Evidence map›Paper›PMID 34797864›Full record

ArticlePloS one2021

The impact of active case finding on transmission dynamics of tuberculosis: A modelling study.

Diepreye Victoria Ayabina, M Gabriela M Gomes, Nhung Viet Nguyen, Luan Vo, Suvesh Shreshta, Anil Thapa, Andrew James Codlin, Gokul Mishra, Maxine Caws

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.3field-weighted citation impact, top 38% of its field
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

11 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Genomic epidemiology ofMicrobial genomics · 2026
    Article
  3. Article
  4. Assessing the TB Mukt Gram Panchayat Program in Rajasthan: A Way toward Tuberculosis Elimination.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2025
    Article
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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

9 authors at 3 institutions in 3 countries.

Diepreye Victoria AyabinaLiverpool School of Tropical Medicine, Liverpool, United Kingdom.ORCID 0000-0002-7005-6734
M Gabriela M GomesLiverpool School of Tropical Medicine, Liverpool, United Kingdom.
Nhung Viet NguyenNational Tuberculosis Control Programme of Vietnam- National Lung Hospital (VNTP-NLH), Hanoi, Vietnam.
Luan VoFriends for International TB Relief (FIT), Ho Chi Minh City, Vietnam.ORCID 0000-0002-5937-6286
Suvesh ShreshtaSave the Children, Kathmandu, Nepal.
Anil ThapaNational TB Control Centre, Thimi, Kathmandu, Nepal.
Andrew James CodlinFriends for International TB Relief (FIT), Ho Chi Minh City, Vietnam.
Gokul MishraLiverpool School of Tropical Medicine, Liverpool, United Kingdom.
Maxine CawsLiverpool School of Tropical Medicine, Liverpool, United Kingdom.
Liverpool School of Tropical Medicine · GBHanoi Lung Hospital · VNUniversidade do Porto · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence for the benefits of ACF to individuals and communities in the broader context. However, there remains no quantification of the impact of ACF with regards to reducing the burden of transmission. We sought to address this knowledge gap and quantify the potential impact of active case finding on reducing transmission of TB at the national scale and further, to determine the intensification of intervention efforts required to bring the reproduction number (R0) below 1 for TB.

methodsWe adopt a dynamic transmission model that incorporates heterogeneity in risk to TB to assess the impact of an ACF programme (IMPACT TB) on reducing TB incidence in Vietnam and Nepal. We fit the models to country-level incidence data using a Bayesian Markov Chain Monte Carlo approach. We assess the impact of ACF using a parameter in our model, which we term the treatment success rate. Using programmatic data, we estimate how much this parameter has increased as a result of IMPACT TB in the implementation districts of Vietnam and Nepal and quantify additional efforts needed to eliminate transmission of TB in these countries by 2035.

resultsExtending the IMPACT TB programme to national coverage would lead to moderate decreases in TB incidence and would not be enough to interrupt transmission by 2035. Decreasing transmission sufficiently to bring the reproduction number (R0) below 1, would require a further intensification of current efforts, even at the sub-national level.

conclusionsActive case finding programmes are effective in reducing TB in the short term. However, interruption of transmission in high-burden countries, like Vietnam and Nepal, will require comprehensive incremental efforts. Complementary measures to reduce progression from infection to disease, and reactivation of latent infection, are needed to meet the WHO End TB incidence targets.

Indexed as

Models, BiologicalBasic Reproduction NumberHumansIncidenceNepalRisk FactorsRisk Reduction BehaviorTuberculosisVietnam

Identifiers

PMID34797864
PMCPMC8604297
OpenAlexW3212280928

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.