Literature DB >> 19249244

Effect of study duration on the interpretation of tuberculosis molecular epidemiology investigations.

G D van der Spuy1, P D van Helden, R M Warren.   

Abstract

Many molecular epidemiological investigations of M. tuberculosis are reported using data collected over relatively short timeframes. We postulated that such studies would tend to under-estimate the amount of disease in a community attributable to ongoing transmission. To test this hypothesis we used 12-year datasets of both real and simulated epidemics with the latter being based on two possible models of transmission. We analysed the effect of viewing the datasets through time windows of varying sizes on the measured degree of strain clustering as an indicator of ongoing transmission. We found that shorter windows significantly under-estimated transmission and that this effect was inversely correlated with the size of a cluster. Accordingly, we recommend that molecular epidemiological studies of M. tuberculosis, for the purposes of estimating transmission, be conducted over a minimum of 3-4 years and that the distribution of cluster size be taken into account in the interpretation of such data.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19249244     DOI: 10.1016/j.tube.2009.01.006

Source DB:  PubMed          Journal:  Tuberculosis (Edinb)        ISSN: 1472-9792            Impact factor:   3.131


  3 in total

1.  Mycobacterium tuberculosis transmission in a country with low tuberculosis incidence: role of immigration and HIV infection.

Authors:  Lukas Fenner; Sebastien Gagneux; Peter Helbling; Manuel Battegay; Hans L Rieder; Gaby E Pfyffer; Marcel Zwahlen; Hansjakob Furrer; Hans H Siegrist; Jan Fehr; Marisa Dolina; Alexandra Calmy; David Stucki; Katia Jaton; Jean-Paul Janssens; Jesica Mazza Stalder; Thomas Bodmer; Beatrice Ninet; Erik C Böttger; Matthias Egger
Journal:  J Clin Microbiol       Date:  2011-11-23       Impact factor: 5.948

2.  Transmission of tuberculosis in a South African community with a high prevalence of HIV infection.

Authors:  Keren Middelkoop; Barun Mathema; Landon Myer; Elena Shashkina; Andrew Whitelaw; Gilla Kaplan; Barry Kreiswirth; Robin Wood; Linda-Gail Bekker
Journal:  J Infect Dis       Date:  2014-07-22       Impact factor: 5.226

3.  Towards eliminating bias in cluster analysis of TB genotyped data.

Authors:  Cari van Schalkwyk; Madeleine Cule; Alex Welte; Paul van Helden; Gian van der Spuy; Pieter Uys
Journal:  PLoS One       Date:  2012-03-29       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.