Evidence map›Paper›PMID 41408609›Full record

ArticleBMC infectious diseases2025

The multipathogen profiles and co-infection characteristics obtained from comprehensive surveillance of patients with acute respiratory infections in the post-COVID-19 era in Shenzhen, China.

Dandan Niu, Qiuying Lv, Yuan Bai, Zhen Zhang, Renli Zhang, Yanxiao Gao, Zhongyao Xu, Honglin Wang, Xiaomin Zhang, Feng Sha and 8 more

Abstract readMulticenter Study
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

18 authors.

Dandan NiuShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Qiuying Lv *Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Yuan Bai *Li Ka Shing Faculty of Medicine, WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China.
Zhen ZhangShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Renli ZhangShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Yanxiao GaoShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Zhongyao XuShenzhen Uni-Medica Technology Co., Ltd., Shenzhen, 518055, China.
Honglin WangShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Xiaomin ZhangShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Feng ShaShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Yingluan ZhangShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Tong LiShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Tengyingzi LiuShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Dan WangShenzhen Uni-Medica Technology Co., Ltd., Shenzhen, 518055, China.
Xiaolu ShiShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Yongchao GuoShenzhen Uni-Medica Technology Co., Ltd., Shenzhen, 518055, China. ycguo@uni-medica.com.
Jinling TangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. jltang@siat.ac.cn.
Tiejian FengShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China. fengtiej@126.com.

Funding

Basic Research Funds of Central Public Welfare Research Institutes, Chinese Academy of Medical Sciences 2020-PT330-006Key Project of Basic Research of Shenzhen Science and Technology Plan JCYJ20200109150715644Sanming Project of Medicine in Shenzhen SZSM202211023Shenzhen Key Discipline of Medicine, Key Specialty of Public Health SZXK064Shenzhen Medical Research Fund B2404002Shenzhen Science and Technology Innovation Commission Key Project of Basic Research Program JCYJ20210324115411030Shenzhen Science and Technology Program JSGG20210713091811036Shenzhen Science and Technology Programs KQTD20190929172835662Shenzhen Sustainable Development Science and Technology Project KCXFZ202002011006190The Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2022-I2M-CoV19-006The National Natural Science Foundation of China 82473754
6 · The paper itself

Abstract

backgroundThe long-term impact of the COVID-19 pandemic on the distribution pattern of respiratory pathogens in China was unknown. Our study aimed to determine the multipathogen profiles and co-infection characteristics among patients with acute respiratory infections (ARIs) in the post-COVID-19 era in Shenzhen, China.

methodsThis multi-center cross-sectional study was conducted among patients with ARIs from five sentinel hospitals from November 1, 2022 to June 30, 2023 in Shenzhen, China. The collected respiratory samples were subjected to targeted next-generation sequencing for high-throughput screening of 108 respiratory pathogens. Multi-stage logistic regression models were built to infer interactions between pathogens at the individual level.

resultsThe median [IQR] age of 1890 patients included was 31.8 [23.7, 45.2] years. The proportions of positivity on any pathogen and co-infection were 84.0% (1587/1890) and 41.4% (782/1890). Children < 5 years and school-age children have the highest viral (78.0%, 99/127) and bacterial positive proportion (65.5%, 114/127). Influenza virus (IFV), SARS-CoV-2, and human rhinovirus (HRV) were the three leading viral pathogens, and Haemophilus influenzae (H. influenzae), Staphylococcus aureus (S. aureus), and Streptococcus pneumoniae (S. pneumoniae) were the three leading bacterial pathogens. The three leading co-infection pathogens were S. pneumoniae combined with H. influenzae (4.6%, 86/1890), IFV with S. aureus (4.5%, 85/1890) and with H. influenzae (3.3%, 62/1890). The proportions of positivity on IFV, enterovirus, SARS-CoV-2, H. influenzae, S. aureus, and S. pneumoniae in outpatients were higher than those in inpatients, while the proportions of positivity on human parainfluenza virus (HPIV), human metapneumovirus (HMPV), Pseudomonas aeruginosa, Acinetobacter baumannii, Mycoplasma pneumoniae, and Legionella pneumophila in inpatients were higher than those in outpatients. RSV, IFV, HPIV, human adenovirus, and HRV were the top five viral pathogens among hospitalized children before, during, and after the COVID-19 pandemic in Shenzhen. Virus‒virus interactions, such as IFV combined with SARS-CoV-2 (OR = 20.3 [95% confidence interval (CI): 7.2-57.0]) and with HRV (OR = 7.2 [95% CI: 3.5-15.0]) exhibited competitive effects. Bacteria-bacteria interactions exhibited synergistic effects such as Moraxella catarrhalis combined with S. pneumoniae (OR = 0.3 [95% CI: 0.2-0.5]).

conclusionsThere were differences in the pathogen profiles among patients with different ages, pneumonia groups, and case types. Virus‒virus interactions presented competitive effects, while bacterium‒bacterium interactions exhibited synergistic effects.

Indexed as

CoinfectionCOVID-19Respiratory Tract InfectionsAdolescentAdultAgedBacteriaChildChild, PreschoolChinaCross-Sectional StudiesFemaleHumansInfantMaleMiddle AgedAcute respiratory infectionsCo-infectionComprehensive surveillancePathogen profilesPost-COVID-19 era

Identifiers

PMID41408609
PMCPMC12821205

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.