甘亚弟, 高艳青, 唐金凤, 胡月, 王新宇, 李梦楠, 刘琪, 李志平, 张丽杰, 李秋玲. 2013-2022年北京市大兴区布鲁氏菌病流行病学特征及患者的发现延误分析[J]. 疾病监测. DOI: 10.3784/jbjc.2021.000
引用本文: 甘亚弟, 高艳青, 唐金凤, 胡月, 王新宇, 李梦楠, 刘琪, 李志平, 张丽杰, 李秋玲. 2013-2022年北京市大兴区布鲁氏菌病流行病学特征及患者的发现延误分析[J]. 疾病监测. DOI: 10.3784/jbjc.2021.000
Gan Yadi, Gao Yanqing, Tang Jinfeng, Hu Yue, Wang Xinyu, Li Mengnan, Liu Qi, Li Zhiping, Zhang Lijie, Li Qiuling. Analysis on epidemiological characteristics of human brucellosis and case detection delay in Daxing district, Beijing, 2013−2022[J]. Disease Surveillance. DOI: 10.3784/jbjc.2021.000
Citation: Gan Yadi, Gao Yanqing, Tang Jinfeng, Hu Yue, Wang Xinyu, Li Mengnan, Liu Qi, Li Zhiping, Zhang Lijie, Li Qiuling. Analysis on epidemiological characteristics of human brucellosis and case detection delay in Daxing district, Beijing, 2013−2022[J]. Disease Surveillance. DOI: 10.3784/jbjc.2021.000

2013-2022年北京市大兴区布鲁氏菌病流行病学特征及患者的发现延误分析

Analysis on epidemiological characteristics of human brucellosis and case detection delay in Daxing district, Beijing, 2013−2022

  • 摘要:
    目的 分析2013—2022年北京市大兴区人间布鲁氏菌病(布病)病例流行特征、发病趋势及感染来源,为制定大兴区布病防控措施提供依据。
    方法 从中国疾病预防控制信息系统子系统传染病报告信息管理系统收集2013—2022年北京市大兴区布病病例相关信息,对布病病例基本情况、流行特征、临床表现、病原学检测及感染来源进行描述性统计分析,采用χ2检验比较各年度及性别发病率;采用Joinpoint回归模型对2013—2022年该地区人间布病病例发现延误变化趋势进行分析。
    结果 2013—2022年大兴区共报告130例布病病例,年均发病率为0.79/10万,发病地区以农村及城乡结合部为主且以夏秋季高发,发病率在各年度组间(χ2=18.828,P=0.027)、性别组间(χ2=28.494,P<0.001)、各年龄组组间(χ2=36.287,P<0.001)差异均有统计学意义;2013—2022年平均就诊延误率为33.33%(40/120),各年间就诊延误率变化差异无统计学意义年度变化百分比(APC)=−6.31%,95%置信区间(CI):−44.03%~56.84%,t=−0.315,P=0.777,病例就诊时间中位数为6 d。2013—2022年平均诊断延误率为50.83%(61/120),各年间诊断延误率总体呈下降趋势,平均每年下降12.00%平均年度变化百分比(AAPC)=−11.40%,95%CI:−23.56%~2.72%,t=−1.623,P=0.108,Joinpoint回归模型分段分析结果显示,在2013—2018年诊断延误率呈逐年下降趋势且差异有统计学意义 (APC=−34.12%,95%CI:−47.76%~−17.11%,t=−4.708,P=0.006),在2018—2022年诊断延误率变化差异无统计学意义 (APC=28.40%,95%CI:−7.27%~77.82%,t=2.014,P=0.105 )。病例诊断时间中位数为10 d,总体呈下降趋势(趋势χ2 =17.395,P<0.001),中位数由2013年19 d降至2022年5 d。
    结论 大兴区布病发病呈现明显的季节性和地区性差异,布病病例发现延误现象较为严重,诊断延误随时间变化总体呈下降趋势。应持续开展多部门联防联控,采取综合性防控措施。

     

    Abstract:
    Objective To analyze the epidemiological characteristics, incidence trend and infection source of human brucellosis in Daxing district of Beijing from 2013 to 2022 and provide data support for the prevention and treatment of human brucellosis in Daxing.
    Methods The incidence data of human brucellosis in Daxing during this period were collected from National Infectious Disease Reporting Information Management System for a descriptive epidemiological analysis on the epidemiological characteristics, incidence, pathogen testing, clinical manifestations, sources of infection and etiological detection of reported human brucellosis cases. The differences in incidence of human brucellosis among different years and between men and women were compared with χ2 test. Joinpoint regression model was used to analyze the changing trend of detection delay of human brucellosis cases.
    Results From 2013 to 2022, a total of 130 cases of human brucellosis were reported in Daxing, The annual average incidence rate was 0.79/100,000. The cases mainly occurred in rural area and urban-rural continuum, and incidence rate was high during summer - autumn. There were significant differences in incidence rates among years (χ2=18.828, P=0.027), between men and women (χ2=28.494, P<0.001), and among age groups (χ2=36.287, P<0.001).The average medical care-seeking delay rate of the human brucellosis cases was 33.33% (40/120), and there was no significant difference in annual medical care-seeking delay rate annual percentage change (APC)=−6.31%, 95% confidence interval(CI): −44.03%~56.84%, t=−0.315, P=0.777, the median time of medical care-seeking was 6 days. The average diagnosis delay rate from 2013 to 2022 was 50.83% (61/120). The annual diagnosis delay rate generally showed a downward trend, with an average annual decrease of 12.0% average annual percentage change (AAPC)=−11.40%, 95% CI: −23.56%~2.72%, t=−1.623, P=0.108. The segmented analysis results of the Joinpoint regression model showed that the diagnosis delay rate showed a downward trend year by year from 2013 to 2018, and the difference was significant (APC=−34.12%, 95% CI: −47.76%~−17.11%, t=−4.708, P=0.006), there was no significant difference in the change in diagnosis delay rate from 2018 to 2022 (APC=28.40%, 95% CI: −7.27%~77.82%, t=2.014, P =0.105). The median interval between onset and diagnosis of the cases was 10 days, showing an overall downward trend from 19 days in 2013 to 5 days in 2022 (χ2=17.395, P<0.001)
    Conclusion From 2013 to 2022, the obvious seasonal and area differences were observed in the incidence of human brucellosis in Daxing. The rate of detection delay of the human brucellosis cases was relatively serious, but showed a decreasing trend over time. It is necessary to take joint and comprehensive prevention and control measures.

     

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