This is the exact problem with our government's thinking & response- despite this strategy of 'tolerating deaths' and half-way measures having spectacularly failed, it's quite amazing that our govt still hasn't learned anything, & continues to promote a policy of death. Thread
U.K. needs to confront
— Esther McVey (@EstherMcVey1) January 2, 2021
\u2018The challenge that faces us is to decide - are we going to try to pursue the elimination of Covid-19 regardless of the costs or decide on a tolerable level of deaths (like we do with the flu) in order to return to a normal life?\u2019
https://t.co/9hWbHIPJUq
https://t.co/VPqJBbkFik
The govt has completely failed us & their continued pursuit of pseudoscience will cost many more lives.
More from Deepti Gurdasani
Thread on the recent report on the possible risk of increased death associated with the new UK variant (B117)- with a discussion of the evidence around this, and what this means.
First, there is strong evidence to support increased transmissibility of B117 - current estimates of increased transmissibility range between 30-70% - from epidemiological evidence examining the differential rate of growth of B117 with respect to other variants & increase in R
There is also evidence from PHE contact studies that the risk of transmission from those carrying the B117 variant is ~50% greater than with other non-B117 variants.
Increased transmissibility, even if a variant has the same fatality rate can increase deaths substantially, because the rate of growth of cases is higher- & more cases means more deaths.
Increased fatality rates also increase deaths- but do so
So how was risk of death with the variant studied?
We don't routinely sequence all samples for the virus. We've found that the variant has a particular deletion which means that some PCR tests on samples with the variant give a different read-out when the variant is present.
First, there is strong evidence to support increased transmissibility of B117 - current estimates of increased transmissibility range between 30-70% - from epidemiological evidence examining the differential rate of growth of B117 with respect to other variants & increase in R
There is also evidence from PHE contact studies that the risk of transmission from those carrying the B117 variant is ~50% greater than with other non-B117 variants.
Increased transmissibility, even if a variant has the same fatality rate can increase deaths substantially, because the rate of growth of cases is higher- & more cases means more deaths.
Increased fatality rates also increase deaths- but do so
How dangerous are the B.1.1.7 and 501Y.V2 hyper-transmissible strains?
— Eric Topol (@EricTopol) January 11, 2021
by @AdamJKucharski @CFR_orghttps://t.co/aycWMN3b5h
h/t @Karl_Lauterbach pic.twitter.com/JlaFzzP06t
So how was risk of death with the variant studied?
We don't routinely sequence all samples for the virus. We've found that the variant has a particular deletion which means that some PCR tests on samples with the variant give a different read-out when the variant is present.
Brief thread to debunk the repeated claims we hear about transmission not happening 'within school walls', infection in school children being 'a reflection of infection from the community', and 'primary school children less likely to get infected and contribute to transmission'.
I've heard a lot of scientists claim these three - including most recently the chief advisor to the CDC, where the claim that most transmission doesn't happen within the walls of schools. There is strong evidence to rebut this claim. Let's look at
Let's look at the trends of infection in different age groups in England first- as reported by the ONS. Being a random survey of infection in the community, this doesn't suffer from the biases of symptom-based testing, particularly important in children who are often asymptomatic
A few things to note:
1. The infection rates among primary & secondary school children closely follow school openings, closures & levels of attendance. E.g. We see a dip in infections following Oct half-term, followed by a rise after school reopening.
We see steep drops in both primary & secondary school groups after end of term (18th December), but these drops plateau out in primary school children, where attendance has been >20% after re-opening in January (by contrast with 2ndary schools where this is ~5%).
I've heard a lot of scientists claim these three - including most recently the chief advisor to the CDC, where the claim that most transmission doesn't happen within the walls of schools. There is strong evidence to rebut this claim. Let's look at
The science shows us that most disease transmission does not happen in the walls of the school, but it comes in from the community. So, CDC is advocating to get our K-5 students back in school at least in a hybrid mode with universal mask wearing and 6 ft of distancing. https://t.co/dfvJ2nl2s4
— Rochelle Walensky, MD, MPH (@CDCDirector) February 14, 2021
Let's look at the trends of infection in different age groups in England first- as reported by the ONS. Being a random survey of infection in the community, this doesn't suffer from the biases of symptom-based testing, particularly important in children who are often asymptomatic
A few things to note:
1. The infection rates among primary & secondary school children closely follow school openings, closures & levels of attendance. E.g. We see a dip in infections following Oct half-term, followed by a rise after school reopening.
We see steep drops in both primary & secondary school groups after end of term (18th December), but these drops plateau out in primary school children, where attendance has been >20% after re-opening in January (by contrast with 2ndary schools where this is ~5%).
We've been falsely told 'schools are safe', 'don't drive community transmission', & teachers don't have a higher risk of infection repeatedly by govt & their advisors- to justify some of the most negligent policies in history. 🧵
data shows *both* primary & secondary school teachers are at double the risk of confirmed infection relative to comparable positivity in the general population. ONS household infection data also clearly show that children are important sources of transmission.
