Health GIS Pipeline for Dengue Case Prediction

The problem

Dengue case data needs spatial context to reveal patterns and risk areas that are hard to see in a table alone.

Our approach

The pipeline combined machine learning/deep learning methods with spatial clustering across two district datasets, producing risk maps for decision-making.

1. Prepare the Thiruvallur and Kothagudem datasets.
2. Apply ML/DL methods to identify case patterns.
3. Use spatial clustering to surface geographic concentrations.
4. Translate findings into spatial risk maps.

Technology

Results

• Spatial risk mapping and pattern detection across the two district datasets.

What this means for your project

This work maps directly to spatial decision-support systems and analytics solutions where data needs to become an evidence-based operational view. Explore the matching service

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