ArticleMicrobial genomics2018
Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population.
Article in Microbial genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark.The Lancet. Microbe · 2021Pooled it
- Spatio-temporal patterns of tuberculosis revealed by routineThe Lancet regional health. Western Pacific · 2026Article
- Phylodynamic inference suggests introductions as main driver of Mpox Clade II outbreak in 2022 in Slovenia.Epidemiology and infection · 2025Article
- Phylodynamic assessment of SNP distances from whole genome sequencing for determining Mycobacterium tuberculosis transmission.Scientific reports · 2025Article
- Bayesian estimation of transmission networks for infectious diseases.Journal of mathematical biology · 2025Article
- Global epidemiology of Mycobacterium tuberculosis lineage 4 insights from Ecuadorian genomic data.Scientific reports · 2025Article
- Distribution and transmission of M. tuberculosis in a high-HIV prevalence city in Malawi: A genomic and spatial analysis.PLOS global public health · 2025Article
- Unraveling tuberculosis patient cluster transmission chains: integrating WGS-based network with clinical and epidemiological insights.Frontiers in public health · 2024Article
- ComparingEpidemiology and infection · 2023Article
- TransFlow: a Snakemake workflow for transmission analysis of Mycobacterium tuberculosis whole-genome sequencing data.Bioinformatics (Oxford, England) · 2023Article
- Local and Travel-Associated Transmission of Tuberculosis at Central Western Border of Brazil, 2014-2017.Emerging infectious diseases · 2021Article
- Genomic Epidemiology Analysis of Infectious Disease Outbreaks Using TransPhylo.Current protocols · 2021Article
- Sudden emergence of aMicrobial genomics · 2020Article
- Transmission analysis of a large tuberculosis outbreak in London: a mathematical modelling study using genomic data.Microbial genomics · 2020Article
- Genomic variant-identification methods may alterMicrobial genomics · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In many countries the incidence of tuberculosis (TB) is low and is largely shaped by immigrant populations from high-burden countries. This is the case in Norway, where more than 80 % of TB cases are found among immigrants from high-incidence countries. A variable latent period, low rates of evolution and structured social networks make separating import from within-border transmission a major conundrum to TB control efforts in many low-incidence countries. Clinical Mycobacterium tuberculosis isolates belonging to an unusually large genotype cluster associated with people born in the Horn of Africa have been identified in Norway over the last two decades. We modelled transmission based on whole-genome sequence data to estimate infection times for individual patients. By contrasting these estimates with time of arrival in Norway, we estimate on a case-by-case basis whether patients were likely to have been infected before or after arrival. Independent import was responsible for the majority of cases, but we estimate that about one-quarter of the patients had contracted TB in Norway. This study illuminates the transmission dynamics within an immigrant community. Our approach is broadly applicable to many settings where TB control programmes can benefit from understanding when and where patients acquired TB.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.