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AIDS ; 33(15): 2431-2435, 2019 12 01.
Article in English | MEDLINE | ID: mdl-31764108

ABSTRACT

OBJECTIVE: To evaluate the utility of a broad and nonspecific symptom screen for identifying people with undiagnosed HIV infection. DESIGN: Secondary analysis of operational data collected during implementation of a cluster-randomized trial for tuberculosis case detection. METHODS: As part of the trial, adults reporting cough, fever, night sweats, weight loss, or difficulty breathing for 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. RESULTS: We identified 3818 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% confidence interval (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 in health facilities = 2.58, 95% CI 1.65-4.05; adjusted prevalence ratio in mobile units = 2.63, 95% CI 1.37-5.03). CONCLUSION: We observed a high yield of new HIV diagnoses among adults identified by active application of a broad symptom screen. Use of integrated tuberculosis and HIV screening could help close the detection gap for both conditions.


Subject(s)
HIV Infections/diagnosis , Health Facilities , Mass Screening/statistics & numerical data , Mobile Health Units , Tuberculosis/epidemiology , Adolescent , Adult , Female , HIV Infections/complications , HIV Infections/epidemiology , Humans , Kenya/epidemiology , Male , Mass Screening/methods , Middle Aged , Prevalence , Regression Analysis , Sex Factors , Tuberculosis/complications , Young Adult
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