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When will the Media and the People in Position of Authority start telling the truth to Americans concerning the risk profile of Covid-19, instead of fomenting panics and hysteria.

When will the Media and the People in Position of Authority start telling the truth to Americans concerning the risk profile of Covid-19, instead of fomenting panics and hysteria.
It is something else to listen to the media again explaining they are doing a great job when every night all they do is feed anxiety of their audience, including parents and children. Shame on them all...again. Yes, again, because this is the new culture of the past 30 years, where every new knowledge on psychological manipulation quickly finds its way at the top of the Nightly News techniques.
For example, the numbers we hear every night, when they are not visually thrown in our faces. Let's try to bring some pondering to this.
Even some"specialists are being caught explaining the big dangers in the "death rate" of this virus..."for seasonal flu: Its is 0,1% and here for Covid-19 it is 1,5%, even higher in China, up to 3,5%..."
This is the ultimate of Fake news, something comitted out of naivete, from experts whom trust other experts, whom have spoken to a more bigger expert, etc...and sometime out of straight malicious intent.
These media "people" are comparing oranges and apples in the most classical style.
And I will try, so as to not add to the confusion, to take the example of the Seasonal flu to make things clear. From the Weekly U.S. Influenza Surveillance Report on the CDC website we can read:
https://preview.redd.it/tcefzh9ssop41.png?width=1144&format=png&auto=webp&s=fbc6d5fce7af2494ea65965d98516deff965e723
From: Weekly U.S. Influenza Surveillance Report Week 12 2020 (take note that week 12 extended about 10 days because of the Covid situation). Further, this is week 40 of the whole Season, which starts of Sep 29 2019, and week 12 in 2020.
Now, in the top blue section you can read:
at Least 39 million flu illnesses;
400,000 Hospitalization;
24,000 Deaths from flu.
Illnesses must be understood strictly as an Estimation (it is also referred to as infection, infection rate, infection in the population, illness in the population). This is important, because just after they say Hospitalization, this is almost entirely a measured amount, very little is estimated. Then the Deaths (also often referred to in the literature as the fatalities, and of which some may be estimated and others counted).
Then in the table you see how much total tests where employed up to March 21st (Cumulative). That is 1,2 Million people where tested for the common seasonal flu. Of these, 242,330 tested positive. This results with a 20% positive rate of testing. The number you hear every night blasted into your eyes and ears is this last number, the tested positive cases, which they refer to simply as the "cases".
Now, you must understand that there is a technique the CDC employs to make the estimation of infected people in the population. They use a multiplier, this multiplier is sometime used against the tested positive cases, sometime against the hospitalization level.
An early estimation made by the CDC in 2009 concerning the Swine Flu H1N1 (2009) was a multiplier of 79. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009
"...23 July 2009, a total of 43,677 laboratory-confirmed cases, 5009 hospitalizations, and 302 deaths had been reported to the Centers for Disease Control and Prevention (CDC)..."
In this case, you multiplied 43,677 confirmed cases against the multiplier 79 = 3,450,000 estimated illnesses.
That is Cases confirmed x Multiplier = Estimated illnesses (or infections) in the general population.
By the end of the crisis, this multiplier had increased quite a bit. Because the last Illness estimation was 61,8 million infections and 240,000 hospitalization. Doing the reverse calculation we get:
61,800,000/240,000 = 257...this was the end multiplier. So, from the July cumulative data of 2009, the multiplier was 79, but by the end of the crisis in may 2010, this multiplier increase about 3 fold to become 257.
An intermediate multiplier from data up to October went as follows:

https://preview.redd.it/xo2sw4cmsop41.png?width=644&format=png&auto=webp&s=76403f385be2c3b7b4c5dec657d63d2b9c331edb
From the CDC report "2009 H1N1-Related Deaths, Hospitalizations and Cases:Details of Extrapolations and Ranges: United States,Emerging Infections Program (EIP) Data
AS you can read: Calculate cases (which here is the wrong expression and it creates confusion, it should read: Calculate illnesses or infections): Multiply Hospitalization by 221,79.
So right here, is where the CDC often uses the term Cases when they should use Illness or Infections, because in most reports when they use cases, it means diagnosed confirmed cases, not estimation in the population of illness. Fauci himself is often caught in this confusing and misleading language.
You can see for yourself from the same document, they estimated cases by November 2009 to be 14 to 34 millions. Clearly this is the Illness level, not the confirmed cases.

