Community and facility-based tuberculosis control: Programmatic comparison and experience from Nepal
Year: 2018
Type: article
Abstract: Background Successful treatment is an essential aspect of tuberculosis (TB) elimination and prevention against drug resistance. The loss to follow up, and treatment failure is the main causes of poor treatment outcome. To prevent these causes from hindering successful treatment of TB patient and increase adherence to treatment, Community Based Directly Observed Treatment Short course (CB DOTS) program are being promoted. This study aims to compare programmatic treatment outcome for all new TB cases registered in Community Based DOTS and Facility-Based DOTS (FB DOTS) program in districts of Nepal. Methodology Analysis of secondary data was carried out to document the outcome of TB patients registered in 2015-16 in terms of success, loss to follow up, treatment failure, and death for CB DOTS in eleven districts of Nepal using publicly available data. Each CB DOTS district was then matched with 11 FB DOTS district to compare the outcomes. The selection was based on pre-decided criteria like districts from similar geographies, population, and same ecology. Finding Districts in which community-based DOTS was implemented showed better median treatment success rate (92.88%) than facility-based DOTS implemented districts (89.84%) (p = 0.02). The median loss to follow up the rate of community-based DOTS implemented districts (0.92%) was better than the median loss to follow uprate of facility-based DOTS implemented districts (2.967%) (p = 0.02). Conclusion Compared to the Facility-Based DOTS, Community Based DOTS approach was found to be more effective in terms of treatment outcome and adherence to treatment. Community-based treatment is a patient-centered approach for tuberculosis treatment and is found to be more useful to achieve high treatment success rate in countries like Nepal that have rough terrain and limited connectivity to some regions.
Authors: Dev Joshi, Ashish Awasthi, Anurag Saxena, Deepak Saxena, Dileep Mavalankar
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,000
OpenAlex ID: W2885855523
