Evidence map›Paper›PMID 35284384›Full record

ArticleFrontiers in public health2022

The Epidemiological Pattern and Co-infection of Influenza A and B by Surveillance Network From 2009 to 2014 in Anhui Province, China.

Jun He, Sai Hou, Yue Chen, Jun-Ling Yu, Qing-Qing Chen, Lan He, Jiang Liu, Lei Gong, Xin-Er Huang, Jia-Bing Wu and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 11 citations in OpenAlex.

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  8. Genomic Surveillance and Evolutionary Dynamics of Influenza A Virus in Sri Lanka.medRxiv : the preprint server for health sciences · 2024
    Article
  9. Article
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

12 authors at 3 institutions in 1 country.

Jun HeMicrobiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Sai HouMicrobiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Yue ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Jun-Ling YuMicrobiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Qing-Qing ChenMicrobiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Lan HeMicrobiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Jiang LiuHuainan City Center for Disease Control and Prevention, Huainan, China.
Lei GongMicrobiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Xin-Er HuangDepartment of Health Inspection and Quarantine, School of Public Health, Anhui Medical University, Hefei, China.
Jia-Bing WuMicrobiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China.
Hai-Feng PanDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.
Rong-Bao GaoNHC Key Laboratory of Biosafety, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Anhui Provincial Center for Disease Control and Prevention · CNAnhui Medical University · CNNational Institute for Viral Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Influenza-like illness (ILI) is one of the most important public health problems globally, causing an enormous disease burden. Influenza infections are the most common cause of ILI. Bacterial and virus co-infection is common yet the data of co-infection with influenza A and B viruses are scarce. To identify the epidemiological patterns of and co-infection of influenza A and B in Anhui province, China, we analyzed the surveillance data of 5 years from 2009 to 2014 collected by the Chinese National influenzas network. The results showed that the weekly ratio of ILI was 3.96 ± 1.9% (95% CI 3.73-4.2%) in outpatients and the highest affected population was children under 5 years old. The epidemic of influenza viruses was highest during 2009-2010. For the other 4 surveillance years, school-aged people (5-14 years) were the most highly affected population. Influenza B and H3N2 viruses were more prevalent than H1N1pdm09 virus after 2010. In addition, a significant co-circulation of influenza A (H1N1pdm09 and H3N2) and influenza B virus was detected with 0.057% PCR positive rate during 2009-2014 in Eastern China, yet isolated only in pediatric patients. Our data reveals school-aged population would be the main vulnerable population and a distinct seasonality for influenza. In addition, the co-infection of influenza A and B were found in Anhui Province, China. Ongoing surveillance is critical to understand the seasonality variation and make evidence-based vaccination recommendations. Information on the epidemiological patterns and co-infections of influenza A and B can help us to implement different strategies for selecting vaccine formulations and monitoring new emerging influenza strains. In addition, the identification of the susceptible population can help us to develop more precise protection measures.

Indexed as

CoinfectionInfluenza, HumanInfluenza VaccinesChildChild, PreschoolChinaHumansInfluenza A Virus, H3N2 SubtypeInfluenza B virusInfluenza Vaccinesco-infectionH1N1pdm09H3N2influenza Binfluenza-like illness

Identifiers

PMID35284384
PMCPMC8907529
OpenAlexW4213457817

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.