Yield and Coverage of Active Case Finding Interventions for Tuberculosis Control:A Systematic Review and Meta-analysis. (30th June 2022)

• Record Type: Journal Article
• Authors: Deya, Ruth W.; Masese, Linnet N.; Jaoko, Walter; Muhwa, Jeremiah Chakaya; Mbugua, Lilian; Horne, David J.; Graham, Susan M.
• Other Names: Ivanyi Juraj Academic Editor.
• Is Part Of: Tuberculosis research and treatment. Volume 2022(2022)
• Publication Date: 2022-06-30
• Subjects: Tuberculosis -- Periodicals; Tuberculosis -- Prevention -- Periodicals; Tuberculosis -- Treatment -- Periodicals; Tuberculosis -- Social aspects -- Periodicals; 616.995005
• DOI: 10.1155/2022/9947068
• Languages: English
• ISSNs: 2090-150X

Abstract

Abstract : Background. Active case finding (ACF) for tuberculosis (TB) is a key strategy to reduce diagnostic delays, expedite treatment, and prevent transmission. Objective. Our objective was to identify the populations, settings, screening and diagnostic approaches that optimize coverage (proportion of those targeted who were screened) and yield (proportion of those screened who had active TB) in ACF programs. Methods. We performed a comprehensive search to identify studies published from 1980-2016 that reported the coverage and yield of different ACF approaches. For each outcome, we conducted meta-analyses of single proportions to produce estimates across studies, followed by meta-regression to identify predictors. Findings. Of 3, 972 publications identified, 224 met criteria after full-text review. Most individuals who were targeted successfully completed screening, for a pooled coverage estimate of 93.5%. The pooled yield of active TB across studies was 3.2%. Settings with the highest yield were internally-displaced persons camps (15.6%) and healthcare facilities (6.9%). When compared to symptom screening as the reference standard, studies that screened individuals regardless of symptoms using microscopy, culture, or GeneXpert®MTB/RIF (Xpert) had 3.7% higher case yield. In particular, microbiological screening (usually microscopy) as the initial test, followed by culture or Xpert for diagnosis had 3.6% higher yield than symptom screening followed by microscopy for diagnosis. In a model adjusted for use of Xpert testing, approaches targeting persons living with HIV (PLWH) had a 4.9% higher yield than those targeting the general population. In all models, studies targeting children had higher yield (4.8%-5.7%) than those targeting adults. Conclusion. ACF activities can be implemented successfully in various populations and settings. Screening yield was highest in internally-displaced person and healthcare settings, and among PLWH and children. In high-prevalence settings, ACF approaches that screen individuals with laboratory tests regardless of symptoms have higher yield than approaches focused on symptomatic individuals.