Communicable diseases platform (CDP): Real-Time clinical analytics for infections

Area of Science:

• Pediatric infectious diseases
• Public health surveillance
• Health informatics

Background:

• Communicable diseases, particularly respiratory infections, are a major cause of pediatric hospitalizations.
• Current surveillance methods for communicable diseases are often manual, retrospective, and lack integrated demographic and clinical data.
• The Communicable Diseases Platform (CDP) was developed to address these limitations by aggregating comprehensive data.

Purpose of the Study:

• To introduce the Communicable Diseases Platform (CDP) as a novel data aggregation tool.
• To demonstrate the CDP's capability in integrating demographic and clinical data for communicable disease surveillance in a pediatric hospital setting.
• To highlight the potential of the CDP in improving understanding of disease patterns and facilitating outbreak control.

Main Methods:

• The CDP pilot phase involved extracting de-identified, aggregated data from electronic medical records for pediatric patients with positive respiratory swabs.
• Data spanned from 2016 to 2025, encompassing positivity rates and cumulative hospital admissions.
• A dashboard was developed for data visualization, allowing filtering by pathogen, age, presentation type, and interventions.

Main Results:

• The CDP successfully aggregated both demographic and clinical data for communicable disease presentations.
• The dashboard provided insights into positivity rates and hospital admission trends.
• Data filtering capabilities allowed for detailed analysis of specific pathogens, age groups, and interventions.

Conclusions:

• The CDP enhances the understanding of clinical profiles, disease burden, and seasonal patterns of communicable diseases in children.
• This improved surveillance supports more effective outbreak control, patient flow prediction, and clinical monitoring.
• Future developments aim to integrate immunization data and employ machine learning for real-time vaccine effectiveness and predictive disease modeling.