Evidence map›Paper›PMID 32014080›Full record

ArticleEpidemiology and infection2020

Comparison of routine field epidemiology and whole genome sequencing to identify tuberculosis transmission in a remote setting.

J L Guthrie, L Strudwick, B Roberts, M Allen, J McFadzen, D Roth, D Jorgensen, M Rodrigues, P Tang, B Hanley and 3 more

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Epidemiology and infection, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Long-term refined genomic analysis of tuberculosis clusters to distinguish between ongoing transmission, reactivations or diagnostic delays, Almería, Spain, 2003 to 2024.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
    Article
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  3. Transmission ofFrontiers in public health · 2023
    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

13 authors.

J L GuthrieSchool of Population and Public Health, University of British Columbia, Vancouver, Canada.ORCID 0000-0001-8565-203X
L StrudwickYukon Communicable Disease Control, Health and Social Services, Government of Yukon, Whitehorse, Canada.
B RobertsYukon Communicable Disease Control, Health and Social Services, Government of Yukon, Whitehorse, Canada.
M AllenYukon Communicable Disease Control, Health and Social Services, Government of Yukon, Whitehorse, Canada.
J McFadzenYukon Communicable Disease Control, Health and Social Services, Government of Yukon, Whitehorse, Canada.
D RothBritish Columbia Centre for Disease Control, Vancouver, Canada.
D JorgensenBritish Columbia Centre for Disease Control, Public Health Laboratory, Vancouver, Canada.
M RodriguesBritish Columbia Centre for Disease Control, Public Health Laboratory, Vancouver, Canada.
P TangDepartment of Pathology, Sidra Medical and Research Center, Doha, Qatar.
B HanleyDepartment of Health and Social Services, Government of Yukon, Whitehorse, Canada.
J JohnstonBritish Columbia Centre for Disease Control, Vancouver, Canada.
V J CookBritish Columbia Centre for Disease Control, Vancouver, Canada.
J L GardySchool of Population and Public Health, University of British Columbia, Vancouver, Canada.

Funding

CIHR
6 · The paper itself

Abstract

Yukon Territory (YT) is a remote region in northern Canada with ongoing spread of tuberculosis (TB). To explore the utility of whole genome sequencing (WGS) for TB surveillance and monitoring in a setting with detailed contact tracing and interview data, we used a mixed-methods approach. Our analysis included all culture-confirmed cases in YT (2005-2014) and incorporated data from 24-locus Mycobacterial Interspersed Repetitive Units-Variable Number of Tandem Repeats (MIRU-VNTR) genotyping, WGS and contact tracing. We compared field-based (contact investigation (CI) data + MIRU-VNTR) and genomic-based (WGS + MIRU-VNTR + basic case data) investigations to identify the most likely source of each person's TB and assessed the knowledge, attitudes and practices of programme personnel around genotyping and genomics using online, multiple-choice surveys (n = 4) and an in-person group interview (n = 5). Field- and genomics-based approaches agreed for 26 of 32 (81%) cases on likely location of TB acquisition. There was less agreement in the identification of specific source cases (13/22 or 59% of cases). Single-locus MIRU-VNTR variants and limited genetic diversity complicated the analysis. Qualitative data indicated that participants viewed genomic epidemiology as a useful tool to streamline investigations, particularly in differentiating latent TB reactivation from the recent transmission. Based on this, genomic data could be used to enhance CIs, focus resources, target interventions and aid in TB programme evaluation.

Indexed as

Contact TracingDisease Transmission, InfectiousGenotypeHumansMolecular EpidemiologyMolecular TypingMycobacteriumTuberculosisWhole Genome SequencingYukon TerritoryEpidemiologyprogramme assessmenttransmissiontuberculosis (TB)whole genome sequencing

Identifiers

PMID32014080
PMCPMC7019559

What OpenQuestion holds

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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.