Open Access Using tuberculosis patient characteristics to predict future cases with matching genotype results

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Abstract:

Setting:

United States.
Background:

It is unknown whether tuberculosis (TB) case or patient characteristics can predict the likelihood of future related TB cases.
Objective:

To estimate the likelihood for future related cases, i.e., cases with matching TB genotypes within the same county diagnosed within the 2 years following the year of reporting of each included case.
Design:

We considered all TB cases with genotyping results reported in the United States during 2004-2010. Predictive scores were calculated based on patient characteristics by dividing the number of patients who were not the last case in a county-level TB genotype cluster by the total number of patients.
Results:

Overall, there was a 30.8% chance that a future related case would be detected during the 2 years following the report year of any given case. Future related cases were detected in 34.7% of instances following the diagnosis of smear-positive cases, 51.9% of instances following the diagnosis of a homeless patient and 45.2% of instances following the diagnosis of a patient who reported substance abuse. Predictive scores ranged by race (White 13.9%, Native Hawaiian 43.8%) and age group (65 years 13.1%, 0-4 years 43%), and were higher for US-born patients.
Conclusion:

Behavioral and sociodemographic factors can help predict the likelihood of future related cases and can be used to prioritize contact investigations.

Keywords: genotype; transmission; tuberculosis

Document Type: Research Article

DOI: http://dx.doi.org/10.5588/pha.13.0098

Affiliations: Division of Tuberculosis Elimination, US Centers for Disease Control and Prevention, National Centers for HIV, Viral Hepatitis, STD, and Tuberculosis Prevention, Atlanta, Georgia, USA

Publication date: March 21, 2014

More about this publication?
  • Public Health Action (PHA), The Union's quarterly open access on-line journal, provides a platform for its mission 'Health solutions for the poor'. PHA addresses the need for show-casing operational research that addresses issues in health systems and services. It publishes high-quality scientific research that provides new knowledge to improve access, equity, quality and efficiency of health systems and services.
  • Editorial Board
  • Information for Authors
  • International Journal of Tuberculosis and Lung Disease
  • Public Health Action
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