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Int J Tuberc Lung Dis ; 26(4): 356-362, 2022 04 01.
Artículo en Inglés | MEDLINE | ID: mdl-35351241

RESUMEN

BACKGROUND: TB was the leading cause of death from a single infectious pathogen globally between 2014 and 2019. Fine-scale estimates of TB prevalence and case notifications can be combined to guide priority-setting for strengthening routine surveillance activities in high-burden countries. We produce policy-relevant estimates of the TB epidemic at the second administrative unit in Bangladesh.METHODS: We used a Bayesian spatial framework and the cross-sectional National TB Prevalence Survey from 2015-2016 in Bangladesh to estimate prevalence by district. We used case notifications to calculate prevalence-to-notification ratio, a key metric of under-diagnosis and under-reporting.RESULTS: TB prevalence rates were highest in the north-eastern districts and ranged from 160 cases per 100,000 (95% uncertainty interval [UI] 80-310) in Jashore to 840 (UI 690-1020) in Sunamganj. Despite moderate prevalence rates, the Rajshahi and Dhaka Divisions presented the highest prevalence-to-notification ratios due to low case notifications. Resolving subnational disparities in case detection could lead to 26,500 additional TB cases (UI 8,500-79,400) notified every year.CONCLUSION: This study is the first to produce and map subnational estimates of TB prevalence and prevalence-to-notification ratios, which are essential to target prevention and treatment efforts in high-burden settings. Reaching TB cases currently missing from care will be key to ending the TB epidemic.


Asunto(s)
Tuberculosis , Bangladesh/epidemiología , Teorema de Bayes , Estudios Transversales , Humanos , Prevalencia , Tuberculosis/diagnóstico , Tuberculosis/epidemiología , Tuberculosis/prevención & control
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