Evidence map›Paper›PMID 40112925›Full record

ArticleVirologica Sinica2025

Epidemiological and molecular characteristics of human parainfluenza virus in southern China during 2016-2020.

Yizhe Li, Minjie Liu, Jingyao Liang, Hengming Ye, Mingcui Lyu, Delin Chen, Linyue Liang, Shuqing Zhang, Kexin Zhang, Shu An and 4 more

Abstract read
In one paragraph

Article in Virologica Sinica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Yizhe LiSchool of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, China.
Minjie LiuSchool of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Jingyao LiangSchool of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Hengming YePublic Health Service Center of Bao'an District, Shenzhen, 518102, China.
Mingcui LyuSchool of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Delin ChenDepartment of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
Linyue LiangDepartment of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
Shuqing ZhangKey Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, China; Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
Kexin ZhangSchool of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Shu AnDepartment of Laboratory Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China.
Wenle ZhouDepartment of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
Jueheng WuKey Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, China; Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
Xun ZhuKey Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, China; Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China. Electronic address: zhuxun8@mail.sysu.edu.cn.
Zhenjian HeSchool of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, China. Electronic address: hezhenj3@mail.sysu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human parainfluenza viruses (HPIV) are common viral pathogens in acute respiratory infection (ARI). We aimed to describe the epidemiological and molecular characteristics of HPIV from ARI patients. This cross-sectional study was conducted using respiratory samples from 9,696 ARI patients between 2016 and 2020 in southern China. All samples were analyzed by quantitative real-time polymerase chain reaction to determine the presence of HPIV and other common respiratory viruses. Descriptive statistics were performed to determine the temporal and population distribution of HPIV. The full-length hemagglutinin-neuraminidase (HN) gene of HPIV3-positive samples was sequenced for phylogenetic analysis. A total of 577 (6.0%) patients tested positive for HPIV, with HPIV3 being the predominant serotype, accounting for 46.8% of cases. Notably, 66.0% of these HPIV-positive cases were children aged 0-2 years. The prevalence of HPIV infections showed a decreased trend and altered peak during 2016-2020. Cough, fever, sputum production, and rhinorrhea were common respiratory symptoms in HPIV-positive patients. The majority of cases had pneumonia (63.4%). Human rhinovirus (HRV) and human coronavirus (HCoV) were the most common coinfection viruses in HPIV-positive cases, with proportions of 20.1% and 14.4%, respectively. Phylogenetic analysis revealed that the predominant lineage of HPIV3 was C3f (86.0%), followed by lineage C3a (8.0%), C3d (4.0%), and C3b (2.0%). These findings help to better understand the epidemiology of HPIV, and improve public health strategies to prevent and control HPIV infections in southern China.

Indexed as

Paramyxoviridae InfectionsRespiratory Tract InfectionsAdolescentAdultAgedChildChild, PreschoolChinaCross-Sectional StudiesFemaleHN ProteinHumansInfantInfant, NewbornMaleMiddle AgedHN ProteinAcute respiratory infection (ARI)EpidemiologyHuman parainfluenza viruses (HPIV)Lineages

Identifiers

PMID40112925
PMCPMC12131018

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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.