Congregate air sampling for population-based detection of tuberculosis

用于基于人群的结核病检测的集中空气采样

• 批准号: 9167046
• 负责人: Jason Randolph Andrews
• 金额: $ 197.09万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2021-08-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9167046
• 关键词: Air; Bacteria; Cause of Death; Communicable Diseases; Country; Custom; Data; Data Collection; Detection; Devices; Diagnosis; Diagnostic; Disease; Environment; Epidemiologic Studies; Epidemiology; Healthcare; Household; Individual; Infection; Link; Methods; Modeling; Molecular; Molecular Diagnostic Techniques; Morbidity - disease rate; Mycobacterium tuberculosis; Phase; Population; Prevalence; Resources; Sampling; Social Network; South African; Testing; Translating; Tuberculosis; air sampling; base; care seeking; case finding; case-based; community setting; data modeling; high risk; member; mortality; novel strategies; population based; real world application; screening; social; tool; transmission process

Project Summary Tuberculosis is one of the leading causes of morbidity and mortality worldwide. Conventional approaches to studying tuberculosis transmission, and to early case detection, have been based on individual-level screening. Because of the long, subclinical phase of tuberculosis, during which infectious individuals have many casual contacts, understanding where transmission occurs in community settings has been a vexing challenge. Social network and molecular epidemiologic studies indicate that over 80% of transmission cannot be linked to close contacts or household members. Additionally, this prolonged period of transmission prior to healthcare-seeking makes tuberculosis difficult to control. Active case finding approaches, which involve screening individuals prior to care-seeking, are resource-intensive due to the high number-needed- to-test and have not been sustainable in most high burden countries. Here, we propose a fundamentally new approach to tuberculosis detection that would overcome these limitations: identifying M. tuberculosis in the shared air of congregate settings. Using custom-built air sampling devices and highly sensitive and specific molecular diagnostic techniques, we will rigorously investigate this approach with three fundamental, real- world applications. The first is to evaluate congregate air sampling as a group screening method for early case detection of tuberculosis, and to identify optimal sampling approaches through empirical data collection and model-based analysis. The second application is to identify high-risk environments for tuberculosis transmission, through systematic air sampling in public settings throughout a highly endemic South African township. The third is to efficiently generate population-level tuberculosis prevalence estimates by combining air sampling and social mixing data, and applying statistical inferential models based upon pooled diagnostic sampling. This project will generate critical data on this new population-based approach to M. tuberculosis detection, and will develop an epidemiologic and statistical framework with which to translate this into a tool for surveillance and early case detection.

项目概要 结核病是全世界发病和死亡的主要原因之一。 研究结核病传播和早期病例的常规方法 检测，都是基于个人层面的筛查。因为时间长， 结核病的亚临床阶段，在此期间感染者有许多偶然的症状 接触者、了解社区环境中传播发生的地点一直是 令人烦恼的挑战。社交网络和分子流行病学研究表明，超过 80% 的传播无法与密切接触者或家庭成员联系起来。 此外，在就医之前这种长时间的传播使得 结核病难以控制。积极的病例发现方法，包括筛查 由于需要的人数较多，在寻求护理之前的个人是资源密集型的 尚待测试，但在大多数高负担国家并不可持续。在此，我们建议 一种全新的结核病检测方法可以克服这些问题 局限性：在聚集环境的共享空气中识别结核分枝杆菌。使用 定制的空气采样装置和高灵敏度和特异性的分子诊断 技术，我们将通过三个基本的、真实的严格研究这种方法 世界应用。第一个是将集体空气采样作为群体筛查进行评估 结核病早期病例检测并确定最佳采样的方法 通过实证数据收集和基于模型的分析的方法。第二个 应用程序是通过以下方式识别结核病传播的高风险环境 在南非流行病高度流行的地区，对公共场所进行系统的空气采样 乡。三是有效产生人口水平的结核病患病率 通过结合空气采样和社会混合数据并应用统计进行估计 基于汇总诊断抽样的推理模型。该项目将生成 关于这种基于人群的结核分枝杆菌检测新方法的关键数据，并将 开发一个流行病学和统计框架，将其转化为工具 用于监测和早期病例发现。