ORIGINAL RESEARCH article
Front. Cell. Infect. Microbiol.
Sec. Clinical Infectious Diseases
Volume 15 - 2025 | doi: 10.3389/fcimb.2025.1624638
This article is part of the Research TopicMajor Global Public Health Concerns: Insights into the Challenges of Climate Change and Emerging Infectious DiseasesView all 3 articles
Epidemiological Trends and Climatic Drivers of Pediatric Respiratory Infections in Wuhan, China: A Multi-Pathogen Analysis
Provisionally accepted
- Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Objectives: To characterize the epidemiology of pediatric respiratory infections and evaluate the lagged, nonlinear associations between meteorological factors and pathogen activity in post-COVID-19 Wuhan, China.Methods: A total of 28,903 respiratory specimens were collected from pediatric patients at a tertiary hospital between November 2023 and February 2025. Seven pathogens-Mycoplasma pneumoniae, adenovirus, respiratory syncytial virus (RSV), influenza A/B, and parainfluenza virus types I/III-were detected using multiplex RT-PCR. Epidemiological patterns were analyzed by age, sex, seasonality, and clinical setting. Daily meteorological data (temperature, relative humidity, wind speed) were aggregated citywide and temporally matched to case data. Spearman correlation and generalized additive models integrated with distributed lag nonlinear models (GAM-DLNMs) were used to assess pathogen-specific climatic sensitivity.Results: M. pneumoniae (18.9%), adenovirus (14.5%), and RSV (9.1%) were the most prevalent pathogens. Distinct age-and sex-specific distributions were observed, with M. pneumoniae peaking in school-aged boys and RSV in infants. Seasonal peaks were evident: RSV and influenza A predominated in winter, while adenovirus peaked in spring. Meteorological analysis revealed pathogen-specific associations: low humidity preceded RSV surges by 7-14 days; influenza B was strongly associated with wind exposure; and extreme climatic conditions showed heterogeneous effects on transmission risk across pathogens.This study demonstrates the utility of GAM-DLNMs in capturing climate-sensitive, time-lagged transmission dynamics for multiple pediatric respiratory pathogens. The findings support the development of localized, climate-informed early warning systems to enhance respiratory disease surveillance and preparedness.
Keywords: pediatric respiratory infections, respiratory viruses, Mycoplasma pneumoniae, Meteorological factors, Distributed lag nonlinear models (DLNM), Climate-sensitive surveillance
Received: 07 May 2025; Accepted: 18 Aug 2025.
Copyright: © 2025 Li, xi, rao, tang, xiang and WANG. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiaomei WANG, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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