Predictive Analytics & Early Warning

Act before outbreaks happen.

Harness AI-powered predictive analytics to detect emerging disease signals, forecast outbreak risks, and provide early warnings—giving public health teams the foresight to intervene before threats escalate.

Forecasts you can plan with

Know what is coming, and how sure we are

Forecasts for 7 to 90 days ahead always come with their confidence ranges, so teams can see both the likely trend and the uncertainty before they commit resources.

  • 80% and 95% confidence ranges on every forecast
  • Proven statistical methods flag emerging clusters
  • Models backtested and monitored for drift
060120180250Forecast →W1W7W13W19W25W31Epidemiological week (simulated)

Illustrative forecast - simulated values, fictional areas. Not a real prediction.

What's included

Capabilities at a glance

Disease forecasting

7, 14, 30 and 90-day forecasts, each with an 80% and 95% confidence range.

Hotspot and cluster detection

Proven statistical methods (Getis-Ord Gi*, Local Moran's I, space-time scan statistics, EARS) find emerging signals.

Composite risk index

A weighted, configurable risk index, plus an Intervention Gap Index that shows where coverage falls short.

Validated models

Every model is backtested, scored on its accuracy and monitored for drift.

Disease modules

Malaria and Dengue today, with more diseases added by configuration.

How it works

From data to decision

  1. 01

    Forecast

    Models project cases over four horizons, with uncertainty shown as confidence ranges.

  2. 02

    Detect

    Statistical methods flag clusters and unusual increases as they emerge.

  3. 03

    Score

    The composite risk index and Intervention Gap Index rank areas for attention.

  4. 04

    Validate

    Accuracy is tracked against what actually happened, and drift is flagged.