https://preview.redd.it/x2vvbt2qsop41.png?width=640&format=png&auto=webp&s=d41d2205758d8281e4c0f42f0fd15f7f14403bb9
Now, the whole media is stuck up in this hysterics by making you believe that you have 1 chance in 50 of dying or so if you catch the virus...that is not true. In fact, you had, for H1N1 less probability of dying from H1N1 than from the seasonal flu by a ratio of 3 to 1.
Currently, neither the CDC nor the WHO have calculated a Multiplier for Covid-19. The Total rate of Hospitalization is difficult to have. On the 25 of March, Andrew Cuomo, in a press conference live on NPR explained that about 1 in 5 confirmed cases is hospitalized currently. On that day, The larger NY City area had about 25,000 cases confirmed, which mean they had about 5,000 hospitalization.
A paper earlier this month from the CDC Mortality and Morbidity Weekly: Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19) an early report when they were 4229 confirmed cases across the US, had a rate of hospitalization of 58% (2,449 out of 4229).
Some independent papers have calculated tentative Multipliers. It's the case of the paper which was used for the structure of the article in the NYTimes of March 20th "Coronavirus Could Overwhelm U.S. Without Urgent Action, Estimates Say". The paper is entitled "Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)" The problem with the NYTimes is that they used color saturation excessively to terrorize people, like they do with Hurricane maps, when they want the people to listen. They don't say how the authors of the paper contributed to its use by the NYTimes. The NYTimes explains that they used their database of Covid pandemics from US cases.But the 500,000 new cases per day appears an exageration...But the scientific paper is excellent, it uses a complex statistical mathematics modeling which is explained over 30 pages Supplemental data.
There might be some short comings, like there always is in these kinds of work, firstly because many parameters must be estimated. And further, for example, some of the tools they use make the assumptions of Gaussian distributions, when progressively it is understood that epidemics, like the weather and networking are non-linear distributions. For example, they use what is called an Ensemble Adjustment Kalman Filter. A model developed in2008, as an adjustment or refinement on the original 1950 Ensemble Kalman Filter. But in climate science,which obeys to laws where the 4 parameters of a distribution are mobile, the Gaussian has only 2 of these, the Mean and the Variance, while the 2 others Kurtosis and Asymmetry are fixed at 2 and 0 respectively.
Parameters of the Standard Normal Distribution are (2,0,1,0), Kurtosis (alpha α ), Skewness (Beta β), Standard Deviation (Sigma σ ) and Mean (Mu µ) respectively.
From the wikipedia Stable Distribution page: https://en.wikipedia.org/wiki/Stable_distribution
The Stable Distribution has always been the parent of most probability distributions, the normal distribution just being a special case of it. The Stable distribution s very complex, to me also, and many attempts have been made over the decades to make integration in many linear models so they perform with better likelihood. Recently, an academic paper has created a more pragmatic approach to it : "...this paper attempts to present a uniform analytical approximation for the stable distribution based on matching power series expansions. For this solution, the trans-stable function is defined as an auxiliary function to evaluate the stable distribution." Asymptotic Expansions of the Stable distribution.
For a graphic represention of the fluidity of the Stable Distribution in regard to the sensitivity of a change in its papameters, you can go to John P Nolan's page.
Recentely, to better adapt the Kalman Filter, climate science has created the Local Ensemble Adjusted Kalman Filter which makes use of of outlayers instead of doing data softening. Network Theory also has made adaptation to take into account the non-linearity of dynamics modeling. Epidemiology is a close relative of both Climatology and Network theory.
Non-Gaussian statistics in global atmospheric dynamics: a study with a 10 240-member ensemble Kalman filter using an intermediate atmospheric general circulation model :
"This study also discusses how many ensemble members are necessary to represent a non-Gaussian PDF (probability distribution function) without contamination due to the sampling error, as higher-order non-Gaussian statistics are generally more vulnerable to the sampling error due to a limited ensemble size."
From the result of their paper, you can infer a multiplier, they used the Wuhan Proving data of Confirmed cases, which stood on the 24 of January at 370. From there, they estimated that 13,118 people were infected in the population. So 13,118/370 = 35. Would this be a reliable multiplier to use against the confirmed cases in the US...it is very difficult to say.
Another original statistical approach is by Tian Hao,Infection Dynamics of Coronavirus Disease 2019 (Covid-19) Modeled with the Integration of the Eyring's Rate Process Theory and Free Volume Concept
I won't explain his approach, but is a short cut approach when too many parameters must be evaluated. His multiplier is 10.
Using the Spreadsheet available at the CDC on the REED's model for Multiplicator, I obtained a multiplier of 110, when confirmed cases were 19,240 in the US. My feeling was that this was a bit high, I thought, from reading quite a bit that would be between 40 and 90. But I made some assumptions myself for lack of information.
