Prediction of Danish Covid19 cases

Questions
1

Hi Experts

I have made a simple model for predicting the number of Danish Covid19 Hospitalized patients with Gaussian Processes.

My notebook is here:
[https://github.com/sojohan/Prediction-of-Danish-COVID-19-Cases/blob/master/GaussianProcess_Danish_Corona_figures.ipynb]

Would be very happy for feedback?

Sojohan

1 Like
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Hey Sojohan,

GPs are generally my go-to approach for non-linear time series, but the reservation I have in this case is that it is not a mechanistic model, so I would be hesitant to use it in place of S(E)IR compartmental models. A GP model might be useful for very short-term predictions (depending on the length scale), but since it does not account for changes in behavior (including specific interventions), I think it has limited use. That said, it might be interesting to incorporate a GP into a mechanistic model as a way of estimating some of the latent parameters, and their dynamics.

One technical observation: once you have fit the model using MCMC (via pm.sample) there is no need to fit it again using find_MAP. The latter is actually an inferior way of fitting the model, since it is not fully Bayesian–it just does brute-force mode hunting.

Chris

2 Likes
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Hi Chris

Thanks for the feedback. Yes I agree that the model is good at short-term predictions. Would try to update priors and see the results.

Yes I know that find_map was not necessary…

sojohan