Sampling bias in the molecular epidemiology of tuberculosis.
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.
Murray
Megan
M
Department of Epidemiology, Harvard School of Public Health, Boston, Massachussetts 02115, USA. mmurray@hsph.harvard.edu
D000462:Algeria / Q000453:epidemiology; D003198:Computer Simulation; D006801:Humans; D017720:Molecular Epidemiology / Q000379:methods*; D009010:Monte Carlo Method; D009169:Mycobacterium tuberculosis / Q000302:isolation & purification; D009426:Netherlands / Q000453:epidemiology; D016017:Odds Ratio; D012307:Risk Factors; D015983:Selection Bias; D013397:Sudan / Q000453:epidemiology; D014376:Tuberculosis / Q000453:epidemiology* / Q000635:transmission*; D014481:United States / Q000453:epidemiology