But these multiplier may give you an idea of what is the real fatality risk of Covid 19.
For example, with a multiplier of 10, today March 29, with 125,000 cases in the US and about 2000 fatalities, you first calculate the Case Fatality Rate (CFR): 2,000/125,000 = 1,6%.
Then you calculate the Infection Mortality Rate, dividing the CFR by the multiplier:
1,6% / 35 = 0,046%
1,6% / 10 = 0,16%
So, you sit between a bit more than the Seasonal Flu, to half of it.
But these numbers may be misleading because a pandemic is something unique for which there is no empirical data, unlike the seasonal flu. Further, because of the massive rapid distribution, a different time of reactions of authorities, the different social structures where the virus may settle...Chronic events statistics, such as those of the seasonal flu, and those of exceptional event, may not really compare and may misinform. What is important to understand, is that the number of cases you see in the media for Covid-19 do reflect the amount of people infected in the population. So the case mortality rate doesn't reflect your probability of death if you catch the SARS-CoV2 virus.
The WHO explained this in detail in the Situation Report 46 (note here they use the term Crude, from the British, instead of Case: but they o use Infection Mortality Rate):
"Mortality for COVID-19 appears higher than for influenza, especially seasonal influenza. While the true mortality of COVID-19 will take some time to fully understand, the data we have so far indicate that the crude mortality ratio (the number of reported deaths divided by the reported cases) is between 3- 4%, the infection mortality rate (the number of reported deaths divided by the number of infections) will be lower. For seasonal influenza, mortality is usually well below 0.1%. However, mortality is to a large extent determined by access to and quality of health care."
It's the same thing with the new expression so popular among the Press, the Reproduction Rate (or Replication Rate). They say it's so high...blablabla...The thing is that they forget to mention that the Replication rate always starts high and then falls shortly towards, and eventually below, 1.
It's not that this situation doesn't call for attention, and action, it is just the tone which is irresponsible by many people in position of authority. We are not helping ourselves by being anxious, and projecting this anxiety on our environment and loved ones.
For example, an early estimation of the H1N1 virus Pandemic was for:

  • US pop: 300 million
  • Cases (read illness or infection): 46 million (37 - 55 million)
  • Hospitlizations: 2.8 million (2 - 3.6 million)
  • On ventilators: 132,000 (228,000 - 454,000)
  • Deaths: 192,000 (126,000 - 226,000)
Zilberberg MD, Sandrock C, Shorr A. Swine origin influenza A (H1N1) virus and ICU capacity in the U.S.: are we prepared? In: PLoS Currents: Influenza. August 22, 2009. (Accessed October 22, 2009, at http://knol.google.com/k/marya-d-zilberberg/swine-origin-influenza-a-h1n1-virus-and/3htiswudddv6h/1#. opens in new tab.)
In the end there were:
61,8 Million illnesses
240,000 Hospitalization
12,470 deaths
A departure, but early forecasts often suffer from this wide excesses. But, lets contain, lets mitigate, and let's not panic...and tell your media they should learn to speak English or French instead of Anxiety, music having always been my first language (as a listener of course)...
submitted by Denys_Picard to u/Denys_Picard

Q1 2020 Letters & Reports

Investment Firm Date Posted
A Primer on Reading Annual Reports April 7
Absolute Return Partners April 7
Bankruptcy Law Primer April 7
Berkshire Hathaway Annual Report April 7
Crescat Capital - Blood in the Streets April 7
Fundsmith April 7
Glasshouse Research - Cubic Corp April 7
Grants - Grand Tour of Junk April 7
Hindenburg Research - HF Foods April 7
Horizon Kinetics - March 20 April 7
Horizon Kinetics - March 25 April 7
Howard Marks Memo - March 3 April 7
Howard Marks Memo - March 19 April 7
Howard Marks Memo - March 31 April 7
J Capital - GDS Holdings April 7
James Montier - Fear and Psychology of Bear Markets April 7
Jamie Dimon April 7
