Discover the unknown, define priority areas and improve program yield
Epidemic mapping, monitoring, evaluation and predictive modelling
Creating a digital twin of your health program
TB Situation Room
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Map the epidemic
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Monitor country targets
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Enable smart guidance
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Zoom in on sub-national level
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Events, triggers and alarms
Sub-national overview
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Screening targets
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Expected vs. actual yield
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Capacity planning
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Regional context and insights
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Local stakeholder engagement
At the core of our platform, we use a powerful machine learning engine that adds an intelligence component to augment reference data and variables. The engine incrementally learns from things, people and processes and quantifies risk at the population and individual level.
Our solution allows for the reasoning in uncertainty which helps to cover for data quality issues and sparsity. We identify the unknown unknowns and map cause-effect patterns and relations in complex datasets. We can distribute intelligence to the edge which is ideal for remote settings and disconnected environments.
Given real-world data, patient records and survey results, the platform will dynamically produce context, program insights, recommendations and actionable output to enable more targeted case finding, optimise country health resources and increase program yield. Such output is visualised at the program steering level or pushed towards stakeholders at all levels of the NTP.