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A Field-Validated Approach Using Surveillance and Genotyping Data to Estimate Tuberculosis Attributable to Recent Transmission in the United States

Supporting Files
File Language:
English


Details

  • Alternative Title:
    Am J Epidemiol
  • Personal Author:
  • Description:
    Tuberculosis genotyping data are frequently used to estimate the proportion of tuberculosis cases in a population that are attributable to recent transmission (RT). Multiple factors influence genotype-based estimates of RT and limit the comparison of estimates over time and across geographic units. Additionally, methods used for these estimates have not been validated against field-based epidemiologic assessments of RT. Here we describe a novel genotype-based approach to estimation of RT based on the identification of plausible-source cases, which facilitates systematic comparisons over time and across geographic areas. We compared this and other genotype-based RT estimation approaches with the gold standard of field-based assessment of RT based on epidemiologic investigation in Arkansas, Maryland, and Massachusetts during 1996-2000. We calculated the sensitivity and specificity of each approach for epidemiologic evidence of RT and calculated the accuracy of each approach across a range of hypothetical RT prevalence rates plausible for the United States. The sensitivity, specificity, and accuracy of genotype-based RT estimates varied by approach. At an RT prevalence of 10%, accuracy ranged from 88.5% for state-based clustering to 94.4% with our novel approach. Our novel, field-validated approach allows for systematic assessments over time and across public health jurisdictions of varying geographic size, with an established level of accuracy.
  • Subjects:
  • Source:
    Am J Epidemiol. 182(9):799-807.
  • Pubmed ID:
    26464470
  • Pubmed Central ID:
    PMC5996379
  • Document Type:
  • Funding:
  • Place as Subject:
  • Volume:
    182
  • Issue:
    9
  • Collection(s):
  • Main Document Checksum:
    urn:sha256:c68cb8107ecce899fc0ec20ac071531cee3b5fbb76e344cbf95c84d1ae03b229
  • Download URL:
  • File Type:
    Filetype[PDF - 544.46 KB ]
File Language:
English
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