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CrystalCast

Biosurveillance & Epidemiological Modelling

INTELLIGENCE · PRODUCT

CrystalCast

Biosurveillance & Epidemiological Modelling

CrystalCast is a disease forecasting and epidemiological modelling tool that combines multiple models to predict outbreaks and anticipate their impact on populations. Through advanced scenario modelling, statistical analysis and data visualisation, it helps decision-makers explore uncertainty, compare potential outcomes and evaluate interventions before taking action.

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Key Capabilities

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Multi-model disease forecasting

Combine multiple epidemiological models to forecast disease outbreaks, compare predictions and provide a more holistic view of potential outcomes.

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What-if scenario modelling

Explore different outbreak scenarios by adjusting factors including disease type, outbreak location, population density and demographics to understand potential impacts.

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Intervention modelling

Model and compare potential interventions including movement restrictions, medication and vaccination to support more informed response planning.

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Model comparison & uncertainty

Identify and highlight disagreements between epidemiological models, helping decision-makers understand uncertainty rather than relying on a single prediction.

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Population impact analysis

Assess potential outcomes across populations, including hospitalisations, recoveries and deaths, and explore how effects vary spatially and demographically.

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Advanced data visualisation

Turn complex model outputs into accessible visual intelligence using time-series charts, spatial views, population trees and statistical visualisations.

In the field

CrystalCast was used operationally by the UK Health Security Agency during the COVID-19 pandemic to support government decision-makers. By combining epidemiological models and visualising uncertain outcomes, the platform helps stakeholders compare potential outbreak scenarios and interventions, turning complex modelling into intelligence that can support faster, more confident decisions.

Modelling approach

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Multi-model ensemble — combines several epidemiological models rather than relying on a single prediction
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Spatial and demographic resolution — outcomes broken down by place and population group

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