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Finding gaps in routine TB surveillance activities in Bangladesh

Finding gaps in routine TB surveillance activities in Bangladesh
Finding gaps in routine TB surveillance activities in Bangladesh
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.
National Tuberculosis Control Programme, SDG-3, case notification, geospatial modeling, spatial analysis, survey methods, tuberculosis, tuberculosis prevalence survey
1027-3719
356-362
Allorant, A.
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Biswas, S.
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Ahmed, S.
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Wiens, K. E.
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LeGrand, K. E.
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Janko, M. M.
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Henry, N. J.
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Dangel, W. J.
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Watson, A.
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Blacker, B. F.
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Kyu, H. H.
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Ross, J. M.
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Rahman, M. S.
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Hay, S. I.
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Reiner, R. C.
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Allorant, A.
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Biswas, S.
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Ahmed, S.
b373ece4-6f89-4197-a2c9-4dd4a301be81
Wiens, K. E.
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LeGrand, K. E.
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Janko, M. M.
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Henry, N. J.
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Dangel, W. J.
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Watson, A.
e6e342bb-dd1d-485c-8ba9-a1efec015392
Blacker, B. F.
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Kyu, H. H.
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Ross, J. M.
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Rahman, M. S.
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Hay, S. I.
ad00c295-7b71-4d56-83d5-2c936e6b77d2
Reiner, R. C.
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Allorant, A., Biswas, S., Ahmed, S., Wiens, K. E., LeGrand, K. E., Janko, M. M., Henry, N. J., Dangel, W. J., Watson, A., Blacker, B. F., Kyu, H. H., Ross, J. M., Rahman, M. S., Hay, S. I. and Reiner, R. C. (2022) Finding gaps in routine TB surveillance activities in Bangladesh. International Journal of Tuberculosis and Lung Disease, 26 (4), 356-362. (doi:10.5588/ijtld.21.0624).

Record type: Article

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.

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More information

Accepted/In Press date: 7 November 2021
Published date: 1 April 2022
Keywords: National Tuberculosis Control Programme, SDG-3, case notification, geospatial modeling, spatial analysis, survey methods, tuberculosis, tuberculosis prevalence survey

Identifiers

Local EPrints ID: 496303
URI: http://eprints.soton.ac.uk/id/eprint/496303
ISSN: 1027-3719
PURE UUID: b75e128c-49ae-43de-897a-94893c52cb1d
ORCID for A. Allorant: ORCID iD orcid.org/0000-0002-9663-7561
ORCID for S. Biswas: ORCID iD orcid.org/0000-0002-0357-5796

Catalogue record

Date deposited: 11 Dec 2024 17:38
Last modified: 14 Dec 2024 03:14

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Contributors

Author: A. Allorant ORCID iD
Author: S. Biswas ORCID iD
Author: S. Ahmed
Author: K. E. Wiens
Author: K. E. LeGrand
Author: M. M. Janko
Author: N. J. Henry
Author: W. J. Dangel
Author: A. Watson
Author: B. F. Blacker
Author: H. H. Kyu
Author: J. M. Ross
Author: M. S. Rahman
Author: S. I. Hay
Author: R. C. Reiner

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