UK variant update:

50% more contagious and the main difference is in the rate of infection in children up to the age of 9.

No significant difference found yet in clinical course, mortality within 28 days or chance of re-infection.

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https://t.co/D8DXVvBeew

50% higher infection rate

(Secondary attack rate 15.1% versus 9.8%)

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Main effect in children under 9 years old

(see age distributions, second image has overlay of reference onto UK variant)

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Essential to stop the UK variant: 50% higher transmission will lead to more cases, more hospitalizations, more ICU cases, more deaths, and greater economic costs.
Independent SAGE's plan for the UK variant

With the new Covid variant everywhere, it's not enough to just wait for the vaccine | Stephen Reicher

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https://t.co/cF1HPC3U2l
1)Accelerate vaccinations
2)Control: a) Advance application for travel to and from the UK, a negative PCR test prior to travel, managed isolation on arrival b) Schools should remain closed until buildings are made as safe as possible for pupils and staff
c)Universities online

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3) test,trace,isolate: a)Test, b)Trace contacts as quickly as possible, isolate before they can infect others. Include forward tracing (identifying who you might have infected) and backwards tracing (who infected you), c)Practical support to isolate

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4) Provide guidance for workplace safety.
5) Provide financial support for the public.

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Compare
👉higher fatality, with
👉increase in transmissibility ON fatality.

Example:
50% higher fatality increases deaths from 129 to 193.
50% higher transmissibility increases from 129 to 978 after one month, more if longer

See:
https://t.co/MYiQUL804z

More from Health

You gotta think about this one carefully!

Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)

The test is 99% effective in detecting both sick and healthy people.

Your test comes back positive.

Are you really sick? Explain below 👇

The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through


You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.

👇


Here is what we know:

- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative

Assuming 1 million people take the test (including you):

- 100 of them are sick
- 999,900 of them are healthy

👇

Let's now test both groups, starting with the 100 people sick:

▫️ 99 of them will be diagnosed (correctly) as sick (99%)

▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)

👇

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