Evidence map›Paper›PMID 37215632›Full record

ArticlePNAS nexus2023

Quantifying the rebound of influenza epidemics after the adjustment of zero-COVID policy in China.

Hao Lei, Lei Yang, Mengya Yang, Jing Tang, Jiaying Yang, Minju Tan, Shigui Yang, Dayan Wang, Yuelong Shu

Abstract read
In one paragraph

Article in PNAS nexus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  16. Changing patterns of infectious diseases in children during the COVID-19 pandemic.Frontiers in cellular and infection microbiology · 2023
    Review
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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

9 authors.

Hao LeiSchool of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, P.R. China.ORCID https://orcid.org/0000-0002-1850-7040
Lei YangNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing 102206, P.R. China.
Mengya YangSchool of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, P.R. China.
Jing TangNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing 102206, P.R. China.
Jiaying YangNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing 102206, P.R. China.
Minju TanNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing 102206, P.R. China.
Shigui YangSchool of Public Health, Zhejiang University School of Medicine, Hangzhou 310058, P.R. China.
Dayan WangNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing 102206, P.R. China.
Yuelong ShuSchool of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coexistence of coronavirus disease 2019 (COVID-19) and seasonal influenza epidemics has become a potential threat to human health, particularly in China in the oncoming season. However, with the relaxation of nonpharmaceutical interventions (NPIs) during the COVID-19 pandemic, the rebound extent of the influenza activities is still poorly understood. In this study, we constructed a susceptible-vaccinated-infectious-recovered-susceptible (SVIRS) model to simulate influenza transmission and calibrated it using influenza surveillance data from 2018 to 2022. We projected the influenza transmission over the next 3 years using the SVIRS model. We observed that, in epidemiological year 2021-2022, the reproduction numbers of influenza in southern and northern China were reduced by 64.0 and 34.5%, respectively, compared with those before the pandemic. The percentage of people susceptible to influenza virus increased by 138.6 and 57.3% in southern and northern China by October 1, 2022, respectively. After relaxing NPIs, the potential accumulation of susceptibility to influenza infection may lead to a large-scale influenza outbreak in the year 2022-2023, the scale of which may be affected by the intensity of the NPIs. And later relaxation of NPIs in the year 2023 would not lead to much larger rebound of influenza activities in the year 2023-2024. To control the influenza epidemic to the prepandemic level after relaxing NPIs, the influenza vaccination rates in southern and northern China should increase to 53.8 and 33.8%, respectively. Vaccination for influenza should be advocated to reduce the potential reemergence of the influenza epidemic in the next few years.

Indexed as

coronavirus disease 2019influenzanonpharmaceutical interventionsreboundvaccination

Identifiers

PMID37215632
PMCPMC10194088

What OpenQuestion holds

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LicenceCC BY
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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.