Details:

Alternative Title:
Emerg Infect Dis
Personal Author:
Althomsons, Sandy P. ; Hill, Andrew N. ; Harrist, Alexia V. ; France, Anne Marie ; Powell, Krista M. ; ... More +
Althomsons, Sandy P. ; Hill, Andrew N. ; Harrist, Alexia V. ; France, Anne Marie ; Powell, Krista M. ; Posey, James E. ; Cowan, Lauren S. ; Navin, Thomas R. Less -
Description:
We previously reported use of genotype surveillance data to predict outbreaks among incident tuberculosis clusters. We propose a method to detect possible outbreaks among endemic tuberculosis clusters. We detected 15 possible outbreaks, of which 10 had epidemiologic data or whole-genome sequencing results. Eight outbreaks were corroborated.
Subjects:
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Cluster Analysis Disease Outbreaks Dispatch Genome, Bacterial Genomics/methods Genotype Humans Incidence Models, Statistical Molecular Epidemiology Mycobacterium Tuberculosis/genetics Polymorphism, Single Nucleotide Prevalence Tuberculosis/diagnosis Tuberculosis/epidemiology Tuberculosis/microbiology
Source:
Emerg Infect Dis. 24(3):573-575.
Pubmed ID:
29460749
Pubmed Central ID:
PMC5823347
Document Type:
Journal Article
Place as Subject:
United States
Collection(s):
Emerging Infectious Diseases
Main Document Checksum:
[+]
urn:sha256:cfc8ce8a4b2b73e4fd4b896461e5964c3e8e49955a670b8078c45a5fa22fa1cf
Download URL:
https://stacks.cdc.gov/view/cdc/52196/cdc_52196_DS1.pdf
File Type:

Supporting Files

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