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STS506 L. Leticia R. et al.
evolution. With this in mind, we propose using RNN that can be trained on
simulated outbreaks with a variety of networks of contacts and epidemic
parameters. Once trained, the predictions are very efficient to obtain.
The motivation of the use of surrogate models is clear and the results are
promising, however it is extremely important to study the error that arise from
their introduction, in order to control it to our needs.

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