Evidence map›Paper›PMID 37009521›Full record

ArticleChina CDC weekly2023

SARS-CoV-2 Surveillance Through China Influenza Surveillance Information System - China, December 1, 2022 to February 12, 2023.

Xiaoxu Zeng, Yiran Xie, Xiaokun Yang, Zhibin Peng, Jing Tang, Lei Yang, Shuxia Lin, Jun Han, Yanping Zhang, Dayan Wang

Open access · diamondAbstract read
In one paragraph

Article in China CDC weekly, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
5.1field-weighted citation impact, top 4% of its field
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

24 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
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  7. China's post-zero-COVID Omicron wave: A Bayesian analysis.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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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

10 authors at 3 institutions in 1 country.

Xiaoxu ZengNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; WHO Collaborating Centre for Reference and Research on Influenza, Beijing Municipality, China.
Yiran XieNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; WHO Collaborating Centre for Reference and Research on Influenza, Beijing Municipality, China.
Xiaokun YangChinese Center for Disease Control and Prevention, Beijing Municipality, China.
Zhibin PengChinese Center for Disease Control and Prevention, Beijing Municipality, China.
Jing TangNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; WHO Collaborating Centre for Reference and Research on Influenza, Beijing Municipality, China.
Lei YangNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; WHO Collaborating Centre for Reference and Research on Influenza, Beijing Municipality, China.
Shuxia LinNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; WHO Collaborating Centre for Reference and Research on Influenza, Beijing Municipality, China.
Jun HanNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; WHO Collaborating Centre for Reference and Research on Influenza, Beijing Municipality, China.
Yanping ZhangChinese Center for Disease Control and Prevention, Beijing Municipality, China.
Dayan WangNational Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; WHO Collaborating Centre for Reference and Research on Influenza, Beijing Municipality, China.
National Institute for Viral Disease Control and Prevention · CNChinese Center For Disease Control and Prevention · CNNational Health and Family Planning Commission · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The World Health Organization (WHO) proposed using influenza surveillance systems to carry out coronavirus disease 2019 (COVID-19) surveillance due to the similarity between the two diseases in some respiratory symptoms. To assess the prevalence of COVID-19, we analyzed the influenza-like illness (ILI) and positive rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detections in ILI patients reported to the influenza Surveillance Information System (CNISIS) since late 2022. Methods: Data related to ILI were reported by national surveillance sentinel hospitals. Positive testing for SARS-CoV-2 and influenza viruses was conducted using real-time reverse transcription polymerase chain reaction (rRT-PCR) detection by the national influenza surveillance network laboratories. Surveillance data were reported to CNISIS. Results: Beginning on December 12, 2022 (Week 50), the ILI percentage increased dramatically, peaking in Week 51 at 12.1%. Subsequently, the ILI percentage began to decline rapidly from Week 52, 2022, and by Week 6, 2023 (February 6-12), the ILI and ILI percentage had returned to the levels observed at the beginning of December 2022. From December 1, 2022 to February 12, 2023, 115,844 specimens were tested for both SARS-CoV-2 and influenza virus. Of these, 30,381 (26.2%) were positive for SARS-CoV-2 and 1,763 (1.5%) were positive for influenza virus. The positive rate of SARS-CoV-2 tests peaked at 74.1% around December 23 and 25. Conclusions: Sentinel-based surveillance, previously established for influenza, is an effective way to track the circulation trend of SARS-CoV-2 during community-level epidemics. There was no co-prevalence of SARS-CoV-2 and influenza virus during the outbreak of SARS-CoV-2, even during the winter influenza season. However, it is important to remain vigilant for the potential rise of influenza activities following the COVID-19 epidemic.

Indexed as

COVID-19ILISARS-CoV-2surveillances

Identifiers

PMID37009521
PMCPMC10061762
OpenAlexW4321217306

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

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.