Evidence map›Paper›PMID 42050905›Full record

ArticleThe Journal of international medical research2026

Impact of coronavirus disease 2019 nonpharmaceutical interventions on influenza epidemiology: A retrospective analysis in Hebei Province, China from 2019 to 2023.

Pei Zhao, Yu Zhang, Jie Wang, Yonghui Li, Mingwen Zhao, Xiaowen Zhang

Abstract read
In one paragraph

Article in The Journal of international medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

6 authors.

Pei ZhaoDepartment of Clinical Laboratory, Hebei General Hospital, China.ORCID 0009-0005-4660-4875
Yu ZhangDepartment of Clinical Laboratory, Hebei General Hospital, China.
Jie WangDepartment of Clinical Laboratory, Hebei General Hospital, China.
Yonghui LiHebei Center for Disease Control and Prevention, China.
Mingwen ZhaoGraduate school, Hebei Medical University, China.
Xiaowen ZhangGraduate school, Hebei Medical University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BackgroundIn this study we retrospectively analyzed the influenza virus antigen detection data from Hebei General Hospital for the period from 2019 to 2023, focusing on the impact of coronavirus disease 2019 nonpharmaceutical interventions on the epidemiology of influenza.MethodsA retrospective analysis was conducted on 45,956 records of patients with influenza-like illness retrieved from the Laboratory Information System of Hebei General Hospital between January 2019 and December 2023. Nasal and pharyngeal swab samples from these patients were tested for influenza A and influenza B virus antigens using colloidal gold immunochromatographic assay.ResultsCompared with the pre-pandemic period, both number of influenza cases and positive detection rates declined substantially during the coronavirus disease 2019 pandemic. Notably, this decline coincided with the peak implementation of nonpharmaceutical interventions aimed at mitigating coronavirus disease 2019 spread. The cases of influenza surged significantly following the relaxation of coronavirus disease 2019 restrictions in 2023 and even approached or exceeded the pre-coronavirus disease 2019 levels.ConclusionsOur findings provide strong evidence that comprehensive nonpharmaceutical interventions implemented to control the transmission of severe acute respiratory syndrome coronavirus-2 also profoundly suppressed seasonal influenza epidemics. The sharp rebound of influenza activity after the relaxation of restrictions underscores the need for integrated preparedness strategies to manage concurrent threats from multiple respiratory viruses.

Indexed as

COVID-19Influenza, HumanChinaHumansInfluenza A virusInfluenza B virusPandemicsRetrospective StudiesSARS-CoV-2coronavirus disease 2019epidemiologyinfluenzaNonpharmaceutical interventions

Identifiers

PMID42050905
PMCPMC13145054

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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.