JDP Capital April 7
JPMorgan - Guide to the Markets April 7
Oaktree Capital - Assessing Relative Credit April 7
Oaktree Capital - Risks and Opportunities in EM April 7
O'Shaughnessey Asset Management April 7
Pershing Square Capital - Annual Letter April 7
Pershing Square Capital - CDS Trade April 7
Sequoia Fund April 7
Spruce Point Capital - WD-40 April 7
Wedgewood Partners April 7
Wolfpack Research - IQIYI April 7
Akre Focus Fund April 8
Alliance Bernstein Long Cap April 8
Bill Nygren Commentary April 8
Howard Marks Memo - April 7 April 8
Vltava Fund April 8
Vulcan Value Partners April 8
Bluehawk Investors April 9
Boston Omaha April 9
Driehaus Life Sciences April 9
Riverpark Floating CMBS April 9
Riverpark Large Growth April 9
Riverpark Long Short Opportunity April 9
Schiehallion Fund April 9
Thornburg Global Opportunities April 9
Brown Advisory April 10
GMO White Paper April 10
Mawer April 10
Newfound Research April 10
Templeton and Phillips April 10
Universa Investments April 10
FPA Crescent Fund Transcript April 11
Third Avenue Value Fund April 11
Desert Lion Capital April 12
Massif Capital April 12
Muddy Waters - eHealth April 12
Turtle Creek April 12
UBS 2020 Real Estate Report April 12
Crescat Capital April 15
Howard Marks Memo - April 14 April 15
Longleaf Partners April 15
Madison Investors Fund April 15
Pabrai Funds April 15
St. James Investment Company April 15
Antipodes April 17
Artisan Mid Cap April 17
Baron Funds April 17
Cooper Investors April 17
David Herro April 17
Ensemble Fund April 17
Jeff Bezos Annual Letter April 17
KKR Global Macro Insights April 17
Robotti April 17
Summer Value Partners April 17
Third Point Capital April 17
Tweedy Browne April 17
Whitebrook Capital April 17
Harding Loevner April 18
Kuleana Capital April 18
Mairs & Power April 18
McKinsey - The Future of Travel April 18
RPIA April 18
Silver Ring Partners April 18
Third Point Capital April 18
Upslope Capital April 18
Rhizome Partners April 20
White Crane Capital April 20
Canterbury Tollgate April 21
Elliot Management - Perspectives April 21
O'Shaughnessy Asset Management April 21
Baron Funds April 21
Diamond Hill April 23
Evermore Global Value April 23
Giverny Capital April 23
Kerrisdale Capital - Short Thesis on Mirati Therapeutics April 23
Maran Capital April 23
Wolfpack Research - Short Thesis on Inspire Medical Systems April 23
Ewing Morris April 24
Hoisington April 24
Horizon Kinetics April 24
Merrill Lynch Capital Markets Outlook April 24
RGA Advisors April 24
Gardner, Russo & Gardner April 26
Greenhaven Road Capital April 26
Polen Focus Growth April 26
Polen Global Growth April 26
Steel City Capital April 26
Guggenheim CIO Outlook April 28
Hindenburg Research - Short Thesis on New Pacific Metals April 28
Laughing Water Capital April 28
Miller Deep Value April 28
Miller Income Strategy April 28
Miller Opportunity Equity April 28
Newfound Research April 28
Quintessential Capital - Short Thesis on Akazoo April 28
RF Capital April 28
White Diamond Research - Short Thesis on BioSig April 28
Open Square Capital April 29
TCI Fund - Letter to Wirecard April 29
Alluvial Capital April 30
Arquitos Capital April 30
Bessemer - State of the Cloud Industry April 30
Broyhill April 30
Alta Fox May 2
Boyar Value May 2
SRK Capital May 2
Distillate Capital May 3
First Eagle Fund of America May 3
First Eagle High Income May 3
First Eagle Income Builder May 3
First Eagle Value May 3
Wolf Hill Capital May 3
Angelo Gordon May 5
Citron - Short Thesis on Inovio May 5
Convexity Maven May 5
Graham & Doddsville - Spring 2020 May 5
Grizzly Reports - Short Thesis on WUBA May 5
Tao Value May 5
Universa on Tail Hedging May 5
Health Invest Partner May 7
Amalthea Capital May 10
Amana Mutual Funds May 10
Andvari Associates May 10
Alphyn Capital May 10
Blue Tower Asset Management May 10
Hayden Capital May 10
Horos Asset Management May 10
LRT Capital May 10
Palm Valley Capital May 10
Paul Tudor Jones May 10
Sextant Mutual Funds May 10
Steel City May 10
Third Avenue Real Estate May 10
Third Avenue Small Cap May 10
Tidefall Capital May 10
Touchstone Funds May 10
Bernzott Capital Advisors May 11
Compound Everyday Capital May 11
Comus Invest May 11
