Finding gaps in routine TB surveillance activities in Bangladesh

Author:

Allorant A.1,Biswas S.2,Ahmed S.2,Wiens K. E.3,LeGrand K. E.4,Janko M. M.4,Henry N. J.5,Dangel W. J.4,Watson A.4,Blacker B. F.4,Kyu H. H.6,Ross J. M.7,Rahman M. S.2,Hay S. I.6,Reiner R. C.6

Affiliation:

1. Department of Global Health, University of Washington, Seattle, WA, Institute for Health Metrics and Evaluation, Seattle, WA, USA

2. International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b), Dhaka, Bangladesh

3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

4. Institute for Health Metrics and Evaluation, Seattle, WA, USA

5. Institute for Health Metrics and Evaluation, Seattle, WA, USA, Big Data Institute, University of Oxford, Oxford, UK

6. Institute for Health Metrics and Evaluation, Seattle, WA, USA, Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA

7. Department of Global Health, University of Washington, Seattle, WA, Department of Medicine, Division of Allergy and Infectious Diseases, University of Washington, Seattle, WA, USA

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.

Publisher

International Union Against Tuberculosis and Lung Disease

Subject

Infectious Diseases,Pulmonary and Respiratory Medicine

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