What if the false diagnosis rate was 90%?
Don’t misunderstand me. I’m a thorough believer in the existence of this virus.

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...

@DesmondSwayne Sir Desmond is right. SAGE makes mathematical predictions based on flawed models.
I chose to stick my neck out almost 4mo ago here:
https://t.co/b0rT5Lq9HI
I experienced much anxiety doing this, aware that, if I was badly wrong here, I would be destroyed as a contributor.

That said, I thought the immunology so clear that I made three, specific & testable predictions which should apply if I was right.
Please examine them, on the right, under the pie chart:

In particular, I predicted that the epidemic would not reignite in London. Obviously, we have many “cases” but I urge people to disregard these & instead to look at excess deaths, on the principle that a severe (occasionally lethal) respiratory virus would show itself this way.

Here is a chart showing the trend of deaths in London alone over recent years. A prominent peak of deaths is evident as the virus swept through in spring. Also visible the August heatwave. But there are no excess deaths now.
I submit this is a striking example of herd immunity.

I’m still waiting for SAGE or indeed anyone to provide an alternative explanation for the sharp nature of the spring excess deaths peak which doesn’t involve herd immunity or otherwise removing from the pool those vulnerable to lethal outcomes (same result). Given this sharp...

In a number of Sunday papers:
Scientific advisers said it was “hard to see” when the restrictions would end as new variants continued to emerge, delivering a potentially devastating blow to the travel industry. The prime minister said that after progress with vaccinations...

...”what we don’t want to see is all that work undone by the arrival of a new variant that is vaccine-busting”.
The idea is planted in people’s mind that this virus is mutating in such a way as to evade prior immunity. This is completely unfounded, certainly as regards immunity..

...gained naturally, after repelling the virus (which well around 99.9% of the population do, fewer, obviously in the very elderly & already ill, more in those younger & well). It’s important to appreciate that upon infection, the human immune system cuts up an infectious...

...agent into short pieces. Each of these short pieces of protein are presented to other cells in the immune system, like an identity parade. Our cells have a truly astonishing range of abilities to recognise different protein structures, and there will be some which recognise...

...each of the pieces of the invader. The cells which recognise a piece are instructed to multiply selectively so that, after a few days to a couple of weeks, our bodies contain large numbers of virus piece specific cells. These have a range of functions. Some make antibodies...

I know some people who seem (to me) more concerned with receiving VALIDATION for their mental health issues than solving them.

They seem to care most about other people BELIEVING their problems are real.

I'm curious about this.

Like, it's more important to them that people know how debilitating their anxiety is, than to overcome the anxiety.

Or it's important to them that others believe that they're actually depressed, not "just sad."

Or they want people buy into the narrative that they've been traumatized, and might be something like offended if someone minimizes that.

What do we make of this?

1. One possibility is that if solving the problems seems hopeless or even just really hard, you need external support to be able to cope.

If no one cuts you slack because of your mental health stuff, maybe you're in a really bad place, so you need people to believe you.

So many people don’t realize that they have OCD because actual obsessive compulsive disorder is rarely talked about openly. So here are the basics: 🧵(thread)

I think that a lot of people forget that OCD is a mental illness, emphasis on the MENTAL. When it’s portrayed on TV, it’s always shown as a very behavioral disorder. And while it’s true that overt behavioral compulsions are part of OCD, they don’t begin to tell the whole story

OCD stands for obsessive compulsive disorder. That’s obsessive thoughts and compulsive behaviors. The OCD cycle is the cycle of obsessions that lead to compulsions that lead to more obsessions that lead to more compulsions etc etc etc.

People with OCD experience intrusive thoughts (which become obsessions.) Intrusive thoughts are unwanted and invasive, and they’re generally REALLY disturbing. It’s a common misconception that people with OCD are exclusively concerned with tidiness and cleanliness. This is false

TW/ OCD subtypes

Intrusive thoughts can be about anything, but there are a few common “subtypes” of obsessions. These include harm OCD, self harm OCD, sexual OCD, pedophelia OCD, relationship OCD, contamination OCD, religious OCD, moral OCD, health OCD and “just right”

8 superfoods that will 10x your body mass:

1. Red Meat

Red meat is an excellent source of protein that aids in weight gain and muscular development.

It has leucine and creatine, which are substances important for increasing muscle building.

Protein and fat found in steak and other red meats contribute to weight gain.

2. Starchy Foods

Potatoes, sweet potatoes, corn, whole grain bread, oatmeal, whole wheat pasta, and brown rice are high-carbohydrate foods.

Carbohydrates, which have a protein-sparing effect, are essential for muscle growth along with proteins.

3. Eggs

Eggs are a powerhouse of protein, zinc, vitamins A, D, B 12, phosphorus, and folate.

Egg protein has a high biological value, which makes it the ideal post-workout snack.

There are 90 calories, 6.7 grams of fat, and 6.1 grams of protein in one large scrambled egg.

4. Fatty Fish

Essential fatty acids and proteins are abundant in fatty fish like salmon.

They aid in weight gain and immune boosting.

The finest source of omega-3 which is important for weight gain is found in these fish.

"Public health" isn't just about vaccinations, clinics and urgent care: it's a holistic discipline that encompasses all the contributors to health outcomes, which include things like housing, employment, transportation, pollution and more.

1/

A new working paper from @nberpubs estimates the number of US covid deaths that could have been prevented with a coherent, effective eviction moratorium and a ban on utility cutoffs:

The paper, written by a multidisciplinary group of Duke researchers from medicine and economics, found that housing precarity (a risk of losing your home) drove risky behavior that increased the spread of the disease and the resulting deaths.

3/

For example, it forced people to double-up on lodgings, making social distancing impossible, to say nothing of self-isolating after an exposure. It also drove people to tolerate high-risk workplace conditions, including illegal conditions.

4/

The authors used regression techniques to control for confounding variables, and used like-for-like counties with different utility and eviction policies to estimate the effect that these had on infection rates.

5/