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山东大学学报 (医学版) ›› 2018, Vol. 56 ›› Issue (8): 114-120.doi: 10.6040/j.issn.1671-7554.0.2018.459

• • 上一篇    

威海市发热伴血小板减少综合征与气象因素关系

王旭1,张丹丹1,郑兆磊1,王珮竹1,许勤勤1,王显军2,丁淑军2,李秀君1,3   

  1. 1.山东大学公共卫生学院生物统计学系, 山东 济南 250012;2.山东省疾病预防控制中心, 山东 济南 250014;3.山东大学气候变化与健康研究中心, 山东 济南 250012
  • 发布日期:2022-09-27
  • 通讯作者: 李秀君. E-mail:xjli@sdu.edu.cn丁淑军. E-mail:dsj_jn@126.com
  • 基金资助:
    国家自然科学基金(81673238);山东省自然科学基金(ZR2016HM75);山东省自然科学基金(ZR2014HP030)

Relationship between severe fever with thrombocytopenia syndrome and meteorological factors in Weihai City

WANG Xu1, ZHANG Dandan1, Zheng Zhaolei1, WANG Peizhu1, XU Qinqin1, WANG Xianjun2, DING Shujun2, LI Xiujun1,3   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Shandong Provincial Center for Disease Control and Prevention, Jinan 250014, Shandong, China;
    3. Shandong University Climate Change and Health Center, Jinan 250012, Shandong, China
  • Published:2022-09-27

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摘要： 目的 探讨威海市发热伴血小板减少综合征(SFTS)与气象因素的关系。 方法 对威海市2011~2015年SFTS发病情况和气象因素进行统计描述,将有SFTS病例的月定义为病例月,无SFTS病例的月定义为非病例月;对比分析病例月和非病例月的气象因素之间是否存在差异;建立决策树对气象因素变量进行二元分离后纳入负二项回归模型,对模型进行诊断,拟合最优模型,分析气象因素对SFTS的影响。 结果 威海市SFTS发病存在明显的季节趋势,每年5~10月为发病高峰期;病例月与非病例月的气象因素除月平均日照时数外,气温、风速等其他气象因素均有差异;月平均气温高于14 ℃时,SFTS的发病率升高(RR=3.41, 95%CI: 1.12~10.89);月平均风速高于5.8 m/s时,SFTS的发病率降低(RR=0.62, 95%CI: 0.39~0.96)。 结论 月平均气温高于14 ℃可能是SFTS的危险因素,月平均风速高于5.8 m/s可能是疾病的保护因素。

关键词: 发热伴血小板减少综合征, 气象因素, 负二项回归, 蜱虫, 危险因素

Abstract: Objective To explore the relationship between severe fever with thrombocytopenia syndrome(SFTS)and meteorological factors in Weihai City. Methods The incidence of SFTS and the meteorological factors in Weihai City from 2011 to 2015 were statistically interpreted. The months in which SFTS occurred were defined as the case months, and the months without SFTS occurrence were the non-case months. The case months and non-cases months were compared to analyze the differences in meteorological factors. Decision tree was established to classify the meteorological factors, which were then fit into negative binomial regression. The variables were diagnosed to select the optimal model. After that, the impacts of meteorological factors on SFTS were analyzed. Results There was a clear seasonal trend in the incidence of SFTS in Weihai City, and May to October was the peak of onset of the disease. The comparative analysis showed that there were differences in meteorological factors between the case months and non-case months except for average monthly sunshine duration. When the average monthly temperature was higher than 14 ℃, the incidence of SFTS increased(RR=3.41, 95%CI: 1.12-10.89). When the average monthly wind speed was faster than 5.8 m/s, 山 东 大 学 学 报 (医 学 版)56卷8期 -王旭,等.威海市发热伴血小板减少综合征与气象因素关系 \=-the incidence of SFTS decreased(RR=0.62, 95%CI: 0.39-0.96). Conclusion The average monthly temperature above 14 ℃ may be a risk factor for SFTS, while the average monthly wind speed above 5.8 m/s may be a protective factor for the disease.

Key words: Severe fever with thrombocytopenia syndrome, Meteorological factors, Negative binomial regression, Tick, Risk factor

中图分类号: 

