Evidence map›Paper›PMID 39129001›Full record

ArticleVirology journal2024

Mycoplasma pneumoniae infection outbreak in Guangzhou, China after COVID-19 pandemic.

Ya Li, Minzhi Wu, Ying Liang, Yihao Yang, Wenyu Guo, Yuezhi Deng, Tao Wen, Caiwei Tan, Cheng Lin, Feifei Liu and 2 more

Abstract read
In one paragraph

Article in Virology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Post-pandemic surge ofJournal of clinical microbiology · 2026
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  8. The expression and clinical value ofTranslational pediatrics · 2026
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  18. Characterizing the epidemiology ofEmerging microbes & infections · 2025
    Article
  19. Article
  20. 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.

Ya Li *Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Minzhi Wu *Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Ying Liang *Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Yihao YangDepartment of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Wenyu GuoDepartment of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Yuezhi DengDepartment of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Tao WenDepartment of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Caiwei TanDepartment of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Cheng LinDepartment of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Feifei LiuGuangzhou Kingmed Center for Clinical Laboratory, Guangzhou, Guangdong, China.
Yongping LinDepartment of Laboratory Medicine, National Cancer Center, National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Shenzhen, China. 18928868278@163.com.
Qigao ChenDepartment of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China. 734449359@qq.com.

Funding

the Guangzhou Science and Technology Project 202201020484the Guangzhou Science and Technology Project 2023A03J0357the Plan on enhancing scientific research in GMU 2024SRP055]the Sanming Project of Medicine in Shenzhen SZSM202311002
6 · The paper itself

Abstract

backgroundsMycoplasma pneumoniae (M. pneumoniae) is a common pathogen causing respiratory diseases in children. This study aimed to characterize epidemiological and disease severity shifts of M. pneumoniae: infections in Guangzhou, China during and after the coronavirus disease 2019 (COVID-19) pandemic.

methodsThroat swab samples were obtained from 5405 hospitalized patients with symptoms of acute respiratory infections to detect M. pneumoniae. Differences in epidemiological and clinical characteristics of M. pneumoniae: infections were investigated during 2020-2022 and after COVID-19 pandemic (2023).

resultsM. pneumoniae were detected in 849 (15.6%, 849/5405) patients. The highest annual positive rate was 29.4% (754/2570) in 2023, followed by 5.3% (72/1367) in 2022, 1.2% (12/1015) in 2021, and 2.0% (11/553) in 2020, with significantly increasing annual prevalence from 2020 to 2023. M. pneumoniae incidence peaked between July and December post-COVID-19 pandemic in 2023, with the highest monthly positive rate (56.4%, 165/293). Clinical characteristics and outcomes of patients with M. pneumoniae did not vary between periods during and after COVID-19 pandemic except that patients with M. pneumoniae post-COVID-19 pandemic were more likely to develop fever. Patients with severe M. pneumoniae pneumonia (SMPP) were more likely to develop respiratory complications, myocardial damage, and gastrointestinal dysfunction than those with non-SMPP. Patients with SMPP had lower lymphocytes, CD3

conclusionOutbreaks of M. pneumoniae: occurred in Guangzhou, China in 2023 upon Non-pharmaceutical interventions easing. Despite the increasing incidence of M. pneumoniae, the disease severity remained similar during and after the COVID-19 pandemic.

Indexed as

COVID-19Mycoplasma pneumoniaePneumonia, MycoplasmaAdolescentAdultAgedChildChild, PreschoolChinaDisease OutbreaksFemaleHumansIncidenceInfantMaleMiddle AgedAcute respiratory tract infectionsEpidemiologyMacrolide-resistant M. pneumoniaeM. pneumoniaeOutbreak

Identifiers

PMID39129001
PMCPMC11318190

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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.