1/ Happy to announce that we have submitted our #paper ‘Bayes Lines Tool (BLT) - A SQL-script for analyzing diagnostic test results with an application to SARS-CoV-2-testing’.

In this ⬇️thread⬇️, I will explain why our tool is that powerful for decision makers. #UnbiasedScience

2/ In the meantime, the submitted paper is available on the preprint platform @zenodo_org. Factual criticism is highly desired and encouraged. The publication itself presents a seminal Bayesian calculator, the Bayes Lines Tool (BLT). (Petje af, @waukema!) https://t.co/FEYvH3D0Gf
3/ The Bayes Line Tool (available on https://t.co/jIomSIxOd9) is able to back-solve disease #prevalence, test #sensitivity, test #specificity, and therefore, true positive, false positive, true negative and false negative numbers from official governmental test outcome reports.
4/ This is done by creating confusion matrices with four variables. Namely: TP, FP, TN, FN. In order to calculate the matrices, we need prevalence, specificity, and sensitivity as well as the number of people that got tested (within a given period) and the number of positives.
5/ The number of positives and the number of tests are given by the government. Prevalence, specificity, and sensitivity are unknown. So we assume any combination of them ranging from 0-99%. These three combinations can amount up to #millions of #combinations.
6/ Typically, we calculate with 7 million combinations. Of these 7 million combinations, only 1-100 usually match the numbers that the government gave us (e.g. TRUE Positives + FALSE Positives = amount of performed tests).
7/ For the 11 Jan 2021, 536,947 tests were performed, resulting in 56,733 reported positives. The confusion matrices contained 21 possible matches for that day, represented in the #columns. We have sorted the columns by ‘prevalence’, as marked in red.
8/ The prevalence in the UK is currently presumed to be 1,52% (https://t.co/DuF3YXRA9s). Given the fact that reported positives dropped by 43% since January 8, we are looking at a prevalence of around 3%, but definitely lower than 12%, leaving us with the following options:
9/ Looking at the bars will already give you a good #indication on the test result in the context of everyone else who got tested in the population. This means that the model tells us whether the test results are/were #relevant.
10/ In the next steps, I will show you how to figure out which event might most likely have been the one that occurred that day, figuring out the real TP/FP rate, test specificity and sensitivity and prevalence. For this, let’s take a look at the tests' sensitivity.
11/ In the UK antigen and PCR tests are used. Antigen tests have a sensitivity between .664 (66.4%) and .738 (73.8%) (https://t.co/9ySnEL8c0l). PCR tests about .842 (84.2%) (https://t.co/guYiZUwW87). PCR tests constitute the majority of tests that are used in the UK.
12/ We are consequently looking for a sensitivity value just below .842. #BINGO! By just getting the amount of performed tests and number of reported positives from the government, we can conclude the actual specificity, sensitivity, and prevalence.
13/ So on January 11th, the prevalence was most likely about 4%, the tests’ sensitivity about 80.5%, and the tests’ specificity about 92.5% (which is much lower than the claimed 98.9%: https://t.co/Pc4YxhiX07). The false-positive rate that day would consequently have been 68%!
14/ Let’s have a look at the calculated data that the Netherlands are providing.
15/ AFAIK, the #Dutch government did not make a recent comment about prevalence, but we can assume a similar one as in the UK. Also, the sensitivity should be in the range of 75-85%, leaving us with the following possible scenarios. Remark: note the low #specificities < 90%.
16/ The model’s outcomes are extremely valuable in that they can provide a decision-making tool for people in charge (i.e. #politicians, #physicians, #policymakers etc.) and support them in evaluating their strategy for fighting the disease. #COVID
17/ This time-series can be further back-solved by solving single events following the #exclusionprinciple and consequently receiving insights with respect to the tests’ specificity/sensitivity or the prevalence within the population.
18/ This method provides the light (i.e. better insights) for individuals, authorities and governmental agencies that are currently in the dark with measuring problems and often using imprecise prediction models.
19/ Furthermore, the outcomes can provide a better insight into the expectable operational effectiveness of the tests (specificity/sensitivity) compared to the theoretical commercial claims of the manufacturers (equipment, primers, probes, supplies etc.).

