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Drivers of Tuberculosis Transmission.
Mathema, Barun; Andrews, Jason R; Cohen, Ted; Borgdorff, Martien W; Behr, Marcel; Glynn, Judith R; Rustomjee, Roxana; Silk, Benjamin J; Wood, Robin.
Afiliação
  • Mathema B; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
  • Andrews JR; Division of Infectious Diseases and Geographic Medicine, Stanford University, California.
  • Cohen T; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut.
  • Borgdorff MW; Centers for Disease Control and Prevention, Kisumu, Kenya.
  • Behr M; Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Academic Medical Center, University of Amsterdam, the Netherlands.
  • Glynn JR; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal,Canada.
  • Rustomjee R; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, United Kingdom.
  • Silk BJ; Tuberculosis Clinical Research Branch, Therapeutics Research Program, Division of AIDS, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, Rockville, Maryland.
  • Wood R; Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia.
J Infect Dis ; 216(suppl_6): S644-S653, 2017 11 03.
Article em En | MEDLINE | ID: mdl-29112745
ABSTRACT
Measuring tuberculosis transmission is exceedingly difficult, given the remarkable variability in the timing of clinical disease after Mycobacterium tuberculosis infection; incident disease can result from either a recent (ie, weeks to months) or a remote (ie, several years to decades) infection event. Although we cannot identify with certainty the timing and location of tuberculosis transmission for individuals, approaches for estimating the individual probability of recent transmission and for estimating the fraction of tuberculosis cases due to recent transmission in populations have been developed. Data used to estimate the probable burden of recent transmission include tuberculosis case notifications in young children and trends in tuberculin skin test and interferon γ-release assays. More recently, M. tuberculosis whole-genome sequencing has been used to estimate population levels of recent transmission, identify the distribution of specific strains within communities, and decipher chains of transmission among culture-positive tuberculosis cases. The factors that drive the transmission of tuberculosis in communities depend on the burden of prevalent tuberculosis; the ways in which individuals live, work, and interact (eg, congregate settings); and the capacity of healthcare and public health systems to identify and effectively treat individuals with infectious forms of tuberculosis. Here we provide an overview of these factors, describe tools for measurement of ongoing transmission, and highlight knowledge gaps that must be addressed.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Transmissão de Doença Infecciosa Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Transmissão de Doença Infecciosa Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article