It's not
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.

During times of crisis it is more important than ever to know who can be relied upon for truthful honest information that is not doctored, colored, or edited for political calculations or reasons. Recently the Prezident has become so unable to perform these basic duties that news media outlets (including Fox news) have been skipping the live feeds of the Presidents news conferences and tuning into New York Governor Andrew Cuomo -- who is rising into the leadership role of this crisis.

Meanwhile the prezident keeps making statements at these press conferences saying things that his administration is doing that are not being done, coloring his administration's actions as something other than complete narcissistic incompetant denial, calling the virus a "chinese" virus despite the ignorant insensitivity of such a statement (it's a bat virus by the way which could have jumped to a human host anywhere in the world where bats are located) and pretending he didn't say things he did that are on tape and were seen by the American people not even 3 weeks ago.

Rather than taking charge and addressing the needs of our country, his people see this as a public relations management operation, an opportunity to pursue their overall agenda.

Here is a link I use to click on all of the relevant newspapers throughout the United States and world. You cannot rely on what is given to you on your twitter feed or mainstream media, even if it is high quality. Some of these newspaper/media outlets are better than others by a very large margin, but I'll let you make those discerned views on your own.

Thursday, 19 March 2020 at 10h 10m 22s

SF Infections jump from 51 to 70

Click here for my regression model update. a = 2.59 b = 0.138954 which projects into 1,120.68 over 2 weeks (using the method I explained in an earlier post) AND 2,786.29 after 3 weeks.

1,120.68 = 70×2.59×(1+.138954)^14

2,786.29 = 70×2.59×(1+.138954)^21

That may not seem like a lot, but that cannot include the ancillary infections that are occuring because people are asymptomatic, so we don't really have good data on the rate of infection. That's why the growth rate of the model fluctuates, now at 13.89% increase per day. If the latest number (70) is actually 75, the model jumps to a 14.7% increase per day.

9:16 a.m. San Francisco now has 70 confirmed COVID-19 cases: San Francisco announced there are 70 confirmed cases of COVID-19 in the city, an increase from 51 on Wednesday, according to the Department of Health.

There were 8 more cases of COVID-19 released at 9:58 am today by the City Department of Public Health. The model is now 3.685 times the number of cases with an 11.88% rate of increase per day ... from 3.82 and 11.6 as of yesterday.

Here is an image

So for instance, running those numbers, I get 1,986 infected over another 3 weeks. Here's how. 1 + .1188 = the growth factor. Raise that to the 21st power (3 weeks) and multiply 51 (the current number). Then multiply 3.685 which the model estimates as the number of unknown infected cases. That's how I got 1,986.

The above analysis comes with huge reservations because the lack of testing leaves us blind. We have no idea how many unknown carriers are out there. Hence that multiple of 3.685 from the model is not reliable. If it is actaully 5, then we arrive at 3,564 cases after 3 weeks, a lot of whom likely infected other people over that duration. Currently it appears the doubling rate is over 5 days, which implies 24,821 cases over another 2 weeks. Full disclosure: I got that by doing 2 raised to the 14/5 power and multiplying to 3,564.

Once you start doubling big numbers over 5 or less days (like what happened in Italy) we got a real health crisis even if the mortality rate is between 1 and 2 percent. If half of the 350 million US population contracts this, 1% of 175 million is 1.75 million people dead. That is more in one year than all of the combined total casualties of war for the United States dating back to the Revolutionary war.

Poof ... mind is blown.

Tuesday, 17 March 2020 at 17h 23m 32s

Science

Be thankful that our health authorities and government leaders made the decisions they made. This is not a hoax. The threat is 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]