[THE POTENTIAL ROLE OF SOCIAL NETWORK ANALYSIS IN TUBERCULOSIS CONTACT INVESTIGATION].

Kekkaku : [Tuberculosis] Pub Date : 2017-01-01
Kiyohiko Izumi, Lisa Kawatsu, Satoshi Miyake, Yu Watanabe, Yoshiro Murase, Kazuhiro Uchimura, Akihiro Ohkado
{"title":"[THE POTENTIAL ROLE OF SOCIAL NETWORK ANALYSIS IN TUBERCULOSIS CONTACT INVESTIGATION].","authors":"Kiyohiko Izumi,&nbsp;Lisa Kawatsu,&nbsp;Satoshi Miyake,&nbsp;Yu Watanabe,&nbsp;Yoshiro Murase,&nbsp;Kazuhiro Uchimura,&nbsp;Akihiro Ohkado","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>[Aim] To explore the possible role of social network analysis (SNA) in identifying infected contacts and visualizing data in a tuberculosis (TB) contact investigation. [Method] We analyzed TB contact investigation data from an outbreak in a Japanese language school in Tokyo, Japan, in 20XX. Information on places which the index case and his contacts commonly shared was collected in line with the data collected routinely in contact investigation. Average hours of exposure to the index case were calculated for each contact by using SNA software, and the relationship to the index case via commonly shared places was visualized as a sociogram. Statistical analysis was performed to. compare the exposure hours and TB infection statuses, between those . infected, including active TB and latent TB infection (LTBI), and non- infected contacts. [Result] The data on the index TB case and 41 contacts, of whom 5 and 10 were diagnosed with active TB and LTBI, were analyzed. Contacts with active TB and LTBI had 12.5 and 11.5 times longer median hours of exposure, which were significantly longer compared to non-infected contacts. The sociogram summarized the network of index TB case, contacts characterized by exposure hours and infection statuses, and the places shared by the index case and the contacts. [Discussion] SNA analysis was considered to be useful in prioritizing contacts in a TB contact investigation, in assisting interpretation of indeterminate Interferon-Gamma release assay test results, in estimating places where transmission occurred, and visualizing data accrued in TB contact inves- tigations.</p>","PeriodicalId":17997,"journal":{"name":"Kekkaku : [Tuberculosis]","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kekkaku : [Tuberculosis]","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

[Aim] To explore the possible role of social network analysis (SNA) in identifying infected contacts and visualizing data in a tuberculosis (TB) contact investigation. [Method] We analyzed TB contact investigation data from an outbreak in a Japanese language school in Tokyo, Japan, in 20XX. Information on places which the index case and his contacts commonly shared was collected in line with the data collected routinely in contact investigation. Average hours of exposure to the index case were calculated for each contact by using SNA software, and the relationship to the index case via commonly shared places was visualized as a sociogram. Statistical analysis was performed to. compare the exposure hours and TB infection statuses, between those . infected, including active TB and latent TB infection (LTBI), and non- infected contacts. [Result] The data on the index TB case and 41 contacts, of whom 5 and 10 were diagnosed with active TB and LTBI, were analyzed. Contacts with active TB and LTBI had 12.5 and 11.5 times longer median hours of exposure, which were significantly longer compared to non-infected contacts. The sociogram summarized the network of index TB case, contacts characterized by exposure hours and infection statuses, and the places shared by the index case and the contacts. [Discussion] SNA analysis was considered to be useful in prioritizing contacts in a TB contact investigation, in assisting interpretation of indeterminate Interferon-Gamma release assay test results, in estimating places where transmission occurred, and visualizing data accrued in TB contact inves- tigations.

[社会网络分析在肺结核接触调查中的潜在作用]。
[目的]探讨社会网络分析(SNA)在结核病(TB)接触者调查中识别感染接触者和数据可视化中的可能作用。[方法]对日本东京某日语学校2009年暴发的结核接触者调查数据进行分析。根据接触者调查常规收集的数据,收集指示病例与其接触者共同居住的场所信息。使用SNA软件计算每个接触者接触指标病例的平均时间,并通过共同共享的场所将与指标病例的关系可视化为社会图谱。进行统计分析。比较它们之间的暴露时间和结核感染状况。感染,包括活动性结核和潜伏性结核感染(LTBI),以及未感染的接触者。[结果]对41例接触者及指数结核病例资料进行分析,其中活动性结核和LTBI分别确诊5例和10例。与未感染的接触者相比,活动性结核病和LTBI接触者的中位数暴露时间长12.5倍和11.5倍。社会图总结了指数结核病例、以暴露时间和感染状况为特征的接触者网络以及指数结核病例与接触者共有的场所。[讨论]SNA分析被认为有助于在结核接触调查中确定接触者的优先次序,协助解释不确定的干扰素- γ释放试验结果,估计发生传播的地点,以及可视化结核接触调查中积累的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信