Earlier this month Matt Hancock, the Health Secretary, insisted Operation Moonshot was still going ahead and aimed to provide huge numbers of tests which could deliver a result in as little as 20 minutes.

However, Prof Deeks said: “The test detects trace amounts of viral genome sequence, which may be either live transmissible virus or irrelevant RNA fragments from previous infection.

“A positive result in someone without symptoms or known recent exposure may be from live or dead virus, and so does not determine whether the person is infectious and able to transmit the virus to others.

“Real concern exists that many people who are not infectious (and not likely to become infectious) will receive positive test results, and together with their contacts, will be forced to isolate unnecessarily. In the context of mass surveillance, this could be a majority of those who test positive.”

The false positive rate of coronavirus tests is currently very low – less than 1 per cent. But even at 0.8 per cent, as suggested by Prof Deeks it would mean huge numbers would test positive without having the virus.

Prof Deeks added: “Even with a specificity of 99 per cent, proposals to do 10 million tests a day will generate many thousands of false positive results, causing unnecessary but legally enforced isolation of both cases and contacts with potentially damaging consequences for the UK economy and for civil liberties.”

The RSS is calling for stronger statistical standards in testing programmes, warning that, unlike medicine, the accuracy and performance of tests are not held to a common standard. 

Professor Deborah Ashby, RSS President and co-chair of the working group, said: “The Covid-19 pandemic has shone a light on gaps in knowledge regarding diagnostic testing and the lack of quality assurance, which is so crucial for controlling the disease. 

“It is essential for public confidence that there is transparency around the evidence base which informs these important policy decisions. 

“As statisticians, we want to help decision-makers by setting out clear statistical criteria that should be used to assure the effectiveness of diagnostic tests.”

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