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Investigating extradomiciliary transmission of tuberculosis: An exploratory approach using social network patterns of TB cases and controls and the genotyping of Mycobacterium tuberculosis
Tuberculosis ( IF 2.8 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.tube.2020.102010
Suani T R Pinho 1 , Susan M Pereira 2 , José G V Miranda 1 , Tonya A Duarte 3 , Joilda S Nery 2 , Maeli G de Oliveira 4 , M Yana G S Freitas 4 , Naila A De Almeida 5 , Fabio B Moreira 1 , Raoni B C Gomes 2 , Ligia Kerr 6 , Carl Kendall 7 , M Gabriela M Gomes 8 , Theolis C B Bessa 9 , Roberto F S Andrade 1 , Mauricio L Barreto 10
Affiliation  

Extradomiciliary contacts have been overlooked in the study of TB transmission due to difficulties in identifying actual contacts in large populations. Complex network analysis provides a framework to model the structure of contacts, specially extradomiciliary ones. We conducted a study of incident sputum-positive TB cases and healthy controls occurring in a moderate TB burden city. Cases and controls were interviewed to obtain data regarding the usual locations of residence, work, study, and leisure. Mycobacterium tuberculosis isolated from sputum was genotyped. The collected data were used to build networks based on a framework of putative social interactions indicating possible TB transmission. A user-friendly open source environment (GraphTube) was setup to extract information from the collected data. Networks based on the likelihood of patient-patient, patient-healthy, and healthy-healthy contacts were setup, depending on a constraint of geographical distance of places attended by the volunteers. Using a threshold for the geographical distance of 300 m, the differences between TB cases and controls are revealed. Several clusters formed by social network nodes with high genotypic similarity were characterized. The developed framework provided consistent results and can be used to support the targeted search of potentially infected individuals and to help to understand the TB transmission.

中文翻译:

调查结核病的体外传播:使用结核病病例和对照的社会网络模式以及结核分枝杆菌基因分型的探索性方法

由于难以确定大量人群中的实际接触者,因此在结核病传播研究中忽略了外部接触者。复杂网络分析提供了一个框架来模拟联系人的结构,特别是外部联系人。我们对一个中等结核病负担城市中发生的痰阳性结核病病例和健康对照进行了研究。对病例和对照进行了访谈,以获取有关通常居住、工作、学习和休闲地点的数据。从痰中分离出的结核分枝杆菌进行了基因分型。收集到的数据用于建立基于假定的社会互动框架的网络,表明可能的结核病传播。一个用户友好的开源环境 (GraphTube) 被设置为从收集的数据中提取信息。根据志愿者参加的地点的地理距离限制,建立了基于患者-患者、患者-健康和健康-健康接触可能性的网络。使用 300 m 的地理距离阈值,可以揭示结核病病例和对照之间的差异。表征了由具有高基因型相似性的社交网络节点形成的几个集群。开发的框架提供了一致的结果,可用于支持对潜在感染者的有针对性的搜索,并有助于了解结核病的传播。揭示了结核病病例和对照之间的差异。表征了由具有高基因型相似性的社交网络节点形成的几个集群。开发的框架提供了一致的结果,可用于支持对潜在感染者的有针对性的搜索,并有助于了解结核病的传播。揭示了结核病病例和对照之间的差异。表征了由具有高基因型相似性的社交网络节点形成的几个集群。开发的框架提供了一致的结果,可用于支持对潜在感染者的有针对性的搜索,并有助于了解结核病的传播。
更新日期:2020-12-01
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