Sampling Bias in the Molecular Epidemiology of Tuberculosis

Details

• Alternative Title:
  Emerg Infect Dis
• Personal Author:
  Murray, Megan
• Description:
  Among the goals of the molecular epidemiology of infectious disease are to quantify the extent of ongoing transmission of infectious agents and to identify host- and strain-specific risk factors for disease spread. I demonstrate the potential bias in estimates of recent transmission and the impact of risk factors for clustering by using computer simulations to reconstruct populations of tuberculosis patients and sample from them. The bias consistently results in underestimating recent transmission and the impact of risk factors for recent transmission.
• Subjects:
  • Research
  • DNA Fingerprinting
  • Computer Simulation
  • Humans
  • Molecular Epidemiology
  • Monte Carlo Method
  • Mycobacterium Tuberculosis
  • Odds Ratio
  • Risk Factors
  • Selection Bias
  More +
• Source:
  Emerg Infect Dis. 8(4):363-369.
• Document Type:
  Journal Article
• Place as Subject:
  Algeria ; Netherlands ; Sudan ; United States
• Location:
  Africa ; Europe ; Africa ; North America
• Volume:
  8
• Issue:
  4
• Download URL:
  https://stacks.cdc.gov/view/cdc/13742/cdc_13742_DS1.pdf
• File Type:
  [PDF - 2.10 MB]
• Collection(s):
  Emerging Infectious Diseases
• Main Document Checksum:
  urn:sha256:d4967030bfb3d1284703e2131a8dcddc7c79242dabaf5e70f3e8d9b82782d6e6