Carl Hennigan

So this is a problem.

People look at it and go, well, look, we've got data on 400,000 deaths.

We must know what we're doing.

What you end up is the problem of big data, precise estimates, but they're nowhere near the target.

It's a bit like I always explain.

It's like you're throwing darts at a dartboard and all the darts are really close together, but they're nowhere near the bullseye.

What John was describing is you want a really accurate estimate and then darts will just sit around the bullseye.

So, you know, when you get the answer, it's bound to be the truth.

There'll be a little bit of uncertainty.

And in doing this well in 10,000 people.

you would have been much better to be able to estimate if you take 10,000 people, this is how many people have the infection.

When they die, you ascertain whether they died from the disease or died with the disease.

How do we ascertain that, Carl?

Yeah, so, and I mean, the crude way you do it is at least you do it through death certification.

You can say, what was the primary cause of death?

What was the secondary cause of death?

And that's one way of doing it.

You can have a committee that looks at it.

But we do this in clinical trials all the time.

We say, was this adverse event, this serious unexpected adverse event caused by the drug, or was it happening anyhow?