As climate change accelerates, being able to predict health risks – not just respond to them – is becoming critical.
Predictive modeling can give Ministries of Health a powerful tool to anticipate where climate-sensitive diseases like malaria, cholera, or dengue might flare up, and take action early.
But using predictive analytics in public health comes with important questions:
How do we make sure models are accurate and useful?
How do we build trust and capacity to use them?
And how do we connect predictions to real decisions on the ground?
This session will explore early experiences in developing and piloting predictive tools like the Modeling App and the Chap Modeling Platform, and open a conversation on how we can unlock the full potential of predictive modeling for health systems in a changing climate.
As climate change accelerates, being able to predict health risks – not just respond to them – is becoming critical.
Predictive modeling can give Ministries of Health a powerful tool to anticipate where climate-sensitive diseases like malaria, cholera, or dengue might flare up, and take action early.
But using predictive analytics in public health comes with important questions:
How do we make sure models are accurate and useful?
How do we build trust and capacity to use them?
And how do we connect predictions to real decisions on the ground?
This session will explore early experiences in developing and piloting predictive tools like the Modeling App and the Chap Modeling Platform, and open a conversation on how we can unlock the full potential of predictive modeling for health systems in a changing climate.
Auditorium 5 The DHIS2 Annual Conference oslo2025@dhis2.orgTechnical Issues?
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