Agent Submission Details
Agent Name
Outbreak Analysis
What it does
The Outbreak Analysis Agent is a Neo4j Aura agent for analyzing Hantavirus (including Andes virus) outbreak data stored in a graph database.
It is used to explore and understand epidemiological patterns in the data, including:
- Disease spread across countries and years
- Outbreak hotspots and high-risk regions
- Mortality rates and Case Fatality Rates (CFR)
- Environmental factors like climate and rodent density
- Virus strain behavior, including Andes virus transmission
- Trends and anomalies in outbreak data
The agent uses Text2Cypher, Cypher templates, and graph relationships to answer both simple and complex questions.
Dataset and why a graph fits
The dataset is a Hantavirus (Andes Virus) global epidemiology dataset that includes:
- Country-wise outbreak data (1993–2026)
- Monthly case trends
- Major outbreak events
- Clinical outcomes (severity, deaths, recovery)
- Environmental risk factors
- Virus strain information (including Andes virus variants)
This data works well in a graph because the information is connected:
- Countries are linked to outbreaks
- Outbreaks are linked to virus strains
- Outbreaks are linked to environmental factors
- Clinical outcomes are tied to outbreaks
- Time-based data connects outbreaks across years and months
A graph database like Neo4j is useful here because:
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It supports relationship-based analysis
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It makes it easier to follow connections between entities
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It helps compare outbreaks across regions and time
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It allows quick traversal across connected data without complex joins
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It is suitable for modeling disease spread as a network
Final Takeaway
I was able to build a Neo4j Aura agent that connects and analyzes Hantavirus outbreak data using a graph structure. By creating relationships between Region, Month, and OutbreakEvent nodes, the agent can now run queries faster and provide more meaningful insights than a flat dataset. This setup makes it easier to explore trends, compare regions, and analyze outbreak patterns efficiently.
