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Originally Posted by jfman

No-one has ever claimed masks to be 100% effective, or else it’d be a case of masking everyone up for six weeks and getting on with our lives.

Nobody has either challenged that there could be more to immunity than simply antibodies, and the notion of pre-existing immunity on some level in some populations has raised itself before.

https://www.theguardian.com/world/20...al-dark-matter

However, what you’ll find is that I scoffed at the frequently touted notion that somehow, by magic, the experience of other countries won’t be replicated here or that the January-March trend is generally the trend for unmitigated growth unless there is evidence we are at or near the herd immunity threshold.

I think as we are approaching lockdown two we can all accept as fact there’s clearly plenty of further opportunities for onward transmission of the virus within the population as a whole. We have accelerating, not decelerating growth that would be associated with reaching the threshold.

---------- Post added at 15:57 ---------- Previous post was at 15:56 ----------



I can’t see a graph I just have

START INTERNET EXPLORER 15:57

Rotate that at 90 degrees I realised I messed up the horizontal and vertical.

Less than distraction from T-cell pre-immunity which has been peer reviewed unlike a report in ther Groaniad.
For instance..

You need models that can allow for all possible states, and assess which ones matter for shaping the pandemic’s trajectory over time.

and

In my field, neurobiology, we call the approach dynamic causal modelling (DCM). We can’t see brain states directly, but we can infer them given brain imaging data. In fact, we have pushed that idea even further. We think the brain may be doing its own dynamic causal modelling, reducing its uncertainty about the causes of the data the senses feed to it. We call this the free energy principle. But whether you’re talking about a pandemic or a brain, the essential problem is the same – you’re trying to understand a complex system that changes over time. In that sense, I’m not doing anything new. The data is generated by Covid-19 patients rather than neurons, but otherwise it’s just another day at the office.

and

To date our predictions have been accurate to within a day or two, so there is a predictive validity to our models that the conventional ones lack.

Finally

For each duration we can calculate the probability that a second wave will emerge, and when. It’s early days for this work, and I look forward with genuine excitement to new data on immunity becoming available, now that reliable antibody tests exist.

Not one mention of a peer reviewed existance of T-Cell pre-immunity. If that is not included in the data model then the model will be flawed. Nor is false positive testing results mentioned which can scew the model data further. Not forgetting the article is from 4 mths ago and a lot has been learned since.