Mobilising community networks for early identification of tuberculosis and treatment initiation in Cambodia: an evaluation of a seed-and-recruit model
ALVIN TEO KUO JING KIESHA PREM Tuot, Sovannary Ork, Chetra Eng, Sothearith Pande, Tripti Chry, Monyrath HSU LI YANG YI SIYAN
Tuot, Sovannary
Ork, Chetra
Eng, Sothearith
Pande, Tripti
Chry, Monyrath
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Abstract
Background and objectives: The effects of active case finding (ACF) models that mobilise community networks for early identification and treatment of tuberculosis (TB) remain unknown. We investigated and compared the effect of community-based ACF using a seed-and-recruit model with one-off roving ACF and passive case finding (PCF) on the time to treatment initiation and identification of bacteriologically confirmed TB. Methods: In this retrospective cohort study conducted in 12 operational districts in Cambodia, we assessed relationships between ACF models and: 1) the time to treatment initiation using Cox proportional hazards regression; and 2) the identification of bacteriologically confirmed TB using modified Poisson regression with robust sandwich variance. Results: We included 728 adults with TB, of whom 36% were identified via the community-based ACF using a seed-and-recruit model. We found community-based ACF using a seed-and-recruit model was associated with shorter delay to treatment initiation compared to one-off roving ACF (hazard ratio 0.81, 95% CI 0.68–0.96). Compared to one-off roving ACF and PCF, community-based ACF using a seed-andrecruit model was 45% (prevalence ratio (PR) 1.45, 95% CI 1.19–1.78) and 39% (PR 1.39, 95% CI 0.99–1.94) more likely to find and detect bacteriologically confirmed TB, respectively. Conclusion: Mobilising community networks to find TB cases was associated with early initiation of TB treatment in Cambodia. This approach was more likely to find bacteriologicall
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ERJ Open Research
Publisher
European Respiratory Society (ERS)
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Date
2020-04
DOI
10.1183/23120541.00368-2019
Type
Article