More from Dr. Simon ツ

1/: The inventor of the corona PCR-Test @c_drosten is one of the #protagonists of the current crisis. He is known for involving himself in contradictions. In 2014, he gave a legendary #interview to @wiwo (https://t.co/jzTRh5Suhc) that I will address in this ⬇️short thread⬇️.


2/: The interview is significant because @c_drosten made totally sane statements back then that follow the principle of common sense. Considering his involvement in the "genesis of the current pandemic", his assertions appear in an entirely different


3/: In 2014, for instance, washing the hands was sufficient against being infected by coronaviruses. Several years he demands measures that destroy national economies and social life worldwide.


4/: Young @c_drosten also severely criticized the fact that Saudi Arabia used the PCR method to detect potential infections. From his point of view, that specific method could lead to many irrelevant cases. Nowadays, his view shifted his opinion towards 'collective punishment'.


5/: Whereas he demands "testing, testing, testing" nowadays and spreads panic and fear via (social) media, he heavily condemned that behaviour of Saudi media in 2014. On top of that, he expressed his concern that medial panic could increase the number of lab tests significantly.
Substantial analysis of @BenMarten regarding the mortality in Germany. Particularly noticeable is the "excess mortality" in December. Ben states that "lockdown deaths" could play an important role here. I would like to elaborate my thoughts on that. ⬇️Mini-Thread⬇️


Factor 1: Vitamin D deficiency.

Many people (especially elderly) have been locked in during the summer. Also the majority of holiday trips have been cancelled, leading to a lower 25(OH)D blood serum level as usual. The body can store vitamin D up to several months.


As vitamin D is a hormon that modulates the immune responses, we can assume that the lockdown measures had some adverse effect on our immune system. Especially elderly people in retirement homes must have been severely affected.

Factor 2: Loneliness

"Loneliness, it seems, can lead to long-term "fight-or-flight" stress signaling, which negatively affects immune system functioning. Simply put, people who feel lonely have less immunity and more inflammation than people who

Factor 3: Hyper Hygiene

Constant disinfections and high hygienic standards weaken the immune system. It gets literally "out of
1/: Avicenna was a Persian scientist, who lived 1000 years ago. He put two lambs in separate cages, which had the same health conditions. But only one lamb could see a wolf that was put in a third cage. The observations were astounding. (h/t @farmer_student) ⬇️a thread⬇️


2/: Both lambs were provided with the same feed. Also, the weight was exactly the same when the experiment started. Several months later, the lamb with sight on the wolf became cranky, restless, weak, and showed a significant weight loss and signs of poor development.

3/: The lamb that was under chronic stress as it was placed in a situation of constant apparent danger died eventually. 🐑🪦 In fact, the wolf did not pose a danger at all, but this was beyond the lamb's perception.

4/: This experiment showed that increased levels of the stress hormone cortisol have a bad impact on the metabolism of mammals. And 1000 years after this experiment, we are facing a similar situation again but with the difference that we are aware of the impact of stress.

5/: Currently, we are overwhelmed with medial and governmental propaganda with respect to a common cold virus (that might hypothetically be more lethal though) that doesn't do harm to the majority of the people. Extreme global measures are taken.

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Trump is gonna let the Mueller investigation end all on it's own. It's obvious. All the hysteria of the past 2 weeks about his supposed impending firing of Mueller was a distraction. He was never going to fire Mueller and he's not going to


Mueller's officially end his investigation all on his own and he's gonna say he found no evidence of Trump campaign/Russian collusion during the 2016 election.

Democrats & DNC Media are going to LITERALLY have nothing coherent to say in response to that.

Mueller's team was 100% partisan.

That's why it's brilliant. NOBODY will be able to claim this team of partisan Democrats didn't go the EXTRA 20 MILES looking for ANY evidence they could find of Trump campaign/Russian collusion during the 2016 election

They looked high.

They looked low.

They looked underneath every rock, behind every tree, into every bush.

And they found...NOTHING.

Those saying Mueller will file obstruction charges against Trump: laughable.

What documents did Trump tell the Mueller team it couldn't have? What witnesses were withheld and never interviewed?

THERE WEREN'T ANY.

Mueller got full 100% cooperation as the record will show.