BAYES' THEOREM: The basic reason we get so many false positives to COVID19. The disease is so rare that the number of false positives greatly outnumbers the people who truly have the disease: THE MATHS:
https://t.co/oLHyxYJW9H

"Suppose that you are worried that you might have a rare disease. You decide to get tested, and suppose that the testing methods for this disease are correct 99 percent of the time"
"Suppose this disease is actually quite rare, occurring randomly in the general population in only one of every 10,000 people. If your test results come back POSITIVE, what are your chances that you actually have the disease? LESS THAN 1% chance that you have the disease!"
"The basic reason we get such a surprising result is because the disease is so rare that the number of false positives greatly outnumbers the people who truly have the disease"
Say mass testing of the contagious virus was done to 1 million people. In that million, 100 will really have the disease, 99 will be correctly diagnosed as having it. 999,900 of the million will not have the disease, but of those about 9,999 will be false positives! #BayesTheorem
1 in 2,000 INCLUDING FALSE POSITIVES classifies Covid19 as a rare disease in winter 20-21
https://t.co/29FNwq0Qw2
Stefano Scoglio, Nobel prize candidate 2018, has calculated a real false positive rate of 95% from official Italian Health Service numbers. This is in line with #BayersTheorem. Calculation in links in thread:
https://t.co/rthjPRJWeB
If we apply the 95% false positive (Scoglio) back to England positive test % incl. false positive: 0.05% (ONS), we get a real % of positives in England of 0.0025% of the population, or 1 in 40,000 people. This would confirm Covid19 as a rare disease as per #BayersTheorem.
Try this calculator for up to 100 tests. https://t.co/5TKEYpjd80
Severe Covid19 is a rare disease in England, if tests are 100% accurate, acc. to hospitalization numbers, it's 0.02% or 1 in 5,000 people.
https://t.co/kFnQVoCspb
#BayesTheorem applied to LF tests: https://t.co/3OrdS7ZFUJ
A simple example of #BayesTheorem with a prevalence of 0.1% (much higher than Covid19) an error range of 1% (RT-PCR Charité range est. 0.8-4%) and only 1,000 people tested: 91% false positives.
#BayesTheorem in simple terms: when medical mass testing includes asymptomatics & the disease affects a minority of the population, a very small margin of error in the testing process will mathematically result in the false positives being many times more than the real positives.
"Covid19"[😞] mass testing graph from The Economist. Y axis being % of test results either true or false. As share of population with active infection (X axis) is well under 1%, most positive tests are false, & most negative results are true. This is called #BAYESTHEOREM.
Latest England estimates:
https://t.co/8hsZ1hNjD7
How to increase the prevalence of a rare disease from 0.01% to 1%? Test the asymptomatics. What prevalence do we estimate Covid19 at including asymptomatic tested? Less than 1%. What could the true prevalence be if we exclude asymptomatic testing? 0.01%. It's called #BayesTheorem
Proof that Matt Hancock is aware of #BayesTheorem, he mentions Bayesian mathematics: https://t.co/hpZYDzD5Pe
As Matt Hancock is clearly aware of #BayesTheorem, if he wanted to avoid the false positives being many more than the true positives, he would not say ONS is applying rigorous Bayesian mathematics, he would instead not implement testing of any asymptomatics not linked to a case.
Matt Hancock is pre-empting the #BayesTheorem false positive trap by mentioning Bayesian mathematics himself in reply. A Freudian slip, a lapsus which reveals what he is really thinking: how do I increase false positives to make Covid19 prevalence appear worse than it really is?
So how does he do it? He implements mass testing of asymptomatics in Universities, then schools. He uses the hierarchical power structures in these institutions to convince healthy students they need to be tested. The schools get closed on false positives, false fear is created.
#BAYESTHEOREM @ Cambridge University. 0.4% of 262 students came back as positive after the first "test". All came back as negative after the second. Government only tests once. ONS would say there is 0.4% prevalence instead it's 0%.
#BAYESTHEOREM @ Cambridge University. 0.5% of 1,937 students came back as positive after the first "test". All came back as negative after the second. Government only tests once. ONS would say there is 0.5% prevalence instead it's 0%.
Sorry this should say 0.4% of 263 students https://t.co/eSNnhyOI4n
See what happens in #BayesTheorem? Number of asymptomatic testing increases & the estimated prevalence of the disease increases!! This can be addressed by requiring confirmatory tests of those who test positive when numbers are small, otherwise DON'T test asymptomatics.
Cambridge Pooled Testing Report #BayesTheorem
https://t.co/BYIzoTl64c
To have the same number of false negatives as false positives you need a disease that is present in 30% of the population. Covid19 affects less than 1%. This means the false positives VASTLY outnumber both the real positives & the false negatives. It's called #BayesTheorem.
Matt Hancock claim: "the ONS report..address directly the question how the ONS adjusts for potential false positives, due to the high but not perfect specificity of the PCR test. I am very happy for one of my academics to take him through the rigorous Bayesian mathematics"
"I am very happy for one of my academics to take him through the rigorous Bayesian mathematics, which I am sure will help to elucidate the debate on this matter still further." @MattHancock to @DesmondSwayne
https://t.co/pZcFlMBKEZ
I am waiting for one of @MattHancock's academics to take us through this as I have seen no evidence of @ONS adjusting for false positives according to #BayesTheorem https://t.co/ykB67TJORe
Professor Emeritus in Public Health, University of Arizona:
https://t.co/aidVGWOVqH
WHO wakes up to #BayesTheorem https://t.co/nDKklwMhQe

