Ct values can be used to estimate epidemic dynamics UPDATE! Ct values are expected to change depending on whether the epidemic is growing or declining, and we harness this to estimate the epidemic trajectory. Lots of cool new analyses and methods!

Some 1300 years ago in Karnataka there lived a genius who wrote "Gaṇitasārasan̄graha" (which is earliest text devoted entirely to mathematics)

The man who's work later borrowed by Arabs & Europeans

Thread on "Mahāvīracharya" astounding but forgotten legacy

Mahāvirachārya was patronised by rashtrakuta king amoghavarasha

His book"Gaṇita-sāra-saṅgraha"is earliest text devoted entirely to Mathematics

He has described the currently used method of calculating(LCM)of given numbers.The same method was used in Europe later in1500CE

Mahavira wrote "Gaṇita-sāra-saṅgraha" (GSS) in 8th century CE which contains some 1100 slokās & contains elementary topics in arithmetic , algebra , geometry , measurements , logic , number theory , dynamical systems etc

A sheer mathematical genius

He was devout jain
His magnum opus "Ganit sara sangraha " start with a sloka bowing to the glory of the jinas

"संख्याज्ञानप्रदिपेन जैनेंद्रन महत्वेशा,
प्रकाशितम जगतसर्व येन तम प्रणमाम्यहम"

He also praised his predecessor aryabhata , brahmagupta & other greats in his works

The importance & popularity of "Gaṇita-sāra-saṅgraha"was so huge that it enjoyed statues of most important textbook of mathematics in South Indian for over 3 centuries

A large no of manuscript copies of
"Gaṇita-sāra-saṅgraha"whr discovered in Kerala shows it's popularity

When respected Scientists resign over the false narrative... Take notice... and thank them.

Google Translated Letter from

Prof. Dr. Thomas Aigner,
Department of Geosciences,
University of Tuebingen, Sigwartstrasse 10,
D-72076 Tuebingen Germany

Dear colleagues,
It was with the greatest astonishment, deepest concern, and indeed bewilderment, that I took note of the "7th ad hoc statement" from the National Academy of Sciences Leopoldina on December 8th, 2020.
In my opinion, this paper is not worthy of an honest, critical-

weighing science oriented towards the service and well-being of man. I do not have any medical expertise. However, as a scientist committed to nothing but the pure truth, I take the liberty of speaking up. I feel very alarmed by several points:

1. On November 27, 2020, a group of 22 internationally recognized experts presented the following report on the PCR test, the linchpin of the "pandemic", for the Eurosurveillance magazine:

"External peer review of the RTPCR test to detect SARS-CoV-2 reveals 10 major scientific flaws at the molecular and methodological level: consequences for false positive results". Quote: "This highly questions the scientific validity of the test".

https://t.co/xvP6tVlIaE
Quite a surprise. Ferguson isn’t qualified to comment on such things. He lacks understanding of basic biological concepts, partly explaining why his predictions are often so extreme.

That said, I’ll take him as an ally. It’s clear we’re already at herd immunity. How can I be sure? London had a huge peak of excess deaths in spring. The timing of peak deaths showed clearly that the pandemic was self-limiting. Recall much debate about whether the interval...

...between lockdown & peak deaths was long enough for lockdown to have been the cause of reducing deaths? The answer was “no”. But it was close & I can understand people thinking “well, it’s close, so perhaps it was lockdown that did it?”, thereby establishing a foundational...

...myth favoured by those who genuinely believe lockdown saves lives (it clearly doesn’t).
I’ll get to London & here immunity. But those wavering about the evidence about lockdown in spring really will benefit from cogitating on this graph.

In blue are the 30 trusts with the earliest date of peak deaths in spring. In red, the 30 with the latest peak deaths. For me, this is proof that national lockdown, which began Mar 23, played no role whatsoever in turning the pandemic. You’ll see some areas had peak daily...

1/

Get a cup of coffee.

In this thread, I'll help you understand the basics of Binomial Thinking.

The future is always uncertain. There are many different ways it can unfold -- some more likely than others. Binomial thinking helps us embrace this view.

2/

The S&P 500 index is at ~3768 today.

Suppose we want to predict where it will be 10 years from now.

Historically, we know that this index has returned ~10% per year.

If we simply extrapolate this, we get an estimate of ~9773 for the index 10 years from now:

3/

What we just did is called a "point estimate" -- a prediction about the future that's a single number (9773).

But of course, we know the future is uncertain. It's impossible to predict it so precisely.

So, there's a sense of *false precision* in point estimates like this.

4/

To emphasize the uncertainty inherent in such predictions, a better approach is to predict a *range* of values rather than a single number.

For example, we may say the index will return somewhere in the *range* of 8% to 12% (instead of a fixed 10%) per year.

5/

10 years from now, this implies an index value in the *range* [8135, 11703]: