Analysis of pathogenic characteristics of acute respiratory tract infections in children and the influence of environmental factors in Shijiazhuang area

Objective To investigate the epidemiological patterns of acute respiratory infections (ARI) in children (0–14 years) in Shijiazhuang and the impact of meteorological factors. Methods Fourteen respiratory pathogens were detected by fluorescent PCR melting curve analysis. LASSO regression screened environmental factors; generalized additive model (GAM) analyzed nonlinear associations between meteorological conditions and ARI incidence; distributed lag nonlinear model (DLNM) explored lagged/cumulative effects of meteorological factors and pollutants. Pathogen distribution differences were tested by χ² or Fisher’s exact test. Results A total of 1,961 ARI cases were included, with an overall pathogen positivity rate of 78.23%. Positivity rates differed significantly by age, season, and case classification (all P 0.05), being highest in 3–6-year-olds, summer, and outpatient/emergency cases. Single infections (59.19%) were dominant; SP and Hi were prone to mixed infections, EV to quadruple+ infections. Pathogen spectrum varied by age and season. Time-series analysis showed seasonal ARI peaks in winter. DLNM revealed nonlinear associations between all environmental factors and ARI: O 3 (33.5 μg/m³, RR = 4.3051) and SO 2 (39.4 μg/m³) had strong effects; high CO (49.40 mg/m³), high temperature (31.1 °C), and low-moderate humidity (27%–42.5%) increased risk; high NO 2 had moderate lagged risk. GAM confirmed nonlinear associations, with highest ARI risk at 3.63 °C (RR = 1.89, 95% CI:1.74–2.05). Conclusion High pathogen detection rate was observed in 2024–2025. ARI had distinct age/season patterns, with winter peaks. Low/high temperature, low humidity, and high SO 2 were key risk factors with immediate + cumulative effects, providing data for prevention and early warning.