河南省流行性乙型脑炎时空分布特征及影响因素研究

Analysis on spatiotemporal patterns and driving factors of Japanese encephalitis in Henan province

目的分析河南省2006-2010年流行性乙型脑炎(乙脑)时空分布特征,研究地理环境因子对乙脑发病情况的影响。方法对2006-2010年河南省乙脑发病数据分市县进行流行病学及空间自相关分析,利用相关分析及多元线性回归研究气象因子、地表因子、社会经济条件等地理环境因素对乙脑发病的影响。结果河南省5年共报告2 729例,年平均发病率为0.547 4/10万,死亡119例,平均病死率为4.36%。年内7-9月发病集中,占全年发病数的97.08%,年际变化呈"U"形。疾病发病"热点"呈现明显的西南多、东北少的空间分布特征,洛阳、南阳、信阳3市发病热点现象显著。气象因子中,降雨量、降雨日数、>80%湿度天数及>25℃积温与发病率正向作用显著,而>30℃温度的累积天数、最高温度>30℃的累积温度将有效降低乙脑发病;地表因子中,省内水网密度低、耕地面积高的地方易致乙脑发病,两者与发病率在置信度为99%水平均呈显著相关;社会经济类因子中,农民人均收入的提升可有效降低疾病暴发,医疗卫生从业人数增加可降低乙脑暴发的可能性。多元线性回归拟合地理环境因素对疾病发病率影响,预测模型中R2=0.643,调整后R2=0.414,拟合效果良好。结论河南省西南地区属于乙脑防控重点区域,关注地理环境因素的动态变化对乙脑防控有前瞻性作用。

Objective This paper was intended to analyze the spatiotemporal patterns of the Japanese encephalitis （JE） in Henan province from 2006 to 2010, and explore the connection between JE incidence and the geographical environmental driving factors. Methods The JE incidence from 2006 to 2010 in Henan was analyzed with epidemiological research, spatial autocorrelation, and correlation method. The multiple linear regression model was also built to identify the impact of meteorological, surficial and socio-economic factors on JE. Results The total number of JE case is 2 729 with yearly incidence of 0.547 4 per 100 thousand people and the overall death case was 119 with mortality rate of 4.36%. The incidence outbreak from July to September, accounting for 97.08% of the whole year cases and the annual incidence declined in 2008 and then fluctuated until 2010. JE cases were mainly concentrated in the southwest area, and ＂hot spots＂ agglomeration was significant in Luoyang, Nanyang, and northern Xinyang city. In terms of the meteorological driving factors, rainfall, the number of rainy days, 〉80% humidity days and 〉25℃ cumulated temperature promoted the outbreak of JE, while 〉30℃ cumulated days and the maximum above 30℃ cumulated temperature would reduce the incidence. For the surficial factors, watershed density and cultivated area illustrated the significant correlation with incidence of 99% confidence. With the increase of income per capita in farmers and total number of health technical staff, the possibility of an outbreak of JE also decreased. The overall predicted R^2 of regression model was 0.643 with the adjusted R^2 of 0.414. Conclusion The southwest area in Henan province is the key area for JE management. Research on the geographical driving factors of JE disease, will have a significant effect on the prevention and control of JE incidence.