Influence of Sampling on Estimates of Clustering and Recent Transmission of Mycobacterium tuberculosis Derived from DNA Fingerprinting Techniques

The availability of DNA fingerprinting techniques for Mycobacterium tuberculosis has led to attempts to estimate the extent of recent transmission in populations, using the assumption that groups of tuberculosis patients with identical isolates (“clusters”) are likely to reflect recently acquired in...

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Bibliographic Details
Published in:American journal of epidemiology 1999-02, Vol.149 (4), p.366-371
Main Authors: Glynn, J. R., Vyonycky, E., Fine, P. E. M.
Format: Article
Language:English
Subjects:
Bacterial diseases
Bias
bias (epidemiology)
Biological and medical sciences
Cluster Analysis
DNA Fingerprinting
Epidemiologic Methods
epidemiology
Human bacterial diseases
Humans
Infectious diseases
Medical sciences
Models, Statistical
molecular
Mycobacterium tuberculosis - genetics
Sampling Studies
San Francisco
South Africa
Stochastic Processes
study design
tuberculosis
Tuberculosis and atypical mycobacterial infections
Tuberculosis, Pulmonary - transmission
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Summary:The availability of DNA fingerprinting techniques for Mycobacterium tuberculosis has led to attempts to estimate the extent of recent transmission in populations, using the assumption that groups of tuberculosis patients with identical isolates (“clusters”) are likely to reflect recently acquired infections. It is never possible to include all cases of tuberculosis in a given population in a study, and the proportion of isolates found to be clustered will depend on the completeness of the sampling. Using stochastic simulation models based on real and hypothetical populations, the authors demonstrate the influence of incomplete sampling on the estimates of clustering obtained. The results show that as the sampling fraction increases, the proportion of isolates identified as clustered also increases and the variance of the estimated proportion clustered decreases. Cluster size is also important: the underestimation of clustering for any given sampling fraction is greater, and the variability in the results obtained is larger, for populations with small clusters than for those with the same number of individuals arranged in large clusters. A considerable amount of caution should be used in interpreting the results of studies on clustering of M. tuberculosis isolates, particularly when sampling fractions are small. Am J Epidemiol 1999;149:366–71.
ISSN:0002-9262
1476-6256
DOI:10.1093/oxfordjournals.aje.a009822