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 prioritysetting 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 underdiagnosis and under-reporting. RESULT S: 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. CONCLUS ION: 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.
| Original language | English |
|---|---|
| Pages (from-to) | 356-362 |
| Number of pages | 7 |
| Journal | International Journal of Tuberculosis and Lung Disease |
| Volume | 26 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 1 2022 |
Keywords
- National Tuberculosis Control Programme
- SDG-3
- case notification
- geospatial modeling
- spatial analysis
- survey methods
- tuberculosis
- tuberculosis prevalence survey
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