CDC Observational Data updated May 8 is compared with approximations of Imperial College Model Projections from March 16.
Post w/ more links:
https://steemit.com/politics/@wikiworldorder/revisiting-imperial-risk-assessments-of-covid-19-may-12
https://medium.com/@wikiworldorder/revisiting-imperial-risk-assessments-of-covid-19-may-12-503f76eeab82
http://WikiWorldOrder.org/2020/05/13/revisiting-imperial-risk-assessments-of-covid-19/
Data Sources:
https://www.cdc.gov/nchs/nvss/vsrr/COVID19/
https://data.cdc.gov/Health-Statistics/Deaths-from-Pneumonia-and-Influenza-P-I-and-all-de/pp7x-dyj2
https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
My Math & Hypotheticals:
http://wikiworldorder.org/dox/imperial-risk-assessment-200512.ods
On March 16, 2020, the London “Imperial College COVID-19 Response Team” led by Neil Ferguson published their “Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand”. This report was very widely shared on mainstream media, social media, and by policymakers. I interpreted this report to be a primary driver of the atmosphere under which policy discussions are still limited.
I’ve been wondering how their model projections have corresponded to the observational data we have thus far. Unfortunately, they do not provide predictions in any formats that can be readily matched with what little data is actually reported by the CDC, etc. Perhaps models intended to inform public policy should always predict specific hard measurements over time for later comparison. How else can policymakers and voters verify the accuracy or efficacy of a given policy?
So for my next thought experiment, I have graphed a few hypothetical projections on top of the 2010-2018 Historical Average of All Deaths Reported Weekly. In this graph, the dark blue line on top is the raw observational data for All Deaths Reported Weekly in 2020 as of May 8. The most recent few weeks in that observational data are clearly missing a lot of reports because the WorldOMeters website has reported over 80,000 COVID-19 deaths in the U.S. cumulatively. So I’ve manually constructed the orange line as a projected/artificial/fabricated/fake set of COVID-19 deaths which represents the ballpark shape of 80,000 Excess COVID-19 Deaths through May 10 — stacked on top of the Historical Average of All Deaths Reported Weekly.
Next, I constructed a hypothetical curve close to the Imperial College’s Projected COVID-19 Deaths if they were reported weekly. With ample trial and error, I was able to roughly simulate the time frame (May~August) and peak intensity with my curve, while getting the area under the curve to total 2,200,000 American deaths from COVID-19. I then scaled this same curve to also simulate 1,100,000 and 300,000 deaths occurring before the end of August. Each of these Projected Excess COVID-19 Weekly Death simulations was then stacked on the Historical Average of All Deaths Reported Weekly for the accurate reference.
...
Open society back up now, while focusing on:
- Protecting nursing homes, assisted living, and other vulnerable populations
- Repairing those with lives destroyed by the reactions to the virus
Make American [Partially] Free Again
Cross-Posted:
https://youtu.be/7hjVhvgNlhQ
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Some related videos I recommend…
The Failure of Expert Predictions and Models | The Coronavirus and Public Policy
https://www.youtube.com/watch?v=mG2vdyfLv7U
Why lockdowns are the wrong policy - Swedish expert Prof. Johan Giesecke
https://www.youtube.com/watch?v=bfN2JWifLCY
Perspectives on the Pandemic | Dr. John Ioannidis Update: 4.17.20 | Episode 4
https://www.youtube.com/watch?v=cwPqmLoZA4s
The Coronavirus and the Constitution | The Coronavirus and Public Policy
https://www.youtube.com/watch?v=rlcl72is3EU
Shelter in Place with Shane Smith & Edward Snowden (Full Episode)
https://www.youtube.com/watch?v=k5OAjnveyJo
