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Finding gaps in routine TB surveillance activities in Bangladesh.
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; Reiner, R C.
Afiliação
  • Allorant A; Department of Global Health, University of Washington, Seattle, WA, Institute for Health Metrics and Evaluation, Seattle, WA, USA.
  • Biswas S; International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b), Dhaka, Bangladesh.
  • Ahmed S; International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b), Dhaka, Bangladesh.
  • Wiens KE; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • LeGrand KE; Institute for Health Metrics and Evaluation, Seattle, WA, USA.
  • Janko MM; Institute for Health Metrics and Evaluation, Seattle, WA, USA.
  • Henry NJ; Institute for Health Metrics and Evaluation, Seattle, WA, USA, Big Data Institute, University of Oxford, Oxford, UK.
  • Dangel WJ; Institute for Health Metrics and Evaluation, Seattle, WA, USA.
  • Watson A; Institute for Health Metrics and Evaluation, Seattle, WA, USA.
  • Blacker BF; Institute for Health Metrics and Evaluation, Seattle, WA, USA.
  • Kyu HH; Institute for Health Metrics and Evaluation, Seattle, WA, USA, Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
  • Ross JM; Department of Global Health, University of Washington, Seattle, WA, Department of Medicine, Division of Allergy and Infectious Diseases, University of Washington, Seattle, WA, USA.
  • Rahman MS; International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b), Dhaka, Bangladesh.
  • Hay SI; Institute for Health Metrics and Evaluation, Seattle, WA, USA, Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
  • Reiner RC; Institute for Health Metrics and Evaluation, Seattle, WA, USA, Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Int J Tuberc Lung Dis ; 26(4): 356-362, 2022 04 01.
Article em En | MEDLINE | ID: mdl-35351241
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose Idioma: En Ano de publicação: 2022 Tipo de documento: Article