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AIDS. 2019 Aug 22. doi: 10.1097/QAD.0000000000002354. [Epub ahead of print]

High yield of new HIV diagnoses during active case-finding for tuberculosis.

Author information

Kenya Medical Research Institute, Kisumu, Kenya.
Harvard Medical School, Boston, Massachusetts, USA.
Kenya Medical Research Institute, US Army Medical Research Directorate - Kenya, Kisumu, Kenya.
US Army Medical Research Directorate - Kenya, Kisumu, Kenya.
Centers for Disease Control and Prevention, Kisumu, Kenya.
Centers for Disease Control and Prevention, Atlanta, Georgia, USA.



To evaluate the utility of a broad and non-specific symptom screen for identifying people with undiagnosed HIV infection.


Secondary analysis of operational data collected during implementation of a cluster-randomized trial for tuberculosis case detection.


As part of the trial, adults reporting cough, fever, night sweats, weight loss, or difficulty breathing of any duration in the past month were identified in health facilities and community-based mobile screening units in western Kenya. Adults reporting any symptom were offered HIV testing. We analysed the HIV testing data from this study, using modified Poisson regression to identify predictors of new HIV diagnoses among adults with symptoms and initially unknown HIV status.


We identified 3,818 symptomatic adults, referred 1424 (37%) for testing, of whom 1065 (75%) accepted, and 107 (10%) were newly diagnosed with HIV. The prevalence of new HIV diagnoses was 21% (95% CI: 17-25%) among those tested in health facilities and 5% (95% CI 4-7%) among those tested in mobile units. More men were diagnosed with HIV than women despite fewer men being screened. People who reported 4-5 symptoms were over twice as likely to be diagnosed with HIV compared to those reporting 1-3 symptoms (adjusted prevalence ratio [aPR] in health facilities = 2.58, 95% CI, 1.65-4.05; aPR in mobile units = 2.63, 95% CI, 1.37-5.03).


We observed a high yield of new HIV diagnoses among adults identified by active application of a broad symptom screen. Integrated tuberculosis and HIV screening using could help close the detection gap for both conditions.

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