Publications by authors named "S Althomsons"

Article Synopsis
  • During 2014-2020, Washington state prisons reported no cases of tuberculosis (TB), but from July 2021 to June 2022, 25 TB cases emerged, indicating a significant outbreak linked to closely related bacteria strains among incarcerated individuals.
  • The outbreak involved a median infectious period of 170 days for contagious patients, leading to the identification of over 3,000 contacts, with 244 diagnosed with latent TB infection (LTBI) due to delayed case detection.
  • The lack of annual TB screening during the pandemic and fear of isolation contributed to the outbreak, highlighting the need for ongoing collaboration between the Washington State Department of Corrections and the Washington State Department of Health to manage and prevent future TB cases.
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A nationwide tuberculosis outbreak linked to a viable bone allograft product contaminated with Mycobacterium tuberculosis was identified in June 2021. Our subsequent investigation identified 73 healthcare personnel with new latent tuberculosis infection following exposure to the contaminated product, product recipients, surgical instruments, or medical waste.

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Objective: This study describes characteristics of large tuberculosis (TB) outbreaks in the United States detected using novel molecular surveillance methods during 2014-2016 and followed for 2 years through 2018.

Methods: We developed 4 genotype-based detection algorithms to identify large TB outbreaks of ≥10 cases related by recent transmission during a 3-year period. We used whole-genome sequencing and epidemiologic data to assess evidence of recent transmission among cases.

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Background: Mycobacterium tuberculosis transmission through solid organ transplantation has been well described, but transmission through transplanted tissues is rare. We investigated a tuberculosis outbreak in the USA linked to a bone graft product containing live cells derived from a single deceased donor.

Methods: In this outbreak report, we describe the management and severity of the outbreak and identify opportunities to improve tissue transplant safety in the USA.

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Article Synopsis
  • Early identification of tuberculosis (TB) clusters is essential for preventing future outbreaks and intervention opportunities.
  • Researchers analyzed U.S. TB surveillance data from 2009-2018, using machine learning to predict which clusters of TB cases were likely to grow beyond expected levels.
  • The study found that cluster characteristics, such as the timing of case accumulation, were more crucial predictors of growth than individual patient demographics, highlighting a comprehensive approach for public health strategies.
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