Yet, in the parliamentary select meeting today, witnesses like Jenny Harries repeated the same claims- that have been debunked by the ONS data, and the data released by the @educationgovuk today. How many lives have been lost to these lies? How many more people have long COVID?
has repeatedly pointed out errors & gaps in the ONS reporting of evidence around risk of infection among teachers- and it's taken *months* to get clarity on this. The released data are a result of months of campaigning by her, the @NEU and others.
Rather than being transparent about the risk of transmission in school settings & mitigating this, the govt (& many of its advisors) has engaged in dismissing & denying evidence that's been clear for a while. Evidence from the govt's own surveys. And global evidence.
Why?
Questions have to be asked about the evidence Jenny Harries gave to the Education Committee today about the risk to teachers.
— Adam Hamdy (@adamhamdy) January 19, 2021
Was she aware of this data?
If not, why wasn\u2019t she properly briefed?#COVID19 #schools https://t.co/4wa1PyAJld pic.twitter.com/eqFjaA1zYC
data shows *both* primary & secondary school teachers are at double the risk of confirmed infection relative to comparable positivity in the general population. ONS household infection data also clearly show that children are important sources of transmission.
Yet, in the parliamentary select meeting today, witnesses like Jenny Harries repeated the same claims- that have been debunked by the ONS data, and the data released by the @educationgovuk today. How many lives have been lost to these lies? How many more people have long COVID?
has repeatedly pointed out errors & gaps in the ONS reporting of evidence around risk of infection among teachers- and it's taken *months* to get clarity on this. The released data are a result of months of campaigning by her, the @NEU and others.
Rather than being transparent about the risk of transmission in school settings & mitigating this, the govt (& many of its advisors) has engaged in dismissing & denying evidence that's been clear for a while. Evidence from the govt's own surveys. And global evidence.
Why?
More from Government
'Peaceful transition to Military Power....'
Cannon
44
....heard around the world
NG - High Alert https://t.co/lfeSiUCCRB
We Will Never Forget
44
Stage is set
https://t.co/h6G3LCevII
Following the 44 trail of breadrumbs
https://t.co/PcX0uKUEUW
Cannon
44
....heard around the world
NG - High Alert https://t.co/lfeSiUCCRB
\U0001f4a5 BOOM \U0001f4a5
— R\u0113d.P\u012bll.Ph\u0101rm\u0101c\u012bst (@Red_Pill_Pharma) January 18, 2021
30 secs in - what do I hear?
\u2018Peaceful transition to military power\u2019
\U0001f1fa\U0001f1f8 MILITARY IS THE ONLY WAY \U0001f1fa\U0001f1f8 pic.twitter.com/9NPMT7N7Qy
We Will Never Forget
44
Stage is set
https://t.co/h6G3LCevII
The stage is set. Staged.
— JeLove (@LovesTheLight) November 7, 2020
Where? (the) Delaware.
10:44
Purple
First graphic in 98https://t.co/PKHlxp0rzS pic.twitter.com/XCx6pVQTHx
Following the 44 trail of breadrumbs
https://t.co/PcX0uKUEUW
Boom, Boom, Boom pic.twitter.com/ZcZXAgL0Qf
— JeLove (@LovesTheLight) August 13, 2020
Which metric is a better predictor of the severity of the fall surge in US states?
1) Margin of Democrat victory in Nov 2020 election
or
2) % infected through Sep 1, 2020
Can you guess which plot is which?
The left plot is based on the % infected through Sep 1, 2020. You can see that there is very little correlation with the % infected since Sep 1.
However, there is a *strong* correlation when using the margin of Biden's victory (right).
Infections % from https://t.co/WcXlfxv3Ah.
This is the strongest single variable I've seen in being able to explain the severity of this most recent wave in each state.
Not past infections / existing immunity, population density, racial makeup, latitude / weather / humidity, etc.
But political lean.
One can argue that states that lean Democrat are more likely to implement restrictions/mandates.
This is valid, so we test this by using the Government Stringency Index made by @UniofOxford.
We also see a correlation, but it's weaker (R^2=0.36 vs 0.50).
https://t.co/BxBBKwW6ta
To avoid look-ahead bias/confounding variables, here is the same analysis but using 2016 margin of victory as the predictor. Similar results.
This basically says that 2016 election results is a better predictor of the severity of the fall wave than intervention levels in 2020!
1) Margin of Democrat victory in Nov 2020 election
or
2) % infected through Sep 1, 2020
Can you guess which plot is which?
The left plot is based on the % infected through Sep 1, 2020. You can see that there is very little correlation with the % infected since Sep 1.
However, there is a *strong* correlation when using the margin of Biden's victory (right).
Infections % from https://t.co/WcXlfxv3Ah.
This is the strongest single variable I've seen in being able to explain the severity of this most recent wave in each state.
Not past infections / existing immunity, population density, racial makeup, latitude / weather / humidity, etc.
But political lean.
One can argue that states that lean Democrat are more likely to implement restrictions/mandates.
This is valid, so we test this by using the Government Stringency Index made by @UniofOxford.
We also see a correlation, but it's weaker (R^2=0.36 vs 0.50).
https://t.co/BxBBKwW6ta
To avoid look-ahead bias/confounding variables, here is the same analysis but using 2016 margin of victory as the predictor. Similar results.
This basically says that 2016 election results is a better predictor of the severity of the fall wave than intervention levels in 2020!
