This is an update as of April 5th, 2020.
We are analyzing the existing available data on daily deaths caused by the SARS-CoV2 virus and use that in conjunction with certain simple models to predict the evolution of the disease in certain geographical areas. You can read the full introduction here.
Romania is added to the list, as it already has enough datapoints. It seems to have a fast outbreak, but for now the size doesn’t seem to be that large. We’ll see how it evolves as the outbreak matures there too.
For many of the regions we are now past the peak of the outbreak, especially in Europe. In the US New York has the largest outbreak and even there we are 2 days away from the peak.
After adding one more temporal data point, it looks now that the temperature has the largest correlation in absolute value with the speed of the outbreak. A plot illustrating that is attached.
The table for the log-normal fit in included as well. While it does capture better the evolution of the outbreak around the peak, it has a harder time than the erf at capturing the points around the onset of the outbreak.
Correlation between those external data and the parameters of the fit
Error Function Fit
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