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Related Experiment Videos

Community-based active case finding for tuberculosis in rural western China: a cross-sectional study.

C Chen1, C-G Yang2, X Gao3

  • 1Aeras, Beijing, China, Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.

The International Journal of Tuberculosis and Lung Disease : the Official Journal of the International Union Against Tuberculosis and Lung Disease
|October 18, 2017
PubMed
Summary

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Active case finding (ACF) using community-based symptom screening and laboratory tests significantly increased tuberculosis case detection in rural China. This approach is feasible and effective, identifying substantially more cases than passive surveillance.

Area of Science:

  • Public Health
  • Infectious Disease Epidemiology
  • Global Health

Background:

  • Passive case finding strategies are insufficient for identifying tuberculosis (TB) patients in rural China.
  • Effective strategies are needed to improve TB case detection in underserved populations.

Purpose of the Study:

  • To evaluate a community-based active case finding (ACF) scheme for identifying symptomatic individuals with TB in rural China.
  • To assess the feasibility and effectiveness of ACF in increasing TB case detection.

Main Methods:

  • Door-to-door household visits screened residents aged ≥15 years for TB symptoms.
  • Symptomatic individuals provided sputum samples for microscopy, culture, and Xpert® MTB/RIF testing.
  • Chest X-rays were performed on all participants.

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Main Results:

  • Out of 19,334 residents screened, 865 (4.5%) reported symptoms; 52 TB cases were detected.
  • Xpert® MTB/RIF identified all culture-positive cases and three additional diagnoses.
  • Prevalence of newly detected TB was 475 and 196 per 100,000 population, significantly higher than passive surveillance.

Conclusions:

  • Community-based symptom screening combined with laboratory testing is a feasible and effective strategy for increasing TB case finding in rural China.
  • ACF substantially improves upon passive surveillance methods for TB detection in this setting.