Evidence map›Paper›PMID 41867188›Full record

ArticlemedRxiv : the preprint server for health sciences2026

The Representativeness of Regional Influenza Virus Genomic Surveillance for National Trends in the United States.

Manon Ragonnet-Cronin, Leigh Papalambros, Emily E Bendall, William J Fitzsimmons, Christopher N Blair, Robert Tibbetts, Ashish Bhargava, Adam Lauring

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Manon Ragonnet-CroninDepartment of Ecology & Evolution, University of Chicago, Chicago, IL.ORCID 0000-0002-4879-2209
Leigh PapalambrosDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
Emily E BendallDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.ORCID 0000-0003-2524-088X
William J FitzsimmonsDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
Christopher N BlairDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
Robert TibbettsDepartment of Pathology and Laboratory Medicine, Henry Ford Health, Detroit, MI.
Ashish BhargavaThomas Mackey Center for Infectious Disease Research, Henry Ford St. John Hospital, Gross Pointe Woods, MI.ORCID 0000-0001-6326-0908
Adam LauringDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.ORCID 0000-0003-2906-8335

Funding

NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00015 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI HENSLEY, SCOTT · 2021 to 2025
$50.7M
The Michigan Infectious Disease Genomics (MIDGE) CenterU19AI181767 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LAURING, ADAM, SNITKIN, EVAN · 2024 to 2024
$6.2M
NIAID NIH HHS U19 AI181767NIH HHS 75N93021C00015
6 · The paper itself

Abstract

Genomic surveillance of influenza viruses informs vaccine strain selection and evolutionary forecasting. Sequencing efforts vary widely across U.S. states, which raises concerns about spatial sampling bias. We evaluated how well 10,958 influenza virus genomes sampled by our group in Michigan captured the genetic diversity in 34,743 genomes circulating nationally from the 2021/22 through 2024/25 seasons. We defined seasonal hemagglutinin haplotypes and tracked their detection across states. A small number of haplotypes dominated each season, and Michigan detected all major haplotypes, even under substantial downsampling. Detection delays were primarily driven by haplotype frequency rather than geographic factors. Comparisons across states showed that higher sequencing effort improved coverage and detection timeliness, with diminishing returns at higher volumes. Rarefaction analysis confirmed that relatively few sequences were needed to capture 95% of national haplotype diversity. These findings suggest that intensive sequencing in a single well-sampled location can be broadly representative of national influenza diversity.

Indexed as

hemagglutinininfluenzaphylogenyPublic health surveillancesequence analysis

Identifiers

PMID41867188
PMCPMC13004091

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.