Use of Death Certificates to Identify Tuberculosis-Related Deaths in Washington State.

Context: Death certificates are routinely used to estimate tuberculosis (TB) mortality rates. The validity of International Classification of Diseases, Tenth Revision (ICD-10) codes and text cause of death data for this purpose is uncertain.

Objective: To evaluate the accuracy of ICD-10 coded and text cause of death data in identifying TB-related deaths in Washington State.

HIV disclosure and subsequent sexual behaviors among men who have sex with men who meet online.

To assess HIV disclosure discussions and related sexual behaviors among men who have sex with men (MSM) who meet sex partners online, 28 qualitative interviews with Seattle-area MSM were analyzed using grounded theory methods and themes and behavior patterns were identified. MSM found a greater ease in communicating and could prescreen partners through the Internet. However, no consistent relationship was found between HIV disclosure and subsequent behaviors: some were safer based on disclosure while perceived HIV status led others to risky behaviors.

Predictors of discordant tuberculin skin test and QuantiFERON®-TB Gold In-Tube results in various high-risk groups.

Setting: Persons in whom targeted testing for latent tuberculosis infection (LTBI) is recommended in Seattle, Washington; Atlanta, Georgia; and central North Carolina, United States.

Objective: To compare the performance of an interferon-gamma release assay (QuantiFERON®-TB Gold In-Tube [QFT-GIT]) with the tuberculin skin test (TST) among foreign-born, homeless, human immunodeficiency virus (HIV) infected and substance abuse persons tested for LTBI.

Design: A cross-sectional study requiring participants to have a blood test, a TST and data collected.

Stochastic models to demonstrate the effect of motivated testing on HIV incidence estimates using the serological testing algorithm for recent HIV seroconversion (STARHS).

Objectives: To produce valid seroincidence estimates, the serological testing algorithm for recent HIV seroconversion (STARHS) assumes independence between infection and testing, which may be absent in clinical data. STARHS estimates are generally greater than cohort-based estimates of incidence from observable person-time and diagnosis dates. The authors constructed a series of partial stochastic models to examine whether testing motivated by suspicion of infection could bias STARHS.