RODS

RODS performs real-time syndromic surveillance to detect and monitor outbreaks by collecting and analyzing emergency department data and over-the-counter medication sales from the National Retail Data Monitor (NRDM).

Key Features:

• Overall Design: Provides a coordinated conceptual architecture for integrating surveillance components and maintaining system coherence.
• Data Collection: Ingests real-time health data streams, including emergency department feeds and external sources such as NRDM.
• Syndrome Classification: Categorizes clinical encounters into syndromic groups for downstream analysis.
• Database and Data Warehousing: Stores and retrieves surveillance data using data warehousing approaches for efficient querying.
• Outbreak Detection Algorithms: Implements algorithms to identify anomalous patterns and potential outbreaks from syndromic signals.
• Data Access: Manages controlled access to surveillance datasets for authorized stakeholders.
• Java Implementation: Maintains the system as Java source code for the surveillance software implementation.

Scientific Applications:

• Syndromic Surveillance: Monitors aggregated syndromic signals to inform public health surveillance and situational awareness.
• Outbreak Detection: Detects and alerts on anomalous patterns indicative of infectious disease outbreaks.
• Emergency Department Surveillance: Performs real-time surveillance of emergency department visit data across multiple jurisdictions.
• NRDM-based Medication Sales Surveillance: Supports national surveillance of over-the-counter medication sales via the National Retail Data Monitor (NRDM).
• Event and Mass-Gathering Surveillance: Applied to high-stakes event surveillance, exemplified by use during the 2002 Winter Olympics.

Methodology:

Real-time data collection from emergency departments and NRDM, syndrome classification, storage in database/data warehouses, application of outbreak detection algorithms, and maintenance as Java source code with data access components.