More from Robin Monotti FRSA MA BSc

I have now re-examined this document:


It clearly does indicate both the risks of bacterial infection & to prescribe broad spectrum antibiotics as part of treatment:
"Collect blood cultures for bacteria that cause pneumonia and sepsis, ideally before antimicrobial therapy. DO NOT
delay antimicrobial therapy"

"6. Management of severe COVID-19: treatment of co-infections
Give empiric antimicrobials [broad spectrum antibiotics] to treat all likely pathogens causing SARI and sepsis as soon as possible, within 1 hour
of initial assessment for patients with sepsis."

"Empiric antibiotic treatment should be based on the clinical diagnosis (community-acquired
pneumonia, health care-associated pneumonia [if infection was acquired in health care setting] or sepsis), local epidemiology &
susceptibility data, and national treatment guidelines"

"When there is ongoing local circulation of seasonal influenza, empiric therapy with a neuraminidase inhibitor [anti-viral influenza drugs] should
be considered for the treatment for patients with influenza or at risk for severe disease."
The evidence based science shows that medical face masks for the healthy do not alter rates of community transmission of SARSCoV2 while they contribute to the plastic pollution of planet. Cloth & masks of other materials increase rates of infection through nebulization spread.

"Speaking through some masks dispersed largest droplets into a multitude of smaller droplets..smaller particles are airborne longer than large droplets (larger droplets sink faster), a mask might be counterproductive."
https://t.co/jBQlWRxcEL


Influenza like illness rates 3 times higher with cloth masks when compared to control group:
https://t.co/djT0mfutv9
Prof. Carl Heneghan, Oxford University: "The high quality trial evidence for cloth masks suggest they increase your rate of reinfection."


Please note, droplets smaller than 120 microns can't be measured. SARSCoV2 is 0.14 microns. This means that the nebulization effect of medical masks could not be measured, not that it does not happen. ⬇️


The really small aerosols <1 μm [the ones that pass through ALL surgical masks] can penetrate all the way to the alveoli - the basic units for gas exchange

More from Category c19

All you need to know about COVID19
FACTS NOT FEAR

Covid 19 is a disease caused by the SARS-CoV-2 virus. SARS-CoV-2 is one of 7 coronaviruses known to man. 1/n

The pandemic is real. Excess deaths were observed in many countries. Not all countries were affected in the same way due to pre-existing immunity, the health status of the population and demographics (the proportion of elderly in the population) 2/n
https://t.co/65elPq3gp5


COVID 19 presents a high risk for the very few and negligible risk for the many.

