VectorWatch

Inspiration

Mosquito-borne diseases like Dengue, Malaria, and Chikungunya kill over 700,000 people annually worldwide. In India alone, Bangalore and Karnataka face recurring outbreaks every monsoon season. We were inspired by the urgent need for predictive, data-driven public health tools that can help communities and health officials anticipate disease outbreaks before they happen. Traditional surveillance is reactive. VectorWatch is proactive.

What it does

VectorWatch is a comprehensive disease risk modeling platform that has live weather integrations, 14-day risk forecasts, and a population dynamic simulation. It has a interactive Bangalore map as a sample, and is very information. It is biology-driven modeling.

How we built it

Next.js, Open-Meteo API, Tailwind CSS, Framer Motion, Recharts, Leaflet Maps.

Challenges we ran into

Typescript strictness. Leaflet SRR Issues. API Rate Limits. Map Bounds. Model Calibration.

Accomplishments that we're proud of

Real scientific modeling. Live data integration. 20 Bangalore neighborhoods. Responsive, accessible UI.

What we learned

Epidemiological modeling. Vector biology. Geospatial visualization. Next.js 16 features. Real-time data architectures.

What's next for VectorWatch

Expand to drone surveillance integration, API for researchers, multi-disease support.

Built With

• gps
• leaflet.js
• next.js
• open-meteo
• recharts
• typescript