This is an update as of April 8th, 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.
One more state is added to the analysis, Pennsylvania. It is still quite early in the outbreak, but it shows signs that it can pick up a lot soon.
All the analysis, including the plots, is moved to the generalized logistic model. This is a skewed model, the parameter α, captures the skewness of the outbreak. A value of α
> 1 means the model is right skewed.
It’s day 44 and most regions are passed the peak of the outbreak.
The b is replace with the speed of outbreak in the table, which is the inverse of the number of days between the time that c/10 people die (10% of the total number of dead) and c/2 people die (50% of the number of dead). It is more representative than just b in this case.
One more region is added named SF and it contains the daily deaths in NYC during the Spanish flu outbreak of 1918. SARS compares quite well with the Spanish flu.
Value of α slightly higher than the Spanish flu (2.5 to 3 versus 1.71) where the SARS-Cov2 outbreak is more mature (Italy and Spain). The speed of the outbreak of the Spanish flu is very similar to the speed of outbreak of SARS-Cov2
Generalized Logistic Fit
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