Case Study: MEWA achieves proactive animal disease forecasting with Dataiku

MEWA Forecasting Animal Outbreaks for Early Prevention

MEWA, the Ministry of Environment, Water and Agriculture in Saudi Arabia, needed a better way to anticipate animal disease outbreaks across millions of livestock. Its earlier GIS-based efforts lacked a systematic method to analyze trends and seasonality by disease, region, and animal type, making it difficult to predict outbreaks and plan preventive action. Dataiku was used as the platform for this forecasting initiative.

Dataiku helped MEWA build a time-series solution with multiple forecast flows by region, animal, disease, and office, plus a dynamic app for user-selected scenarios. The model is retrained weekly, predictions are visualized in Dataiku, and the solution runs on an automation node with a self-service application. As a result, MEWA can forecast disease spread up to six months ahead, identify hotspots and outbreaks more quickly, and support more data-driven prevention efforts at scale.

MEWA

Amr Mansour

Lead AI Consultant