about being liberal or conservative anymore y'all. That is a hype offered by the fascist whores who want to confuse the people with lies while they turn this country into an aristocratic police state. Some people will say anything to attain power and money. There is no such thing as the Liberal Media, but the Corporate media is very real.
President Trump’s surprisingly sober press conference on Monday was reportedly sparked by a British study suggesting that the U.S. could face 2.2 million fatalities if the coronavirus epidemic goes unabated.
The report ... was put together by a team of epidemiologists at Imperial College London.
[SOURCE:Josh Kovensky | Talkingpointsmemo.com | 17 March 2020]
Tuesday, 17 March 2020 at 12h 44m 7s
I am updating an exponential model of the data from SF
Click here for a Desmos exponential regression model that I am doing with data that is daily released from San Francisco.
Right now, the a value is how many times more people are probably infected. The b value is the percentage of increase in the rate of infections. Add one to get a growth factor. Multiply the a value to the current number of infections to get an estimate of the actual number infected. Then use the initial value multiplied to the growth factor raised to the 14th power to model how many infections are possible at a minimum.
Hence, I get 768 infected, if we assume that the current actions of "shelter at home" and "social distancing" have had a mitigating effect. An 11.6% is based solely upon the current low rate of testing that has occurred. More likely over the rest of the week, that rate of increase will be higher.
For instance if that last data point goes from 43 to just 50, the rate of increase goes from 11.6% to 13.28% and the initial "a" value becomes 3. Doing that calcultion, 3 times 50 multiplied to the growth factor of 1.1328 to the 14th power ... you get 859 people infected after 2 weeks.
Notice how quickly the expansion can occur just by going to 43 to 50. 768 becomes 859.
I bet it's more like 150 (because of the a value). If you put that in the model, the rate of increase becomes 54% -- which translates (hold your breath) into 63,296 infected after 2 weeks.
Holy shit. That's why this is serious. Because that 63,296 is more likely already baked in, and would become 1.3 million by the end of the 3rd week if nothing had been done.
UPDATE ON METHOD: I am using an exponential model on the statistical data using euler's constant ( y=ae^bx ) in order to obtain parameters that I use in a growth factor exponential model ( y=a(1+b)^x ) in order to get the best and worst case scenarios.
Monday, 16 March 2020 at 16h 50m 50s
The Covid-19 Recession
This is called "Flattening the Pandemic and Recession Curves", presented at Princeton University by UC Berkeley Economics Professor Pierre-Olivier Gourinchas. The lecture is a good discussion about how the means of containing and eliminating the pandemic are related to the inevitable recession.
In a perfect world, people would self-isolate until infection rates decline sufficiently and public health authorities give the all-clear ...
The first thing to note is that, even in that "perfect" world, the economic damage would be considerable. To see this, assume that, relative to a baseline, containment measures reduce economic activity by 50% for one month and 25% for another month, after which the economy returns to the baseline...
That scenario would still deliver a massive blow to headline GDP numbers, with a decline in annual output growth of the order of 6.5% relative to the previous year. Extend the 25% shutdown for just one more month and the decline in annual output growth (relative to the previous year) reaches almost 10%.
As a number of economists have pointed out, most of this lost GDP will not be coming back, so it is reasonable to assume a return to the baseline, rather than a later surge ... We are about to witness a downturn that could dwarf the "Great Recession" [of 2008-09]
[SOURCE:Pierre-Olivier Gourinchas | Professor of Economics, UC Berkeley | 13 March 2020]
In an earlier post I used the data from Italy (which is a good example of what can happen in the Bay Area) to discern that a 19% daily rate of increase and 6.5% of current cases known is quite possible. Which means there are people walking around spreading the disease who do not realize it for 3 or more days before they start feeling the symptoms. Already San Francisco has gone from 21 to 28 to 37 in a matter of 3 days. That's called exponential growth, which can very quickly reach 1,000 depending on the underlying growth rate, which cannot be measured effectively since we very likely are only aware of 6.5% of cases (see above).
So if 37 is only 6.5% of the actual cases, that means we have 569 now. And if that increases at the rate of 1.32 (37/28) for 2 weeks, we are looking at 27,742 cases -- and this assumes the general population takes preventative actions now, because if that rate of growth expands for 3 weeks, we are looking at 193,715 cases by early April, 5% or more of whom will possibly die (at least 9,685).
[SOURCE:Ida Mojadad | San Francisco Examiner | 15 March 2020]
I know it sounds rash but I would be staying at home and not going anywhere unless you need to. No hanging out at cafe's and bars and going to restaurants, because otherwise you will be responsible for potentially spreading the virus to vulnerable populations -- in addition to yourself.
I live in a building with a lot of elderly people. We touch the same doorknobs, stairway bannisters, and use the same elevator.
Going from 21 cases on February 21 to 1,128 on February 29 ... 8 days later. 5,883 another 7 days later. 17,660 6 days later. Which means a caseload nearly 10,000 times larger than on February 21st, over a period of 3 weeks !!!!
There are (according to the worldometers website) in Italy 21,157 cases and 1,441 deaths. That is 6.8%. Out of active cases, 9% are in serious condition. Out of all current Cases that had an outcome, 42% have died.
Here is a link to Desmos where I took the above data from bullet #1 and exponentially regressed to euler's number. The B value is the percentage of increase. It's 19.1% per day which means a 1.191 growth factor. Look at that A value, 320. That's the number of people the model predicts to have been the actual number of infected people on 21 February. Hence the model says only 6.5% of all current cases have been discovered. Notice that the R squared is 99%. Statistically that means 99% of the variation can be accounted for by the passage of time alone. Holy shit.
Now I know that sounds really scary, and I admit that I myself am freaked out. However, take a deep breath. Right now in San Francisco and the Bay Area we are at February 21 on the potential exponential growth model. Since our local governments initiated school closures and cancellations of all public events for the next month, there is an outside chance that we can avoid what is happening to Italy right now. If we stay at home and go outside only if absolutely necessary, then the curve will flatten out. Because of the Bay Area's density and mild climate this virus has the potential to hit us the same way it hit Italy, with the same mortality rates.
That's why schools are closed all over the Bay Area. This is not a hoax. Unmitigated, this virus has the potential to kill 5% of the population at a minimum. 5% of 10 million is 500,000 people. Not to mention the stress on our fucked up health care system.
Saturday, 14 March 2020 at 12h 27m 29s
Mark's Daily Apple on Dairy
Click here for what Mark Sisson has to say about Dairy products. Mark is my go to source when I have questions about nutrition. His marksdailyapple blog is excellent for good nutrition advice -- as opposed the the mythology that has captured the discourse since the low-fat mantra became the standard assumption of how to be healthy and live-long.