Cook Victoria J, Sun Sumi J, Tapia Jane, Muth Stephen Q, Arguello D Fermin, Lewis Bryan L, Rothenberg Richard B, McElroy Peter D
Department of Medicine, University of British Columbia, 655 W. 12th Avenue, Vancouver, BC, Canada.
J Infect Dis. 2007 Nov 15;196(10):1517-27. doi: 10.1086/523109. Epub 2007 Oct 31.
Social network analysis (SNA) is an innovative approach to the collection and analysis of infectious disease transmission data. We studied whether this approach can detect patterns of Mycobacterium tuberculosis transmission and play a helpful role in the complex process of prioritizing tuberculosis (TB) contact investigations.
We abstracted routine demographic and clinical variables from patient medical records and contact interview forms. We also administered a structured questionnaire about places of social aggregation to TB patients and their contacts. All case-contact, contact-contact, case-place, and contact-place dyads (pairs and links) were considered in order to analyze the structure of a social network of TB transmission. Molecular genotyping was used to confirm SNA-detected clusters of TB.
TB patients not linked through conventional contact-investigation data were connected through mutual contacts or places of social aggregation, using SNA methods. In some instances, SNA detected connected groups prior to the availability of genotyping results. A positive correlation between positive results of contacts' tuberculin skin test (TST) and location in denser portions of the person-place network was observed (P<.01).
Correlation between TST-positive status and dense subgroup occurrence supports the value of collecting place data to help prioritize TB contact investigations. TB controllers should consider developing social network analysis capacity to facilitate the systematic collection, analysis, and interpretation of contact-investigation data.
社交网络分析（SNA）是一种收集和分析传染病传播数据的创新方法。我们研究了这种方法是否能够检测结核分枝杆菌的传播模式，并在结核病（TB）接触者调查优先排序的复杂过程中发挥有益作用。
我们从患者病历和接触者访谈表格中提取常规人口统计学和临床变量。我们还向结核病患者及其接触者发放了一份关于社交聚集场所的结构化问卷。为了分析结核病传播社交网络的结构，我们考虑了所有病例-接触者、接触者-接触者、病例-场所和接触者-场所二元组（配对和联系）。采用分子基因分型来确认社交网络分析检测到的结核菌群。
通过社交网络分析方法，未通过传统接触者调查数据建立联系的结核病患者通过共同接触者或社交聚集场所建立了联系。在某些情况下，社交网络分析在基因分型结果出来之前就检测到了有联系的群体。观察到接触者结核菌素皮肤试验（TST）阳性结果与在人际-场所网络较密集部分的位置之间存在正相关（P<0.01）。
TST阳性状态与密集亚组出现之间的相关性支持收集场所数据以帮助确定结核病接触者调查优先顺序的价值。结核病防控人员应考虑发展社交网络分析能力，以促进接触者调查数据 的系统收集、分析和解释。
