1. Finding gaps in routine TB surveillance activities in Bangladesh.
- Author
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Allorant A, Biswas S, Ahmed S, Wiens KE, LeGrand KE, Janko MM, Henry NJ, Dangel WJ, Watson A, Blacker BF, Kyu HH, Ross JM, Rahman MS, Hay SI, and Reiner RC
- Subjects
- Bangladesh epidemiology, Bayes Theorem, Cross-Sectional Studies, Humans, Prevalence, Tuberculosis diagnosis, Tuberculosis epidemiology, Tuberculosis prevention & control
- Abstract
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.
- Published
- 2022
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