Critique of COVID-19 Modeling and Response

Most people who use mathematical models did not understand that this

is so limited in terms of its ability to tell us something.

They thought that that was hardcore science

and they need to take it for granted

that this is what it is and

it's certain, and that was very far from reality.

There was no understanding that this was just very tentative, very

sketchy, very speculative.

Not only they were taken for serious, which was ridiculous,

honestly, because a model is just a model.

It's not hard facts. It's not data.

But it's also that apparently nothing was learned,

even though they had been wrong several times again in the

past and just a few years before, actually.

Nobody apparently remembered that.

This is an infection that in the majority of people,

they get no symptoms or very minor symptoms.

They don't even ask about what do I have.

The number of people infected was much larger compared

to the number of documented cases.

That meant also that the risk of dying if you get infected

or similarly the risk of getting serious complications is

much lower compared to the original anticipation.

For example, the World Health Organization had

estimated a case

fatality rate of 3.4%.

Globally,

about 3.4% of reported

COVID-19 cases have died.

This means one out of 30 people who get infected dies, and that's

completely out of range compared to the reality that we

could see in these seroprevalence studies.

It was a very different picture compared to what the original

perception based on China would look like.

What happened to you then?

There was a very, very aggressive response,

mostly from media and social media and

influencers, some of them scientists who turned

themselves to

influencers.

As a scientist, I found myself immersed into a situation

that I was

totally unprepared. But it was all that wave

of heroizing and demonizing.

I think both of that was incorrect. It was just scientific work.

It was not more than that.

First

of

all, we looked at the model and

we didn't think it seemed very realistic.

So we didn't really believe in it from very early on.

According to that model, we should have had like almost 100,000

cases during the first

spring.

And after the first spring in Sweden, we had about 3,000 cases.

So that's

how wrong the model ended up. We didn't have a pandemic plan on national

level and

all the regions also had pandemic plans and those were followed.

We also

tried to find data on lockdowns and the possible effects of those.

And there's very little, if any, data on that.

It's also incredibly difficult to have a

lockdown on a modern open society, especially a

society in Sweden where we interact all the time and

it's completely necessary to keep our society running.

So the whole concept of trying to lockdown,

we never felt it was feasible. We saw so many problems with

lockdowns and as I said, very few benefits.

Can we take Sweden just like as a control group?

We could. And when you look at the whole pandemic,

like four years from the beginning in 2020 or late

2019,

Sweden did better than any other country.

While in other countries that took very serious measures,

including unfortunately the US,

we had much higher excess deaths. When you look up to

2024, Sweden is by far the best compared to any

other

country in the world.

One big difference with the swine flu time

is that at the time, the real experts

were taken for serious.

I was not the only one interviewing people like Tom

Jefferson, Carl Hennigan, Wolfgang

Wodark. They were all still considered

experts. And then when the COVID era started, started

stoning of scientists, especially those that were the real

experts. They became radioactive.

Nobody could even mention them. Nobody could interview

them.

As an epidemiologist, I could not change the tide of what

was happening.

I should have been able to change the tide.

Many other epidemiologists feel equally frustrated.

They feel that

as scientists, we knew that things were wrong.

We just couldn't change them. Other experts or quote-unquote experts

were very powerful, were lobbying, were connected to policy cycles.

And

even though they had no clue about epidemiology, they

were just running the show

along with media and influencers.

I do worry about how this whole thing was completely

derailed. And very little epidemiology, very little science

went into decision-making eventually.