Evidence map›Paper›PMID 40627783›Full record

ArticlePLoS computational biology2025

Infectivity and fatality of influenza in pre- and post-COVID-19 pandemic year.

Shuanglin Jing, Hao Wang

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. 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
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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

2 authors.

Shuanglin JingSchool of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou, Gansu, China.
Hao WangDepartment of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada.ORCID 0000-0002-4132-6109

Funding

Canada Research Chairs ProgramFoundation for Innovative Fundamental Research Group Project of Gansu ProvinceKey Program of Natural Science in Gansu ProvinceNatural Sciences and Engineering Research Council of Canada
6 · The paper itself

Abstract

The COVID-19 pandemic and related non-pharmaceutical interventions (NPIs) significantly alter the transmission dynamics of non-SARS-CoV-2 infectious diseases, with respiratory infections such as influenza being disproportionately affected. We aim to compare influenza's epidemiological characteristics between pre-pandemic and post-pandemic periods to inform public health responses. We develop two influenza transmission models incorporating age structure and multi-strain dynamics, featuring time-varying transmission and mortality rates. Using publicly available U.S. data, we calibrate these models to evaluate age- and strain-specific transmission patterns and mortality rates across different pandemic eras. Our analysis reveals that during the final pandemic year, influenza transmission among adults ([Formula: see text] years) initially declined but rebounded to pre-pandemic levels within the first post-pandemic year following NPI relaxation and behavioral normalization, while transmission stability persists in the <18 cohort. All-age influenza mortality rates exhibit a transient elevation during the pandemic's final year before returning to baseline levels pre-pandemic. Furthermore, after the COVID-19 pandemic, the transmission rate of influenza A decreases alongside peaks in new cases, while the transmission of influenza B fluctuates without a decline. Our findings indicate that while the COVID-19 pandemic has induced significant transient modifications in influenza's epidemiological profile, key transmission and mortality characteristics regain pre-pandemic equilibrium within one year following pandemic resolution.

Indexed as

COVID-19Influenza, HumanPandemicsAdolescentAdultAgedChildChild, PreschoolComputational BiologyHumansInfantMiddle AgedSARS-CoV-2United StatesYoung Adult

Identifiers

PMID40627783
PMCPMC12251249

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.