Moonshot plans uses point of care tests (POCT) approved for home use which don’t yet exist.

Proposals use computer modelling not empirical evidence. Understanding model assumptions is critical.

Widely claimed model is based on using LESS ACCURATE TESTS. This is WRONG.

2/10
The model assumes new POCT is positive in people who have INFECTIOUS Covid-19

and negative in both those who don’t have COVID-19 infection at all

and negative in those who have NON-INFECTIOUS Covid-19.

(infectious means you can pass the virus to somebody else).

3/10
So the Moonshot POCT tests need to be very sensitive for INFECTIOUS Covid-19

but don't need to be sensitive for Covid-19 INFECTION.

So they still need to be very accurate tests, but for a different target condition. It’s a subtle but really important point.

4/10
And it is definitely not an opportunity for any duff test with lower sensitivity to enter the market.

But many seem to be taking the opportunity to try.

5/10
It is easy to make this test in a computer model, but real life is much harder.

We don't have hard and fast ways of knowing whether somebody is infectious or not. Our only tool is viral culture, which is hard to run and has high failure rates - so no reference standard.

6/10
PCR cycle threshold (Ct) value is a proxy measure of viral load known to correlate with viral culture. But as culture is unreliable & Ct values vary between runs, machines and labs, we can't set a safe threshold for Ct to distinguish between infectious and non-infectious.

7/10
So we don’t have the POCT tests we need for Moonshot,

and even if we did,

we don’t have an way to validate that they reliably identify all cases that are infectious.

If they miss infectious cases they will allow the virus to continue to spread.

8/10
Initially people just exposed and infected have low viral loads. PCR can pick them up before they are infectious and appropriately isolate.

Moonshot POCT test will pick them up only when they are infectious. Tests must be used frequently to minimise numbers they infect.

9/10
Specificity? No harms were considered in the model.

With specificity>99% ten million tests a day generates thousands of false positive results, causing unnecessary legally enforced isolation of cases and contacts with consequences for economy and for civil liberties.

10/10
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