Evidence map›Paper›PMID 41561020›Full record

ArticleThe Lancet regional health. Western Pacific2026

Spatio-temporal patterns of tuberculosis revealed by routine

Xiaomei Zhang, Carl J E Suster, Eby M Sim, Connie Lam, Elena Martinez, Taryn Crighton, Ellen J Donnan, Ben J Marais, Vitali Sintchenko

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Lancet regional health. Western Pacific, 2026. 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

9 authors.

Xiaomei ZhangSydney Infectious Diseases Institute (Sydney ID), Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.
Carl J E SusterSydney Infectious Diseases Institute (Sydney ID), Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.
Eby M SimSydney Infectious Diseases Institute (Sydney ID), Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.
Connie LamSydney Infectious Diseases Institute (Sydney ID), Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.
Elena MartinezCentre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Western Sydney Local Health District, Sydney, New South Wales, Australia.
Taryn CrightonCentre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Western Sydney Local Health District, Sydney, New South Wales, Australia.
Ellen J DonnanSydney Infectious Diseases Institute (Sydney ID), Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.
Ben J MaraisSydney Infectious Diseases Institute (Sydney ID), Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.
Vitali SintchenkoSydney Infectious Diseases Institute (Sydney ID), Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tuberculosis (TB) remains a global public health challenge. Even low-incidence countries, like Australia, are struggling to achieve ambitious targets to eliminate local TB transmission. Whole genome sequencing (WGS) of Methods: WGS and geolocation data from 2492 Findings: Most notified TB cases were successfully sequenced and geolocated, with 88.3% (2200/2492) residing in metropolitan Sydney. The local health districts (LHDs) with the highest case counts were South Western (523/2492, 21.0%) and Western Sydney (476/2492, 19.1%). Using a 5-SNP threshold, WGS identified 106 putative transmission clusters involving 288 cases (11.7%), with 50% spanning multiple LHDs. Eight large clusters (≥5 members) were identified, containing 64 cases (2.6%). The largest cluster (17 members) was caused by a Lineage 1 strain, although most large clusters were associated with Lineage 2 strains; two were isoniazid resistant. There was poor correlation between genetic and geographic distances, which showed some improvement with removal of outliers. Most recent common ancestor estimates suggested recent introduction of strains associated with local transmission. Strain clustering and lineage-through-time analyses revealed temporal patterns in cluster expansion and contraction, facilitating accurate monitoring of cluster spread across all of NSW. Interpretation: The findings demonstrate the added value of integrating genomic and spatiotemporal clustering data to detect persistent transmission and guide targeted interventions to pursue the aspirational goal of "zero local TB transmission". Funding: NHMRC Centre for Research Excellence in Tuberculosis (www.tbcre.org.au) and New South Wales Health Prevention Research Support Program.

Indexed as

Dated phylogenyLow-incidence settingsRoutine whole genome sequencingSpatiotemporal analysisTB transmission

Identifiers

PMID41561020
PMCPMC12813591

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Registered trials

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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.