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A couple of things people I think people have misunderstood about the school DCT study - lets clarify them!
First, test sensitivity of "only 53%"
Does this mean the test is rubbish?
Well actually, it's irrelevant!
1/
There is a BIG difference between a study of test performance, and real world test implementation
Good tests can be harmful in the real world, bad tests can end up being useful
For this study, we don't care about performance...
2/
This study measured secondary cases compared to quarantine - the outcome we actually care about is people getting infected
There is no noticeable difference here. It could be both are equally terrible! the important thing is there is not a big difference
3/
Next, concerns about the non-inferiority level are overblown, because they ignore that this is relative, not absolute
Rates of secondary cases were <2%. A 50% increase from e.g. 1.5 to 2.2% is negligible in real terms, and would be well worth not dismissing bubbles
4/
People draw attention to relative risks like this to obscure the true impact of the intervention
Besides, the result was well within this margin - the upper CI was 1.22, so a max 22% increase (e.g. 1.5% to 1.83%, or 2% to 2.44%) - tiny real increase
5/
This shouldn't be impacted by community transmission either, as this is rates per index case. More spread elsewhere will just mean more index cases.
There you have it - don't let statistical wizardry or misdirection pull the wool over your eyes!
6/
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A randomised trial of daily testing of school contacts of COVID-19 cases found it was just as good (or maybe better) at preventing transmission than sending kids home
Some seems to be some confusion on why it's better to coincide easing of restrictions with schools closing for summer
If schools are not drivers of community transmission, why does it matter?
Don't worry, it's quite simple! Let me explain...
1/
Firstly, closing schools does not just stop transmission in school
When schools are closed, adults have to stay home, change their plans etc to look after children
This appears to be a pretty major source of reduction in R associated with school closures in general
2/
For example, modelling frequently shows closing Primary schools to reduce R by a greater degree than closing Secondary schools, despite more transmission occurring in Secondary age children
This is likely because closing primary schools forces more parents to remain home
3/
It's important we are all cognisant of the impact of highly emotive and fear based messaging around #COVID19
It can create deep and lasting damage, and is often counter productive
This is especially the case when it comes to children
1/
It is great to use facts to and establish risk and to inform people (although for kids this is almost universally reassuring when used in the right context)
But to deliberately stoke fear and anger is not healthy, and will not end well
None of this is new to public health
2/
There is a long history here with HIV in particular
Potentially creating lasting fear and stigma around sexual relationships
Are we creating the same around social experiences? Around our children attending school?
The study uses PHE modelling data on infection rates, as case data over the year is unreliable (we tested only people who were admitted to hospital during the first wave)
Through this, they estimate just short of 500,000 infections
This is a massive underestimate
2/
We can get a better estimate of total infections by measuring seroprevalence - who has positive antibodies
By July last year, 4% of children were positive - that is already nearly 500,000 BEFORE the second wave
Many people believe children are more likely to have false negative results to:
- antibodies tests, due to them having mild illness
- PCR tests, due to difficulty sampling
Turns out, that's almost never the case
1/
First, antibody tests
Most serology tests used in studies test for antibodies against the Spike protein (we call these S IgG)
This nice Australian study, found no difference in rates of children seroconverting to S IgG compared to adults