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Start4All: protocol for evaluating TB screening and diagnostic tests and test algorithms in the community and lower care levels in seven high-burden countries

  • iccdr,b
  • Bingham University
  • Friends for International TB Relief
  • Karolinska Institutet
  • Stop TB Partnership
  • Janna Health Foundation
  • School of Health & Wellbeing
  • University of Glasgow
  • Center for Health Promotion and Research
  • Fundação de Apoio à Pesquisa e Extensão de Sergipe
  • Kenya Medical Research Institute

Research output: Contribution to journal › Article › peer-review

Abstract

BACKGROUND: Despite advances in TB care, ap-proximately 2.4 million people with TB remain undi-agnosed or unreported each year. A key contributor to these ‘missed millions’ is that major diagnostic gaps persist especially among underserved populations. De-veloping diagnostic algorithms that are accessible and integrated into health care systems where they are intended to be used is essential to meet WHO End TB targets. 

METHODS: Start4All a multi-country, cross-sectional diagnostic accuracy study (in Bangladesh, Brazil, Cameroon, Kenya, Malawi, Nigeria, and Viet Nam) aims to assess and model algorithms using combinations of WHO-endorsed, and experimental TB screening and diagnostic tests across the lowest levels of care and the community, compared to a sputum culture reference standard. Evaluated tools include C-reactive protein tests, computer-aided detection–interpreted chest X-rays, pooled Xpert® MTB/RIF Ultra (Xpert Ultra) testing, and a third generation lipoarabinomannan (LF-LAM) assay. 

DISCUSSION: Start4All will generate high-quality evidence to guide policy decisions on the adoption and the integration of non-sputum and laboratory independent tools to accelerate early TB detection and close the treatment gap. 

CONCLUSION: A feature of Start4All is its implementation within national TB programmes across seven high-burden countries to ensure that findings are directly translatable to policy and operational decision making. Harmonised protocols, standardised microbiological reference testing, and unified data management systems will enable cross-country comparison and strengthen the external validity of results.

Original languageEnglish
Pages (from-to)526-533
Number of pages8
JournalIJTLD Open
Volume3
Issue number8
DOIs
Publication statusPublished - 1 Aug 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • ACF
  • Bangladesh
  • Brazil
  • CAD
  • Cameroon
  • community-based case finding
  • facility-based case finding
  • Kenya
  • Malawi
  • Nigeria
  • tuberculosis
  • Viet Nam
  • vulnerable populations

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