Guiding epidemic interventions through a fog of noisy data

Imperial College London’s Department of Infectious Disease Epidemiology reports a model-predictive control approach that times non-pharmaceutical interventions from noisy real-time case data, generally achieving better control with lower intervention costs than preset schedules or simple thresholds.

This article was originally published on MedicalXpress.com

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