结核与肺部疾病杂志 ›› 2020, Vol. 1 ›› Issue (2): 154-158.doi: 10.3969/j.issn.2096-8493.2020.02.013

• 论著 • 上一篇    下一篇

广东省阳江市某高校结核病聚集性疫情调查

曾玉环, 陈建仁, 姚正钢, 张晨晨, 温文沛()   

  1. 529500 广东省阳江市公共卫生医院公共卫生科(曾玉环、陈建仁、姚正钢);广东省结核病控制中心(张晨晨、温文沛)
  • 收稿日期:2020-05-06 出版日期:2020-09-30 发布日期:2020-10-15
  • 通信作者: 温文沛 E-mail:568323856@qq.com
  • 基金资助:
    “十三五”国家科技重大专项(2017ZX10201302-005)

Investigation of a tuberculosis outbreak in an university in Yangjiang prefecture, Guangdong Province

ZENG Yu-huan, CHEN Jian-ren, YAO Zheng-gang, ZHANG Chen-chen, WEN Wen-pei()   

  1. Public Health Branch, Yangjiang Public Health Hospital of Guangdong Province, Yangjiang 529500,China
  • Received:2020-05-06 Online:2020-09-30 Published:2020-10-15
  • Contact: WEN Wen-pei E-mail:568323856@qq.com

摘要:

目的 探索广东省阳江市某高校结核病聚集疫情发生、发展及处置情况,为学校结核病防控工作提供实践经验。方法 收集2019年9—12月阳江市某高校发现的9例肺结核患者及疫情处置资料,对与患者密切接触的676名学生进行胸部X线摄影(简称“胸片”)和结核菌素纯蛋白衍生物(PPD)皮肤试验筛查。第一轮对65名“17动漫班”同班同学、同宿舍及任课老师开展密切接触者筛查;第二轮对389名与“17动漫班”共用教室的班级及与患者宿舍同楼层的学生和相关任课老师开展密切接触者筛查,上述两轮均发现患者的班级为高暴露组(5个班级共454名学生);第三轮对222名与“17动漫班”同楼层(非同教室)上课的其他班级学生开展密切接触者筛查,为低暴露组(4个班级共222名学生)。分析聚集性疫情的流行特征、发生原因和处置措施,探讨疫情扩散的原因。结果 9例患者中4例有咳嗽症状,其中1例咳嗽6个月(怀疑是首发传染源患者)。第一轮密切接触者筛查中进行PPD皮肤试验的学生65名,强阳性11名,强阳性率为16.92%,胸片显示异常13名;第二轮筛查共389名,PPD皮肤试验强阳性8名,强阳性率为2.06%,胸片显示异常5名;前两轮有疫情的班级强阳性19名,强阳性率为4.19%;第三轮筛查222名,PPD皮肤试验强阳性2名,强阳性率为0.90%,胸片异常者2名;高暴露组PPD皮肤试验强阳性率(4.19%,19/454)明显高于低暴露组(0.90%,2/222),两组比较差异有统计学意义(χ2=4.16,P=0.040)。结论 阳江市发现学校结核病患者后及时开展密切接触者分组筛查,结果表明高暴露组结核潜伏感染者高于低暴露组。

关键词: 结核,肺, 院校, 疾病暴发流行, 接触者追踪, 疾病影响状态调查

Abstract:

Objective To explore the occurrence, development and response of a tuberculosis epidemic in an university in Yangjiang prefecture, and to provide practical experience for the prevention and control of tuberculosis in schools. Methods From September to December 2019, 9 tuberculosis cases were found in an university in Yangjiang prefecture, Guangdong Province. Chest X-ray and tuberculin pure protein derivative (PPD) skin test were performed on 676 students in close contact with the patients. In the first round of investigation, 65 classmates from the “17 animation class”, roommates and teachers of TB patients were screened; In the second round of screening, 389 students from other classes that shared classrooms with the “17 animation class”, students on the same floor with TB patient’s dormitory and relevant teachers were screened. Classes that found patients in those 2 rounds were defined as the high exposure group (total 454 students in 5 classes). In the third round, 222 students from other classes in the same floor (other than the same classroom) with the “17 animation class” were screened, which was considered as the low-exposure group(222 students in 4 classes). We analyzed the epidemic characteristics, causes and treatment measures of this outbreak to discuss the causes of spread of this epidemic. Results Among those 9 patients, 4 had cough symptoms, among whom 1 had being coughing for more than half a year (suspected to be the first source of infection). In the first round of close contact screening, 65 students underwent PPD skin test, of which 11 were strongly positive (strong positive rate:16.92%), and 13 showed abnormality in chest radiograph. A total of 389 students were screened in the second round, 8 of them were strongly positive for PPD skin test (strong positive rate: 2.06%) and 5 showed abnormality in chest radiograph. In those first two rounds, totally 19 students were strongly positive, with a positive rate of 4.19%. Among the 222 students screened in the third round, 2 were strongly positive in PPD skin test, with a positive rate of 0.90% and 2 with abnormal chest radiograph; the PPD positive rate of high exposure group (4.19%, 19/454) was significantly higher than that of low exposure group (0.90%, 2/222),difference was statistically significant (χ2=4.16,P=0.040). Conclusion Close contact screening were carried out in a timely manner,the result showed that latent TB infection in high exposure group was significantly higher than that of the low exposure group.

Key words: Tuberculosis,pulmonary, Schools, Disease outbreaks, Contact tracing, Sickness impact profile