Evidence map›Paper›PMID 42396301›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Durability and Seasonal Variation in the Effectiveness of Nirsevimab over Three Seasons in Connecticut.

Hanmeng Xu, Camilla Aparicio-Llorente, Joshua L Warren, Lee Kennedy-Shaffer, Virginia E Pitzer, Daniel M Weinberger, Carlos R Oliveira, PROVE-ID Group Authors

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.

Hanmeng XuDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.ORCID 0009-0000-2805-0171
Camilla Aparicio-LlorenteDepartment of Pediatrics, Section of Infectious Diseases and Global Health, Yale School of Medicine, New Haven, CT, USA.
Joshua L WarrenDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Lee Kennedy-ShafferDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.ORCID 0000-0001-7604-3638
Virginia E PitzerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Daniel M WeinbergerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Carlos R OliveiraDepartment of Pediatrics, Section of Infectious Diseases and Global Health, Yale School of Medicine, New Haven, CT, USA.ORCID 0000-0003-1897-6581
PROVE-ID Group Authors

Funding

Predicting and monitoring variations in the effects of vaccines against RSVR01AI137093 · NIAID · YALE UNIVERSITY · PI Virginia E Pitzer, Daniel Martin Weinberger · 2018 to 2026
$3.4M
Real-World Effectiveness of Perinatal RSV ImmunoprophylaxisR01AI179874 · NIAID · YALE UNIVERSITY · PI Carlos Rafael Oliveira · 2024 to 2026
$2.5M
NIAID NIH HHS R01 AI137093NIAID NIH HHS R01 AI179874
6 · The paper itself

Abstract

Background: Nirsevimab has been widely administered in the United States since 2023 to protect infants and young children from severe disease caused by respiratory syncytial virus (RSV). Although early post-licensure studies have shown high effectiveness against medically attended RSV infection, uncertainty remains about the durability of protection, effectiveness beyond the first RSV season, and the extent to which changing RSV seasonality influences real-world effectiveness. Objective: To estimate the effectiveness of nirsevimab against medically attended RSV infection across three consecutive RSV seasons and to examine how effectiveness varies by season and time since immunization. Methods: We conducted a test-negative case-control study utilizing electronic health records of infants and young children tested for RSV by polymerase chain reaction in outpatient and inpatient settings within the Yale New Haven Health System between October 1, 2023, and March 1, 2026. Effectiveness of nirsevimab was estimated using multivariable logistic regression, adjusting for age, weekly RSV activity, pre-existing risk factors, and other potential confounders. Variation in effectiveness was examined by season, encounter setting, and time since immunization up to 24 months. Results: Overall, 17,755 infants and young children were tested for RSV infection, of whom 2,388 (13.4%) were cases and 15,367 (86.6%) were controls. The overall effectiveness of nirsevimab was 67.3% (95% confidence interval [CI]: 59.8, 73.3%) against all medically-attended RSV infections, 60.2% (95% CI: 49.6, 68.5%) against RSV-associated outpatient visits, and 88.9% (95% CI: 82.3, 93.0%) against RSV-associated hospitalization. Effectiveness against medically attended RSV infection declined across seasons, from 76.7% (95% CI: 60.5, 86.3%) in 2023/24 to 54.4% (95% CI: 33.0, 68.9%) in 2025/26. Lower season-specific effectiveness in later seasons corresponded with progressively delayed RSV activity over. Protection against RSV-associated hospitalization declined with increasing time since immunization, from 92.5% (95% credible interval [CrI]: 85.9, 96.4%) at 1 month, to 77.2% (95% CrI: 60.4, 87.6%) at 6 months, and 39.9% (95% CrI: 2.4, 63.3%) at 12 months post-immunization, after which effectiveness plateaued. Conclusions: Nirsevimab remained effective against RSV-associated hospitalization through 6 to 12 months after immunization. Delayed RSV activity was associated with lower effectiveness, highlighting the importance of aligning administration with local RSV circulation.

Identifiers

PMID42396301
PMCPMC13321200

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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.