Pediatric Respiratory Pathogen and Climate Data from Lanzhou, China
by Biao Wang·Updated 18d ago
9.6 KB1files
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Description
Table 2_Epidemiological trends and climate-driven dynamics of children respiratory infections in Lanzhou, China: a multi-pathogen time-series analysis.xlsx contains data on respiratory pathogen prevalence among children in Lanzhou, China, during the post-COVID-19 pandemic period. The dataset, authored by Biao Wang and shared under a CC-BY-4.0 license, includes pathogen-specific infection rates, age-stratified results, and correlations with meteorological factors like temperature and atmospheric pressure. It was last updated on 2026-05-19.
Use Cases
Modeling the relationship between meteorological factors (e.g., temperature, pressure) and infection risk for pathogens like influenza virus (IFV) and respiratory syncytial virus (RSV) based on described correlations.
Analyzing age-dependent infection patterns, such as the prevalence of RSV and IFV in infants versus Mycoplasma pneumoniae (MP) in school-aged children.
Investigating seasonal transmission patterns, including winter peaks for IFV and summer peaks for enteroviruses, as described in the study.
Assessing the prevalence and characteristics of mixed respiratory infections, which increased with child age in the dataset.
Strengths
Includes specific prevalence rates for multiple pathogens (e.g., 12.3% for influenza virus, 8.2% for adenovirus).
Provides age-stratified results (e.g., RSV peaked at 14.1% in infants <1 year).
Contains quantified correlations between pathogens and meteorological factors (e.g., IFV negatively correlated with temperature, r = -0.50).
Reports on mixed infection rates (9.7% overall) and their variation by age group.
Limitations
Row count is unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
The dataset is very small (9.6 KB), indicating limited scope or a summary table rather than raw case-level data.
Provenance
Source
Biao Wang via figshare.
Collection Method
Likely contains aggregated results from a multi-pathogen time-series analysis of pediatric respiratory infections, as described in the study abstract.
Time Range
Covers the post-COVID-19 pandemic period; specific years are not stated.
Freshness
Last updated 2026-05-19 05:29:15; freshness should be verified.