Test bank for critical care nursing a holistic approach 11th edition morton f...
COVID-19 Analysis: March 31, 2020
1. Caveats and Comments
1. These are not confidential. You can freely share this output freely. The code is available at
https://github.com/StevenLShafer/COVID19/.
2. This is my analysis, not Stanford’s analysis. My understanding is that Stanford’s internal analysis, done to plan resource
allocation at Stanford, shows substantially longer doubling times. This is reassuring for those of us working at Stanford.
3. The data are from usafacts.org. Here is the file: https://usafactsstatic.blob.core.windows.net/public/data/covid-
19/covid_confirmed_usafacts.csv. The data are collected from state and county public health departments.
4. With trepidation, I have changed the fits. Previously I used two log linear fits. However, because the curves are starting to truly
flatten, I now fit the second curve to exp(log(observed Y on day 1 of final segment) + peak * (1-exp(-k * delta time))). This is an
empiric function of the rise to steady state.
5. The number printed on the graph is the projection for a week from today. Because that is only a week out, it is probably not far
off. However, the "peak" in the caption is the estimated total peak at time = infinity from the model. I have very little confidence
because it is a projection will into the future.
6. The idiosyncratic locations chosen for the analysis reflect where Pamela and I have friends and family. I’m happy to add other
regions. Also, I’m happy to add people to the blind CC distribution list. Just let me know.
7. Send any questions to steven.shafer@stanford.edu.
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4. Santa Clara and San Mateo
1,833
1
10
100
1,000
10,000
100,000
1,000,000
10,000,000
Date
Actual(points)/Predicted(line)
Phase
Pre log linear
Log linear
Social distancing
Steve's Santa Clara and San Mateo Projection as of 2020-04-01
Initial doubling: 3.4 days, Predicted peak: 5,777
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