Evidence map›Paper›PMID 39346692›Full record

ArticleChina CDC weekly2024

Two Peaks of Seasonal Influenza Epidemics - China, 2023.

Yiran Xie, Shuxia Lin, Xiaoxu Zeng, Jing Tang, Yanhui Cheng, Weijuan Huang, Jiandong Li, Dayan Wang

Abstract read
In one paragraph

Article in China CDC weekly, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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

8 authors.

Yiran XieNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Shuxia LinNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaoxu ZengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Jing TangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yanhui ChengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Weijuan HuangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Jiandong LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Dayan WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Disease, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Influenza is a communicable respiratory disease that causes annual epidemics and occasional unpredictable pandemics. This study examines the occurrence of two unexpected influenza peaks within the year 2023. Methods: Influenza-like illness (ILI) data were reported, and specimens of ILI were collected by designated surveillance hospitals. Positive cases were confirmed using real-time reverse transcription polymerase chain reaction (rRT-PCR) testing conducted at national surveillance network laboratories. The data were then submitted to the Chinese Influenza Surveillance Information System. Results: From December 2022 to January 2023, influenza activity was minimal until a spring epidemic began in February, peaking in late March. The outbreak spread from the north to the south, with A(H1N1)pdm09 being the predominant strain and A(H3N2) also circulating concurrently. The positivity rate in northern and southern provincial-level administrative divisions (PLADs) reached 60.0% (week 10) and 60.2% (week 13), respectively, before dropping to below 5% from May to August. Subsequently, rates surged starting in week 41 in the south and week 44 in the north, peaking at 54.4% (week 50) and 44.0% (week 49), respectively, and remained high until the end of 2023. A(H3N2) became the prevailing strain, with a notable increase in B/Victoria lineage viruses from December, resulting in two peaks during the 2023 influenza season. Conclusions: The pattern of the influenza epidemic shifted due to the coronavirus disease 2019 (COVID-19) outbreak and is gradually returning to its usual seasonal and intensity patterns. It is, therefore, crucial to continuously strengthen influenza surveillance, enhance the influenza surveillance network, and lay the groundwork for advancing integrated surveillance of multiple pathogens in China.

Indexed as

epidemicsseasonal influenzasurveillance

Identifiers

PMID39346692
PMCPMC11425296

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.