Epidemiological evaluation of spatiotemporal and genotypic clustering of Mycobacterium tuberculosis in Ontario, Canada
BACKGROUND: In Canada, tuberculosis (TB) rates are at a historic low, with the remaining risk concentrated in a few vulnerable population subgroups.OBJECTIVES: To describe the epidemiology of TB in the Canadian province of Ontario and to characterise risk factors associated with transmission events,...
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Published in | The international journal of tuberculosis and lung disease Vol. 17; no. 10; pp. 1322 - 1327 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Paris, France
International Union Against Tuberculosis and Lung Disease
01.10.2013
International Union against Tuberculosis and Lung Disease |
Subjects | |
Online Access | Get full text |
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Summary: | BACKGROUND: In Canada, tuberculosis (TB) rates are at a historic low, with the remaining risk concentrated in a few vulnerable population subgroups.OBJECTIVES: To describe the epidemiology of TB in the Canadian province of Ontario and to characterise risk factors associated with
transmission events, identified using genetic typing techniques.DESIGN: Retrospective analysis of 2186 culture-positive TB cases between August 2007 and December 2011. Temporal trends and risk of spatiotemporal and genotypic clustering were evaluated using Poisson and logistic regression
models.RESULTS: Being in a spatiotemporal cluster was associated with Aboriginal status (odds ratio [OR] 3.63, 95% confidence interval [CI] 1.23-10.71). Cases in genotypic clusters were more likely to report homelessness as a risk factor (adjusted OR [aOR] 2.92, 95%CI 1.74-4.90)
or be male (aOR 1.35, 95%CI 1.09-1.68), and were less likely to be aged ≥65 years (aOR 0.63, 95%CI 0.49-0.82), foreign-born (aOR 0.32, 95%CI 0.24-0.43) or Aboriginal (aOR 0.40, 95%CI 0.16-0.99). The Beijing lineage had an annual rate of increase of almost 10% (P
= 0.047), and was associated with genotypic clustering (aOR 2.84, 95%CI 2.19-3.67).CONCLUSION: Genotypic data suggest that disease clusters are smaller, but far more common, than would be estimated using spatiotemporal clustering. |
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Bibliography: | 1027-3719(20131001)17:10L.1322;1- (R) Medicine - General ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 1027-3719 1815-7920 |
DOI: | 10.5588/ijtld.13.0145 |