Evidence map›Paper›PMID 40346656›Full record

ArticleGenome medicine2025

The TyphiNET data visualisation dashboard: unlocking Salmonella Typhi genomics data to support public health.

Zoe A Dyson, Louise Cerdeira, Vandana Sharma, Megan E Carey, Kathryn E Holt, Global Typhoid Genomics Consortium

Abstract read
In one paragraph

Article in Genome medicine, 2025. 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. Article
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  5. Observational
  6. Laboratory epidemiology ofOne health (Amsterdam, Netherlands) · 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

6 authors.

Zoe A Dyson *Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK. zoe.dyson@lshtm.ac.uk.
Louise Cerdeira *Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Vandana SharmaDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Megan E CareyDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Kathryn E HoltDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK. kat.holt@lshtm.ac.uk.
Global Typhoid Genomics Consortium

Funding

Technology CoreU19AI110820 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI DUNNING HOTOPP, JULIE · 2014 to 2023
$36.5M
Horizon 2020 Framework Programme 845681NIAID NIH HHS U19 AI110820Wellcome TrustWellcome Trust 219692/Z/19/Z & 226432/Z/22/Z
6 · The paper itself

Abstract

backgroundSalmonella enterica subspecies enterica serovar Typhi (abbreviated as 'Typhi') is the bacterial agent of typhoid fever. Effective antimicrobial therapy reduces complications and mortality; however, antimicrobial resistance (AMR) is a major problem in many endemic countries. Prevention through vaccination is possible through recently-licensed typhoid conjugate vaccines (TCVs). National immunisation programs are currently being considered or deployed in several countries where AMR prevalence is known to be high, and the Gavi vaccine alliance has provided financial support for their introduction. Pathogen whole genome sequence data are a rich source of information on Typhi variants (genotypes or lineages), AMR prevalence, and mechanisms. However, this information is currently not readily accessible to non-genomics experts, including those driving vaccine implementation or empirical therapy guidance.

resultsWe developed TyphiNET ( https://www.typhi.net ), an interactive online dashboard for exploring Typhi genotype and AMR distributions derived from publicly available pathogen genome sequences. TyphiNET allows users to explore country-level summaries such as the frequency of pathogen lineages, temporal trends in resistance to clinically relevant antimicrobials, and the specific variants and mechanisms underlying emergent AMR trends. User-driven plots and session reports can be downloaded for ease of sharing. Importantly, TyphiNET is populated by high-quality genome data curated by the Global Typhoid Pathogen Genomics Consortium, analysed using the Pathogenwatch platform, and identified as coming from non-targeted sampling frames that are suitable for estimating AMR prevalence amongst Typhi infections (no personal data is included in the platform). As of February 2024, data from a total of n = 11,836 genomes from 101 countries are available in TyphiNET. We outline case studies illustrating how the dashboard can be used to explore these data and gain insights of relevance to both researchers and public health policy-makers.

conclusionsThe TyphiNET dashboard provides an interactive platform for accessing genome-derived data on pathogen variant frequencies to inform typhoid control and intervention strategies. The platform is extensible in terms of both data and features, and provides a model for making complex bacterial genome-derived data accessible to a wide audience.

Indexed as

Genome, BacterialGenomicsPublic HealthSalmonella typhiTyphoid FeverAnti-Bacterial AgentsDrug Resistance, BacterialGenotypeHumansAnti-Bacterial AgentsAntimicrobial ResistanceDashboardGenetic epidemiologyGenomicsSalmonella TyphiSurveillanceTyphoid feverWeb applicationWhole Genome Sequencing

Identifiers

PMID40346656
PMCPMC12063449

What OpenQuestion holds

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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.