Table 2.

Sensitivity analysis for different values of observation and model error covariance matrices. The first two rows show number of latent infected patients and patients under treatment predicted for the 28.05.2020, the last day in the sample. The last two rows show the mean forecasting errors for treated patients and confirmed cases over the full sample for each covariance matrix configuration. The table exemplifies a bad fit with a high amount of forecasting errors when using a naive unit covariance setup

$\mathbf{P}$ Value	0.1	1	1	1	100	100
$\mathbf{Q}$ Value	0.5	100	1	10	1	10
Treatment	230,760	231,336	230,792	231,517	230,782	230,934
Infections	210,311	2,102,126	2,102,549	2,102,431	2,102,576	2,102,603
MRSFE T	888	863	901	807	829	836
MRSFE R	39,476	39,291	39,431	39,381	39,459	39,469