Evidence map›Paper›PMID 40795091›Full record

ArticleThe Journal of infectious diseases2025

Impact of Case Detection and COVID-19-Related Disruptions on Tuberculosis in Vietnam: A Modeling Analysis.

Viet Long Bui, Romain Ragonnet, Angus E Hughes, David S Shipman, Emma S McBryde, Binh Hoa Nguyen, Hoang Nam Do, Thai Son Ha, Greg J Fox, James M Trauer

Abstract read
In one paragraph

Article in The Journal of infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Viet Long BuiSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0001-9997-593X
Romain RagonnetSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0001-8520-2362
Angus E HughesSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
David S ShipmanSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Emma S McBrydeCentre for Clinical Research, The University of Queensland, Brisbane, Queensland, Australia.ORCID 0000-0002-9570-9172
Binh Hoa NguyenNational Lung Hospital, Ha Noi, Vietnam.ORCID 0000-0002-1543-4907
Hoang Nam DoNational Lung Hospital, Ha Noi, Vietnam.
Thai Son HaAdministration of Medical Services, Ministry of Health, Ha Noi, Vietnam.
Greg J FoxFaculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
James M TrauerSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-0991-1631

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVietnam, a high-burden tuberculosis (TB) country, experienced marked declines in TB notifications during the COVID-19 pandemic. We assessed the impact of pandemic-related disruptions on TB case detection and transmission using a dynamic transmission model calibrated to local demographic and epidemiological observations.

methodsWe developed an age-structured compartmental TB transmission model to estimate COVID-19's impact on TB in Vietnam. Four model assumptions reflecting reductions in detection and/or transmission were calibrated to notification data, with the best-fitting assumption used for future projections and to evaluate the effects of enhanced case detection scenarios.

resultsCOVID-19 significantly disrupted TB services in Vietnam, resulting in an estimated 2000 additional TB episodes (95% credible interval [CrI]: 200-5100) and 1100 TB-related deaths (95% CrI: 100-2700) in 2021. By 2035, the cumulative impact of these disruptions could reach 22 000 additional TB episodes (95% CrI: 2200-63 000) and 5900 deaths (95% CrI: 600-16 600) by 2035. We predicted two hypothetical scenarios of enhancing TB case detection. Under the ambitious scenario, enhancing TB case detection could mitigate these potential impacts by preventing 17.8% of new TB episodes (95% CrI: 13.1%-21.9%) and 34.2% (95% CrI: 31.5%-37.0%) of TB-related deaths by 2035, compared with no enhancement.

conclusionsCOVID-19-related disruptions have hindered TB detection in Vietnam, likely causing long-term increases in new TB episodes and deaths. However, the uncertainty around these effects is considerable. Sustained investment in diagnostics, system resilience, and patient-centric policies has the potential to achieve benefits that are substantially larger than these pandemic-related setbacks.

Indexed as

COVID-19TuberculosisAdolescentAdultAgedChildChild, PreschoolFemaleHumansMaleMiddle AgedPandemicsSARS-CoV-2VietnamYoung Adultcase detectioncompartmental modelCOVID-19 pandemicmycobacterium tuberculosistransmission dynamic model

Identifiers

PMID40795091
PMCPMC12526866

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.