Please use this identifier to cite or link to this item: https://doi.org/10.1183/23120541.00368-2019
Title: Mobilising community networks for early identification of tuberculosis and treatment initiation in Cambodia: an evaluation of a seed-and-recruit model
Authors: ALVIN TEO KUO JING 
KIESHA PREM 
Tuot, Sovannary
Ork, Chetra
Eng, Sothearith
Pande, Tripti
Chry, Monyrath
HSU LI YANG 
YI SIYAN 
Issue Date: Apr-2020
Publisher: European Respiratory Society (ERS)
Citation: ALVIN TEO KUO JING, KIESHA PREM, Tuot, Sovannary, Ork, Chetra, Eng, Sothearith, Pande, Tripti, Chry, Monyrath, HSU LI YANG, YI SIYAN (2020-04). Mobilising community networks for early identification of tuberculosis and treatment initiation in Cambodia: an evaluation of a seed-and-recruit model. ERJ Open Research 6 (2) : 00368-2019. ScholarBank@NUS Repository. https://doi.org/10.1183/23120541.00368-2019
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
Source Title: ERJ Open Research
URI: https://scholarbank.nus.edu.sg/handle/10635/167838
ISSN: 2312-0541
DOI: 10.1183/23120541.00368-2019
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