Evidence map›Paper›PMID 41818142›Full record

ArticleMMWR. Morbidity and mortality weekly report2026

Interim Estimates of 2025-26 Seasonal Influenza Vaccine Effectiveness - California, October 2025-January 2026.

Sophie Zhu, Joshua Quint, Tomás M León, Nancy J Li, Shantel Muldrew, Charsey Porse, Brendan Flannery, Sascha Ellington, Erin L Murray, Darpun Sachdev and 2 more

Abstract read
In one paragraph

Article in MMWR. Morbidity and mortality weekly report, 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

12 authors.

Sophie Zhu
Joshua Quint
Tomás M León
Nancy J Li
Shantel Muldrew
Charsey Porse
Brendan Flannery
Sascha Ellington
Erin L Murray
Darpun Sachdev
Kalyani McCullough
Robert Schechter

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interim estimates of state-level influenza vaccine effectiveness (VE) can help guide timely local public health actions for prevention and treatment of influenza. Linked influenza vaccination and public health influenza surveillance data from California allowed estimation of interim influenza VE by comparing the odds of seasonal influenza vaccination among persons who received positive and negative influenza test results reported to the California Department of Public Health (CDPH) using a case-control study design. During October 1, 2025-January 31, 2026, a total of 952,765 influenza laboratory test results were reported to CDPH. These data were analyzed, including results for 86,369 (9%) persons with receipt of a positive influenza test result (case-patients) and 866,396 (91%) with receipt of a negative test result (control patients). Overall, 22% of case-patients and 27% of control patients were vaccinated against influenza. Interim VE against any influenza was 33% for all age groups, 39% for children and adolescents aged 6 months-17 years, and 22% for adults aged ≥65 years; VE was 32% against a positive influenza A test result, and 47% against a positive influenza B test result. These results suggest that influenza vaccination was associated with reduced odds for laboratory-confirmed influenza among children and adults. CDPH recommends annual influenza vaccination for all persons aged ≥6 months to reduce the risk for influenza and influenza-associated adverse health outcomes.

Indexed as

Influenza, HumanInfluenza VaccinesPopulation SurveillanceVaccine EfficacyAdolescentAdultAgedCaliforniaCase-Control StudiesChildChild, PreschoolFemaleHumansInfantInfluenza B virusMaleInfluenza Vaccines

Identifiers

PMID41818142
PMCPMC13211850

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.