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Trying out HopkinsIDD/flepiMoP to model influenza in Belgium, both spatially-explicit and non-spatially-explicit.

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flepimop_influenza_BE

A repisitory containing an age-stratified influenza model, simulated either spatially-explicit or non-spatially-explicit for Belgium. Uses the in-house code of the JHU IDD group to simulate and calibrate the model.

Goals

  • Learn how to build models with FlepiMoP
  • Benchmark computational complexity and user-friendliness against my influenza demo model implemented using pySODM.
  • Calibrate the models to data from the 2017-2018 Influenza season in Belgium. Once more assess its computational complexity and user-friendliness.

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Trying out HopkinsIDD/flepiMoP to model influenza in Belgium, both spatially-explicit and non-spatially-explicit.

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