  • R384
[1] 尤爱国, 杨建华, 唐晓燕, 等. 新布尼亚病毒感染致发热伴血小板减少综合征的危险因素分析[J]. 中国人兽共患病学报, 2015, 31(8): 704-708. YOU Aiguo, YANG Jianhua, TANG Xiaoyan, et al. Risk factors of sever fever with thrombocytopenia syndrome(SFTS)infected by SFTSV[J]. China Journal of zoonoses, 2015, 31(8): 704-708.
[2] Yu XJ, Liang MF, Zhang SY, et al. Fever with thrombocytopenia associated with a novel bunyavirus in China[J]. N Engl J Med, 2011, 364(16): 1523-1532.
[3] 张永振, 周敦金, 熊衍文, 等. 中国淮阳山地区由新蜱传布尼亚病毒引起的出血热[J]. 中华流行病学杂志, 2011, 32(3): 209-220. ZHANG Yongzhen, ZHOU Dunjin, XIONG Yinwen, et al. Hemorrhagic fever caused by a novel tick-borne Bunyavirus in Huaiyangshan, China[J]. Chinese Journal of Epidemiology, 2011, 32(3): 209-220.
[4] 姜晓林, 王显军, 李建东, 等. 家养动物体表蜱中发热伴血小板减少综合征布尼亚病毒分离及鉴定[J]. 病毒学报, 2012, 28(3): 252-257. JIANG Xiaolin, WANG Xianjun, LI Jiandong, et al. Isolation and identification of bunyavirus with fever syndrome and thrombocytopenia in domestic animals[J]. Chinese Journal of Virology, 2012, 28(3): 252-257.
[5] 刘芸, 张洁, 王博, 等. 辽宁省新布尼亚病毒流行特点及生物特性分析[J]. 中国公共卫生, 2013, 29(5): 721-723. LIU Yun, ZHANG Jie, WANG Bo, et al. Epidemic characteristics and biological features of severe fever with thrombocytopenia syndrome bunyavirus(SFTSV)found in Liaoning province[J]. Chinese Journal of Public Health, 2013, 29(5): 721-723.
[6] Li H, Zhou Y, Wang W, et al. The clinical characteristics and outcomes of patients with human granulocytic anaplasmosis in China[J]. Int J Infect Dis, 2011,15(12): 859-866.
[7] Liu Q, He B, Huang S Y, et al. Severe fever with thrombocytopenia syndrome, an emerging tick-borne zoonosis[J]. Lancet Infect Dis, 2014,14(8): 763-772.
[8] 刘昆. 发热伴血小板减少综合征流行病学特征和传播风险预测研究[D]. 北京: 中国人民解放军军事医学科学院, 2015.
[9] Torina A, Blanda V, Blanda M, et al. A geographical information system based approach for integrated strategies of tick surveillance and control in the Peri-Urban natural reserve of monte pellegrino(Palermo, Southern Italy)[J]. Int J Environ Res Public Health, 2018, 15(3). doi: 10.3390/ijerph15030404.
[10] Cat J, Beugnet F, Hoch T, et al. Influence of the spatial heterogeneity in tick abundance in the modeling of the seasonal activity of Ixodes ricinus nymphs in Western Europe[J]. Exp Appl Acarol, 2017, 71(2): 115-130.
[11] 尤爱国,康锴,王海峰,等. 气象因素与发热伴血小板减少综合征发病关系的生态学研究[J]. 中国人兽共患病学报, 2012, 28(9): 898-901. You AG, Kang K, Wang HF, et al. Ecological study on the relationship between meteorological factors and incidence of fever, thrombocytopenia and leukopenia syndrome(FTLS)[J]. Chinese Journal of Zoonoses, 2012, 28(9): 898-901.
[12] Xu B, Liu L, Huang X, et al. Metagenomic analysis of fever, thrombocytopenia and leukopenia syndrome(FTLS)in Henan Province, China: discovery of a new bunyavirus[J]. PLoS Pathog, 2011, 7(11): e1002369. doi: 10.1371/journal.ppat.1002369.
[13] 臧攀, 鲍倡俊. 发热伴血小板减少综合征病原学与流行病学研究进展[J]. 江苏预防医学, 2017, 28(2): 176-178. ZANG Pan, BAO Changjun. Fever with thrombocytopenia syndrome etiology and epidemiology research progress[J]. Jiangsu Journal of preventive medicine, 2017, 28(2): 176-178.
[14] Takahashi T, Maeda K, Suzuki T, et al. The first identification and retrospective study of Severe Fever with Thrombocytopenia Syndrome in Japan[J]. J Infect Dis, 2014, 209(6): 816.
[15] Yoo SJ, Sang TH, Lee KH. Severe fever with thrombocytopenia syndrome[J]. Korean J Crit Care Med, 2014, 29(2): 59.
[16] Ding F, Zhang W, Wang L, et al. Epidemiologic features of severe fever with thrombocytopenia syndrome in China, 2011-2012[J]. Clin Infect Dis, 2013, 56(11): 1682-1683.
[17] Liu Q, He B, Huang SY, et al. Severe fever with thrombocytopenia syndrome, an emerging tick-borne zoonosis[J]. Lancet Infect Dis, 2014, 14(8): 763-772.
[18] Kim KH, Yi J, Kim G, et al. Severe fever with thrombocytopenia syndrome, South Korea, 2012[J]. Emerg Infect Dis, 2013, 19(11): 1892.
[19] Yun SM, Lee WG, Ryou J, et al. Severe fever with thrombocytopenia syndrome virus in ticks collected from humans, South Korea, 2013[J]. Emerg Infect Dis, 2014, 20(8): 1358.
[20] Lafferty KD. The ecology of climate change and infectious diseases[J]. Ecology, 2009, 90(4): 888-900.
[21] Kaizer AM, Foré SA, Kim HJ, et al. Modeling the biotic and abiotic factors that describe the number of active off-host Amblyomma americanum larvae[J]. J Vector Ecol, 2015, 40(1): 1-10.
[22] Li S, Heyman P, Cochez C, et al. A multi-level analysis of the relationship between environmental factors and questing Ixodes ricinus dynamics in Belgium[J]. Parasit Vectors, 2012, 5(1): 1-11.
[23] Wang C, Jiang B, Fan J, et al. A study of the dengue epidemic and meteorological factors in Guangzhou, China, by using a zero-inflated Poisson regression model[J]. Asia Pac J Public Health, 2014, 26(1): 48-57.
[24] Xu L, Stige LC, Chan KS, et al. Climate variation drives dengue dynamics[J]. Proc Natl Acad Sci USA, 2017, 114(1): 113.
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