热带病与寄生虫学 ›› 2024, Vol. 22 ›› Issue (3): 177-182.doi: 10.3969/j.issn.1672-2302.2024.03.009

• 防治研究 • 上一篇    下一篇

基于分布滞后非线性模型分析巢湖市发热伴血小板减少综合征与气象因素的关系

柳坤鹏1,2(), 朱启星1()   

  1. 1.安徽医科大学公共卫生学院,安徽合肥 230032
    2.巢湖市疾病预防控制中心
  • 收稿日期:2024-01-17 出版日期:2024-06-20 发布日期:2024-06-28
  • 通信作者: 朱启星,E-mail: zqxing@yeah.net
  • 作者简介:柳坤鹏,男,硕士在读,研究方向:虫媒传染病控制。E-mail: 522472136@qq.com

Analysis on the relationship between severe fever with thrombocytopenia syndrome and meteorological factors in Chaohu City based on distributed lag non-linear model

LIU Kunpeng1,2(), ZHU Qixing1()   

  1. 1. School of Public Health, Anhui Medical University, Hefei 230032, Anhui Province, China
    2. Chaohu Center for Disease Control and Prevention
  • Received:2024-01-17 Online:2024-06-20 Published:2024-06-28
  • Contact: ZHU Qixing, E-mail: zqxing@yeah.net

摘要:

目的 研究巢湖市发热伴血小板减少综合征(severe fever with thrombocytopenia syndrome, SFTS)与气象因素的关系,为SFTS的防控提供科学依据。方法 通过中国疾病预防控制信息系统收集巢湖市2013—2022年每日SFTS发病资料,通过中国科学院资源环境科学数据中心收集同期气象资料。以周平均气温中位数(17.4 ℃)、周平均气压中位数(1 012.8 hPa)、周日照时数中位数(33.4 h)和周降水量最小值(0 mm)作为参考值,利用分布滞后非线性模型(distributed lag non-linear model, DLNM)分析SFTS周病例数和周气象因素的关系。结果 2013—2022年巢湖市共报告SFTS病例231例,年发病率为0.63/10万~5.78/10万,年均发病率2.93/10万,年发病率总体呈上升趋势(Z=3.04,P<0.01)。男性和女性报告病例数分别为113例和118例,年均发病率分别为2.90/10万和2.97/10万;各年龄组中≥60岁人群的报告病例数和发病率均最高(175例,10.54/10万)。SFTS周发病风险对周平均气温、周平均气压、周日照时数的响应曲线近似倒“V”型,对周降水量的响应曲线近似半“U”型。周平均气温为22.4 ℃时,SFTS发病累积相对危险度(cumulative relative risk, CRR)最大[CRR=9.210,95%CI:(0.832,118.353)];周平均气温在17.5~21.8 ℃时,SFTS发病风险升高(P<0.05)。周平均气压为1 015.5 hPa时,SFTS发病的CRR最大[CRR=1.877,95%CI:(0.649,5.435)],周平均气压在998.7~1 012.7 hPa和1 022.1~1 031.5 hPa时SFTS发病风险降低(P<0.05)。周日照时数为31.0 h时,SFTS发病的CRR最大[CRR=1.024,95%CI:(0.882,1.188)],在周日照时数>39.3 h时,SFTS发病风险降低(P<0.05);周降雨量越大,SFTS发病风险越大(P<0.05)。结论 SFTS发病和气象因素呈现非线性关系,适宜的温度、丰沛的降雨量会增加SFTS的发生风险,较高的气压和日照时数可以降低SFTS的发生风险。

关键词: 发热伴血小板减少综合征, 气象因素, 分布滞后非线性模型, 巢湖市

Abstract:

Objective To investigate the relationship between severe fever with thrombocytopenia syndrome (SFTS) and meteorological factors in Chaohu City for scientific basis for prevention and control of SFTS. Methods Daily cases of SFTS in Chaohu area from 2013 to 2022 were retrieved from the China Information System for Disease Control and Prevention, and meteorological data during the same period were obtained through the Resources and Environmental Science Data Platform. The reference values were set based on the median of weekly average temperature (17.4℃), weekly average pressure (1 012.8 hPa), weekly sunshine duration (33.4 h) and the minimum weekly precipitation (0 mm). Then the distributed lag non-linear model (DLNM) was used to analyze the relationship between weekly SFTS cases and meteorological factors. Results In total, 231 cases of SFTS were reported in Chaohu area from 2013 through 2022. The annual incidence ranged from 0.63 per 100 000 to 5.78 per 100 000 population, with an average annual incidence at 2.93 per 100 000, and the overall trend of the annual incidence was on the rise (Z=3.04, P<0.01). Of the reported cases, 113 were males and 118 females, with average annual incidence being 2.90 per 100 000 and 2.97 per 100 000, respectively. By age group, the reported cases and incidence were the highest in population aged ≥60 years (175 cases, 10.54 per 100 000). The response curve of weekly SFTS incidence risk to weekly average temperature, weekly average pressure and sunshine duration was almost in inverted V-shape, and the response curve to weekly precipitation approximately presented half U-shape. The cumulative relative risk (CRR) of SFTS was the highest when the weekly average temperature was 22.4 ℃ [CRR=9.210, 95%CI: (0.832, 118.353)], and the risk of SFTS was increased when the weekly average temperature was 17.5-21.8 ℃ (P<0.05). When the weekly average pressure was 1 015.5 hPa, the CRR of SFTS was the highest [CRR=1.877, 95%CI: (0.649, 5.435)]. The risk of SFTS was decreased when weekly average pressure was 998.7-1 012.7 hPa and 1 022.1-1 031.5 hPa (P<0.05). The highest CRR of SFTS [CRR=1.024, 95%CI: (0.882, 1.188)] was seen at the sunshine duration being 31.0 h, and the risk of SFTS was decreased upon the sunshine duration being >39.3 h (P<0.05). The higher the weekly precipitation, the higher the risk of SFTS (P<0.05). Conclusions There is a nonlinear relationship between the cases of SFTS and meteorological factors. Suitable temperature and abundant precipitation are conducive to the occurrence of SFTS, yet high pressure and sunshine duration are unfavorable to the occurrence of SFTS.

Key words: Severe fever with thrombocytopenia syndrome, Meteorological factors, Distributed lag non-linear model, Chaohu City

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