The infection fatality rate in different age groups:
<19 y, IFR= 0.003%
20-49 y: IFR= 0.02%
50-69 y: 0.5%
>70y, IFR=

Not everybody is susceptible to the virus. If reinfected, pre-existing immunity from related viruses gives protection from developing the disease or from developing serious symptoms.
4/n

“The evidence that a subset of people has a cross-reactive T cell repertoire through exposure to related coronaviruses is
@welt published an article today on the “panic paper”-scandal in Germany.

Title is "Maximum collaboration”, showing @BMI_Bund / Horst Seehofer had a secret paper drafted in the 1st COVID-19 wave that dramatically depicted the threat.

A scandal of gigantic proportions. Thread⬇️


2/: @welt released 2 versions: long version as print, short-edit, online.

This thread focuses on the long version. It's of crucial importance-people around the globe understand this earthshaking scandal. Share.

English:
https://t.co/qAbU6D8c0P

German: https://t.co/W2i1FtVrCg


3/: Mid-March 2020: Federal Minister of the Interior-Horst Seehofer (@BMI_Bund, @cducsubt) was on the edge: Christian Drosten (@c_drosten) & Lothar Wieler (@RKI) urgently warned: Germany was threatened w/ dramatic consequences if the country returned to everyday life too quickly.


4/: Horst Seehofer sent his Secretary of State Markus Kerber into the lane. The plan was to bring together leading scientists: they should produce a paper that would then serve as legitimation for further tough political measures, beyond Easter - now known as the “panic paper”.


5/: Markus Kerber launched a corresponding call to researchers via e-mail, 4 days later, the request was fulfilled: A classified paper, which presented the danger posed by the virus as dramatically as possible, and which quickly spread through the media.

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हिमालय पर्वत की एक बड़ी पवित्र गुफा थी।उस गुफा के निकट ही गंगा जी बहती थी।एक बार देवर्षि नारद विचरण करते हुए वहां आ पहुंचे।वह परम पवित्र गुफा नारद जी को अत्यंत सुहावनी लगी।वहां का मनोरम प्राकृतिक दृश्य,पर्वत,नदी और वन देख उनके हृदय में श्रीहरि विष्णु की भक्ति अत्यंत बलवती हो उठी।


और देवर्षि नारद वहीं बैठकर तपस्या में लीन हो गए।इन्द्र नारद की तपस्या से घबरा गए।उन्हें हमेशा की तरह अपना सिंहासन व स्वर्ग खोने का डर सताने लगा।इसलिए इन्द्र ने नारद की तपस्या भंग करने के लिए कामदेव को उनके पास भेज दिया।वहां पहुंच कामदेव ने अपनी माया से वसंतऋतु को उत्पन्न कर दिया।


पेड़ और पौधों पर रंग बिरंगे फूल खिल गए और कोयलें कूकने लगी,पक्षी चहकने लगे।शीतल,मंद,सुगंधित और सुहावनी हवा चलने लगी।रंभा आदि अप्सराएं नाचने लगीं ।किन्तु कामदेव की किसी भी माया का नारद पे कोई प्रभाव नहीं पड़ा।तब कामदेव को डर सताने लगा कि कहीं नारद क्रोध में आकर मुझे श्राप न देदें।

जैसे ही नारद ने अपनी आंखें खोली, उसी क्षण कामदेव ने उनसे क्षमा मांगी।नारद मुनि को तनिक भी क्रोध नहीं आया और उन्होने शीघ्र ही कामदेव को क्षमा कर दिया।कामदेव प्रसन्न होकर वहां से चले गए।कामदेव के चले जाने पर देवर्षि के मन में अहंकार आ गया कि मैने कामदेव को हरा दिया।

नारद फिर कैलाश जा पहुंचे और शिवजी को अपनी विजयगाथा सुनाई।शिव समझ गए कि नारद अहंकारी हो गए हैं और अगर ये बात विष्णु जी जान गए तो नारद के लिए अच्छा नहीं होगा।ये सोचकर शिवजी ने नारद को भगवन विष्णु को ये बात बताने के लीए मना किया। परंतु नारद जी को ये बात उचित नहीं लगी।