Greenwood Investors May 11
Guggenheim Investments May 14
Elliot Management - Alexion May 14
HG Capital Trust May 14
Huffman Prairie May 14
Independent Franchise Partners - Kirin May 14
Tao Value - Strategy May 14
Value Investor Insight - Bill Nygren May 14
Credit Suisse - Global Money Notes May 15
Howard Marks Memo - Uncertainty May 15
Logica Funds - Talking Your Book About Value May 15
Mittleman Brothers May 15
Top Retail Brands May 15
Donville & Kent May 16
Goehring & Rozencwajg May 16
Apollo Asia Fund May 18
Bonitas Research - Short Thesis on Pets at Home May 18
Culper Research - Update on Catasys May 18
Hindenburg Research - Short Thesis on China Metals Resource Utilization May 18
Lightsail Capital May 18
Muddy Waters - Update on Burford Capital May 18
Spruce Point Capital - Short Thesis on Forescout Technologies May 18
Verdad - High Yield May 18
KKR Global Macro Trends May 20
Lightsail Capital May 20
FPA Crescent Fund May 20
Aoris May 22
Giverny Capital Asset Management May 22
Bireme Capital May 25
Greenhaven Road Partners Fund May 25
Hindenburg Research - Short Thesis on Sorrento Therapeutics May 26
Land & Buildings - Short Thesis on Empire State Realty Trust May 26
Muddy Waters - Short Thesis on GSX May 26
Viceroy Research - Short Thesis on Sorrento Therapeutics May 26
JLL - US Office Outlook May 27
Massif Capital - Long Thesis on Bakkafrost May 27
Bonhoeffer Fund May 29
Howard Marks Memo - Uncertainty II May 29
Muddy Waters - Update on GSX May 29
Citron Research - Long Thesis on RH June 1
CloudyThunder Research - Short Thesis on Tianneng Power June 1
Horseman Capital June 1
JCapital Research - Short Thesis on NovaGold June 1
Asset Value Investors - Fujitec June 7
GMO June 7
Grizzly Research - Report on GSX Techedu June 7
Michael Mauboussin Report June 7
Culper Research - Short Thesis on VBI Vaccines June 9
Grizzly Research - Short Thesis on Hebron Technology June 9
Muddy Waters - Short Thesis on EHTH June 9
OSS Research - Short Thesis on Tactile Systems June 9
JPMorgan Guide to Alternatives June 11
Michael Mauboussin - The Math of Value and Growth June 11
Morgan Stanley - Gaming & Lodging Primer June 11
Old West June 14
Arisaig June 15
A Guide to Social Media in China June 18
Brookfield Asset Management June 18
First Eagle June 18
Pender Funds June 18
Peter Lynch Collection 1993 to 1999 June 18
Prescience Point Capital - Short Thesis on Enphase Energy June 18
Pzena - Extreme Discounts in Oil Services June 18
Alta Fox - Evolution Gaming Thesis June 19
Alta Fox - Letter to Collectors Universe June 19
Crescat Capital June 19
Howard Marks Memo - June 18 June 19
J.P. Morgan CIO Survey 2020 June 19
Cambridge Associates - Managing Portfolios Through Downturns July 1
Citron Research - Sonos July 1
JCapital Research - Ideanomics July 1
JCapital Research - WiseTech Software July 1
Logica Funds - Talking Your Book About Value III July 1
Interviews & Lectures Date Posted
Bill Ackman - Bloomberg April 7
Bill Ackman - CNBC April 7
Jim Chanos April 7
Murray Stahl April 7
Oaktree Capital - Emerging Markets April 7
Oaktree Capital - Relative Value April 7
Steve Bregman April 7
Fundsmith Annual Meeting April 8
Grant Williams 2020 Series April 9
Barry Diller April 17
Willow Oak Value Hour April 17
Ray Dalio - Bloomberg April 18
Invest Like the Best - Dan Rasmussen April 18
Invest Like the Best - Gavin Baker April 18
Masters in Business - James Montier April 18
Carl Icahn - Bloomberg April 26
Greg Maffei - CNBC April 26
A Shift in Investment Strategies Post Coronavirus April 28
Bill Ackman - Farnam Podcast April 29
Jim Chanos on Financial Fraud May 3
Sam Zell - Bloomberg May 5
David Tepper - CNBC May 15
Stanley Druckenmiller - ECNY May 15
Howard Marks - Bloomberg May 18
Jerome Powell - 60 Minutes May 18
Chris Bloomstran May 20
Gavin Baker - CSIMA May 20
Howard Marks - CFA May 20
CFA Institute Virtual Conference May 25
Jorge Paulo Lemann May 26
Invest Like The Best - Jeremy Grantham June 11
Peter Kolchinsky and Kush Parmar on Biotech Investing June 18
Horizon Kinetics - Economically Resilient Business Models June 18
Bruce Flatt June 19
Bill Ackman July 1
Jim Chanos July 1
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