PedMap

PedMap maps epidemiological patterns of pediatric diseases using clinical data from The Children's Hospital Zhejiang University School of Medicine (ZUCH) to analyze age-, season-, and climate-related trends and disease co-occurrence.

Key Features:

• Data-Driven Insights: Constructed from ZUCH outpatient data comprising over 5 million visits by approximately 2.19 million unique pediatric patients from 2013 to 2016.
• Disease Mapping and Visualization: Identifies the top 100 most-reported pediatric diseases and visualizes their relationships, incidence rates, age of onset, and seasonal variations, with diseases categorized into four age groups and seasons.
• Co-occurrence Analysis: Highlights co-occurrence patterns among common pediatric diseases to characterize comorbidity relationships.
• Predictive Modeling: Employs Gaussian regression models to forecast disease incidence using weather data.
• Resource Planning Support: Provides epidemiological summaries to inform workforce and resource allocation decisions in pediatric care.

Scientific Applications:

• Epidemiological research: Enables analysis of age-related, seasonal, and climate-related variation and co-occurrence patterns in pediatric disease populations.
• Clinical decision support: Informs clinicians and hospital departments on disease incidence trends relevant for staffing and resource management.
• Public health surveillance and policy: Supports surveillance and policy development through visualization and forecasting of pediatric disease incidence driven by environmental factors.

Methodology:

Aggregates outpatient records from ZUCH (2013–2016; >5 million visits, ~2.19 million patients); identifies the top 100 reported pediatric diseases; categorizes diseases into four age groups and seasons; performs visualization of relationships, incidence rates, age of onset, and seasonal variations; conducts co-occurrence analyses; and applies Gaussian regression models using weather data to forecast disease incidence.