Serendipity affected
Advisory
predictions presented here are probably wrong
I understand

One vis to rule them all beta

These are the daily data from Italy first spread of Covid-19.

Let's suppose we are on the last day of the lockdown.

Last data, at 18:00 of {{ (inspections[0] || {}).date && inspections[0].date.toDateString() }} was of {{ (inspections[0] || {}).total }} total cases.

Let's try to fit these data in a simpler trend (aka non linear regression on a logistic function).

Prediction tell us that total cases will presumely be around {{ (inspections[0] || {}).max }}.

But removing last data and checking yesterday forecast...

there is a difference of {{ abs((inspections[0] || {}).max - (inspections[1] || {}).max) }} cases

This can be done more and more

The moral

To predict new data based on old ones is not a good practice.

It is necessary to the experts to check the current spreading of the virus, but it is extremely misleading as predicting the future: to use responsibly.

Feel free to explore last days forecasts, (just over on the black line)!

Thanks in advance!

Mauro
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