 9.2 software to analyze the correlation between other infectious diarrhea and meteorological factors. Results From Jan l 2008 to Dec 31 2013, cases with other infectious diarrhea appeared in Datong, Taiyuan, Changzhi and Yuncheng, and the incidence varied in different areas of the same city.The peak season was in July and August and most cases were children under 5 years old.The incidence of other infectious diarrhea was positively correlated with average temperature, relative humidity and daily lowest temperature( P<0.05), while negatively correlated with average wind speed(r=-0.067, P=0.005; r=-0.103, P<0.01; r=-0.066, P=0.006; r=-0.083, P<0.01).The negative binomial regression model showed that the fitting model of 6, 5, 2 and 6 days behind in Datong, Taiyuan, Changzhi and Yuncheng was the optimal model. Conclusions Meteorological factors affect the incidence of other infectious diarrhea with lagging effect.
Objective To understand the spatial distribution characteristics of other infectious diarrhea and to explore the correlation with meterological factor in four major cities of Shanxi Province. Methods The spatial distribution characteristics of other infectious diarrhea from Jan.1, 2008 to Dec.31, 2013 in four major cities of Shanxi was described by ArcGIS 10.0 software.The negative binomial regression model was constructed by SAS 9.2 software to analyze the correlation between other infectious diarrhea and meteorological factors. Results From Jan l 2008 to Dec 31 2013, cases with other infectious diarrhea appeared in Datong, Taiyuan, Changzhi and Yuncheng, and the incidence varied in different areas of the same city.The peak season was in July and August and most cases were children under 5 years old.The incidence of other infectious diarrhea was positively correlated with average temperature, relative humidity and daily lowest temperature( P<0.05), while negatively correlated with average wind speed(r=-0.067, P=0.005; r=-0.103, P<0.01; r=-0.066, P=0.006; r=-0.083, P<0.01).The negative binomial regression model showed that the fitting model of 6, 5, 2 and 6 days behind in Datong, Taiyuan, Changzhi and Yuncheng was the optimal model. Conclusions Meteorological factors affect the incidence of other infectious diarrhea with lagging effect.
引文
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[2] Hay AJ,McCauley JW.The WHO global influenza surveillance and response system (GISRS)-A futureperspective[J].Influenza Other Respir Viruses,2018,12(5):551-557.
[3] Fletcher-Lartey SM,Caprarelli G.Application of GIS technology in public health:successes and challenges[J].Parasitology,2016,143(4):401-415.
[4] Waits A,Emelyanova A,Oksanen A,et al.Human infectious diseases and the changing climate in the Arctic[J].Environ Int,2018,121(Pt 1):703-713.
[5] Otmani Del Barrio M,Simard F,Caprara A.Supporting and strengthening research on urban health interventions for the prevention and control of vector-borne and other infectious diseases of poverty:scoping reviews and research gap analysis[J].Infect Dis Poverty,2018,7(1):94.
[6] Machalaba CM,Karesh WB.Emerging infectious disease risk:shared drivers with environmental change[J].Rev-Off Int Epizoot,2017,36(2):435-444.
[7] 陶燕,刘志明,米生权,等.气象因素对其他感染性腹泻病的影响[J].兰州大学学报(自然科学版),2015,5:646-651.
[8] 黎健,潘浩,肖文佳,等.上海2013-2015年感染性腹泻病原流行病学特征分析[J].中华预防医学杂志,2017,51(12):1113-1117.
[9] 张平,张静.我国2014-2015年其他感染性腹泻监测现状分析[J].中华流行病学杂志,2017,38(4):424-430.
[10] 华伟玉,赵振,李洋等.2011-2015年北京市海淀区其他感染性腹泻监测分析[J].疾病监测,2017,32(7):577-581.
[11] 李海娇,李丽丽,董瑞强,等.2006-2015年北京市房山区其他感染性腹泻流行特征 [J].职业与健康,2017,53(3):639-641.
[12] 袁月荣,蒋长征,孙灵英,等.2006-2015年宁波市江东区其他感染性腹泻病发病趋势及季节性特征分析[J].现代预防医学,2017,44(5):907-913.
[13] Zuccotti G,Meneghin F,Dilillo D,et al.Epidemiological and clinical features of rotavirus among children younger than 5 years of age hospitalized with acute gastroenteritis in Northern Italy[J].BMC Infect Dis,2010,10:218.
[14] Ma SL,Tang QL,Liu HW,et al.Correlation analysis for the attack of bacillary dysentery and meteorological factors based on the Chinese medicine theory of Yunqi and the medical-meteorological forecast model[J].Chin J Integr Med,2013,19(3):182-186.
[15] 刘重程,唐雅清,王瑞琴,等.气象因素与北京市昌平区其他感染性腹泻发病相关性研究 [J].首都公共卫生,2017,11(2):75-76.
[16] Gao L,Zhang Y,Ding G,et al.Identifying flood-related infectious diseases in Anhui Province,China:a spatial and temporal analysis[J].Am J Trop Med Hyg,2016,94(4):741-749.
[17] Yu G,Li Y,Cai J,et al.Short-term effects of meteorological factors and air pollution on childhood hand-foot-mouth disease in Guilin,China[J].Sci Total Environ,2019,646:460-470.
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