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.

Public Health Relevance

Tuberculosis is one of the leading causes of death by a communicable disease globally. Existing approaches to studying tuberculosis transmission and diagnosing cases are based on screening individuals, which often identifies disease late in its course, after individuals have transmitted the infection to many others. We propose to study a new approach to identifying tuberculosis cases early through detection of the bacteria causing tuberculosis in the air of public congregate environments.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
NIH Director’s New Innovator Awards (DP2)
Project #
1DP2AI131082-01
Application #
9167046
Study Section
Special Emphasis Panel (ZRG1-MOSS-C (56)R)
Program Officer
Lacourciere, Karen A
Project Start
2016-09-30
Project End
2021-06-30
Budget Start
2016-09-30
Budget End
2021-06-30
Support Year
1
Fiscal Year
2016
Total Cost
$1,970,897
Indirect Cost
$405,861
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304