Evidence map›Paper›PMID 38633430›Full record

ArticleChina CDC weekly2024

Epidemiological Characteristics of Human Parainfluenza Viruses Infections - China, 2019-2023.

Yixuan Gao, Yingwei Ma, Daxing Feng, Feng Zhang, Biao Wang, Xiaoqing Liu, Bing Zhu, Hui Xie, Linqing Zhao, Xiaoru Long and 8 more

Open access · diamondAbstract 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 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.4field-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

10 citing papers in PubMed, 14 citations in OpenAlex.

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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 at 4 institutions in 1 country.

Yixuan GaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; Beijing, China.
Yingwei MaPrecision Medicine Research Center, Children's Hospital of Changchun, Changchun City, Jilin Province, China.
Daxing FengHenan Provincial Center for Disease Control and Prevention, Zhengzhou City, Henan Province, China.
Feng ZhangLaboratory of Viral Diseases, Qingdao Municipal Centre for Disease Control and Prevention, Qingdao City, Shandong Province, China.
Biao WangVirus Laboratory, Gansu Provincial Center for Disease Control and Prevention, Lanzhou City, Gansu Province, China.
Xiaoqing LiuJiangxi Provincial Center for Disease Control and Prevention, Nanchang City, Gansu Province, China.
Bing ZhuVirus Laboratory, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou City, Guangdong Province, China.
Hui XieInstitute for Immunization and Prevention, Beijing Center for Disease Prevention and Control, Academy for Preventive Medicine, Institute of Tuberculosis Control Research and Prevention, Beijing, China.
Linqing ZhaoLaboratory of Virology, Beijing Key Laboratory of Etiology of Viral Diseases in Children, Capital Institute of Pediatrics, Beijing, China.
Xiaoru LongDepartment of Infection, Children's Hospital of Chongqing Medical University, Chongqing, China.
Ying ChenInner Mongolia Autonomous Region Comprehensive Center for Disease Control and Prevention, Hohhot City, Inner Mongolia Autonomous Region, China.
Bing WangShenyang Prefecture Center for Disease Control and Prevention, Shenyang City, Liaoning Province, China.
Jie JiangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; Beijing, China.
Zhen ZhuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; Beijing, China.
Yan ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; Beijing, China.
Aili CuiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; Beijing, China.
Baicheng XiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; Beijing, China.
Naiying MaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention; Beijing, China.
Capital Institute of Pediatrics · CNChinese Center For Disease Control and Prevention · CNChongqing Medical University · CNInner Mongolia Comprehensive Disease Prevention and Control Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A retrospective study based on sentinel surveillance was conducted in 10 provincial-level administrative divisions (PLADs) in China to enhance the understanding of the epidemiological characteristics of human parainfluenza viruses (HPIVs). Methods: From January 2019 to June 2023, respiratory specimens were collected from individuals with acute respiratory infections (ARIs) and screened for four HPIVs serotypes and other common respiratory viruses using multiplex real-time polymerase chain reaction (PCR). This study analyzed the association of HPIVs infections with seasonal patterns, geographical distribution, demographic profiles, clinical features, and co-infection status. Results: During the study period, a total of 12,866 ARIs were included. The overall detection rate of HPIVs was 6.15%, varying from 5.04% in 2022 to 9.70% in 2020. The median age of HPIVs-infected patients was 3 years. HPIV2 was more prevalent among individuals aged 5-17 years (42.57%), while HPIV4 was more common in those over 65 years (12.24%). HPIV3 (54.16%) and HPIV1 (27.18%) were the predominant serotypes, and their prevalence exhibited significant seasonal fluctuations post- coronavirus disease 2019 (COVID-19) pandemic. The peak of HPIV3 shifted three months later in 2020 compared to 2019 and returned to a summer peak thereafter. Two peaks of HPIV1 were observed in 2021 following the peak of HPIV3. Additionally, co-infections were frequent in HPIVs cases (overall rate: 22.12%), with human rhinovirus being the most common co-infecting virus. Conclusions: The prevalence of HPIVs in China was predominantly due to HPIV3 and HPIV1, and their seasonal patterns were altered by pandemic restrictions. Hence, continuous surveillance of HPIVs is essential.

Indexed as

Acute respiratory infectionsEpidemiological characteristicsHuman parainfluenza viruses

Identifiers

PMID38633430
PMCPMC11018516
OpenAlexW4393169502

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.