According to the World Health Organization, the global burden of tuberculosis peaked in 2000 and has since declined by 1.5% per year. This modest progress falls short of the Millennial Development Goals for tuberculosis elimination. Moreover, this average decline hides important variation in the incidence and prevalence of tuberculosis around the world today. This variation highlights that determinants of disease incidence may differ across regions, so interventions must be tailored to local the epidemiology of disease. The standard approach to tuberculosis control today relies on detection and treatment of prevalent tuberculosis cases. This approach may have limited effectiveness in areas of high tuberculosis burden where M. tuberculosis transmission is correspondingly high. Indeed, by the time a case is diagnosed and treated, the next generation of cases has already been newly infected. To make progress in curbing the epidemic of tuberculosis, new cases must be prevented, either by reducing transmission or by preventing disease. Household contact investigation has been a mainstay of active case finding of tuberculosis for decades. Although the household is a setting of intense transmission of tuberculosis, household transmission accounts for less than 25% of tuberculosis that occurs in a given community. While the household is a convenient, localized social network for transmission that is easily identified and evaluated, we must better understand the complex community networks that support M. tuberculosis transmission and lead to disease ?hotspots?. The goal of this proposal is to develop methods for measuring community networks that support tuberculosis transmission. In this proposal, we plan to reconstruct the social and mobility networks of infectious tuberculosis cases before diagnosis by using cellular telephone metadata and integrate this information with whole genome sequences of the M. tuberculosis strains from index cases to infer transmission networks.
The Specific Aims are: 1) To assess the movement of pulmonary tuberculosis cases before diagnosis as an indicator of M. tuberculosis transmission in an urban African community; 2) To infer transmission trees of M. tuberculosis in an urban African community using whole genome sequencing of isolates from tuberculosis index cases and relate transmission inferences to social networks and mobility patterns. To address these aims, we will expand the design of our current project by collecting archived cellular telephone metadata from index cases for one year prior to the diagnosis of tuberculosis. We will then construct socio-mobility networks that map movement within the community prior to diagnosis of tuberculosis. We will use whole genome sequencing of isolates collected from case networks to reconstruct transmission trees using a Bayesian framework which combines social and mobility networks with phylogenetic information. This novel approach to mapping transmission may give tuberculosis control programs a useful way to tailor public health interventions that are responsive to the local epidemiology of tuberculosis.

Public Health Relevance

In this proposal, we plan to study transmission of M. tuberculosis in an African urban setting by tracing the movements of tuberculosis cases in the community before diagnosis using archived cellular telephone records. These movements may be a marker of where the cases infect their contacts in the community. We will also use molecular epidemiology to infer the patterns of geographic spread of tuberculosis in the community. With better understanding of this local epidemiology, tuberculosis control programs can design and implement tailored interventions to control disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI093856-07
Application #
9761955
Study Section
Infectious Diseases, Reproductive Health, Asthma and Pulmonary Conditions Study Section (IRAP)
Program Officer
Lacourciere, Karen A
Project Start
2012-04-01
Project End
2022-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
7
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Georgia
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
004315578
City
Athens
State
GA
Country
United States
Zip Code
30602
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Martinez, Leonardo; Handel, Andreas; Shen, Ye et al. (2018) A Prospective Validation of a Clinical Algorithm to Detect Tuberculosis in Child Contacts. Am J Respir Crit Care Med 197:1214-1216
Martinez, Leonardo; Shen, Ye; Handel, Andreas et al. (2018) Effectiveness of WHO's pragmatic screening algorithm for child contacts of tuberculosis cases in resource-constrained settings: a prospective cohort study in Uganda. Lancet Respir Med 6:276-286
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Martinez, Leonardo; Xu, Lin; Chen, Cheng et al. (2017) Delays and Pathways to Final Tuberculosis Diagnosis in Patients from a Referral Hospital in Urban China. Am J Trop Med Hyg 96:1060-1065
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Martinez, Leonardo; Sekandi, Juliet N; Castellanos, MarĂ­a E et al. (2016) Infectiousness of HIV-Seropositive Patients with Tuberculosis in a High-Burden African Setting. Am J Respir Crit Care Med 194:1152-1163
Ma, Mai-Juan; Yang, Yang; Wang, Hai-Bin et al. (2015) Transmissibility of tuberculosis among school contacts: an outbreak investigation in a boarding middle school, China. Infect Genet Evol 32:148-55

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