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Finding gaps in routine TB surveillance activities in Bangladesh

  • A. Allorant
  • , S. Biswas
  • , S. Ahmed
  • , K. E. Wiens
  • , K. E. LeGrand
  • , M. M. Janko
  • , N. J. Henry
  • , W. J. Dangel
  • , A. Watson
  • , B. F. Blacker
  • , H. H. Kyu
  • , J. M. Ross
  • , M. S. Rahman
  • , S. I. Hay
  • , R. C. Reiner
  • University of Washington
  • International Centre for Diarrhoeal Disease Research Bangladesh
  • Johns Hopkins University
  • University of Oxford

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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 languageEnglish
Pages (from-to)356-362
Number of pages7
JournalInternational Journal of Tuberculosis and Lung Disease
Volume26
Issue number4
DOIs
StatePublished - 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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