# HOW RELIABLE IS THE COVID TEST?

*YOU MAY FIND THIS HARD TO BELIEVE*

*Most people who test positive for Covid 19 do not have the disease.*

*Surely this can’t be true. *

*Unfortunately it is.*

__Let me explain:__

*The test being used for Covid 19 is a swab called PCR (Polymerase chain reaction).*

*It detects active Covid infections but can also be (falsely) positive in old infections, re-infections and other virus infections.*

* The false positive rate is 0.8%. (It is 99.2% accurate)*

*This seems impressive.*

*But there is a problem and it is a major one.*

*Whenever there is a disease with a low prevalence then false positives will always outnumber true positives.*

*This has been known for years and is called the False Positive Paradox.*

*The prevalence of Covid 19 is approximately 1 in a 500 or 0.2% at the moment (end of September 2020). *

*This is a low.*

**PLEASE NOTE: THE ORIGINAL BLOG WAS WRITTEN AT THE END OF SEPTEMBER 2020 WHEN THE PREVALENCE OF COVID WAS 1 IN 500 AND FALSE POSITIVES TESTS WERE FOUR TIMES COMMONER THAN TRUE POSITIVES. THIS HAS CHANGED AS THE PREVALENCE OF THE DISEASE HAS INCREASED.**

**BY DECEMBER 2020 THE PREVALENCE OF COVID WAS JUST UNDER ONE IN A HUNDRED, AND BY THAT TIME A POSITIVE TEST WAS MORE LIKELY TO BE A TRUE POSITIVE THAN A FALSE POSITIVE. **

**BY JANUARY 2021 THE PREVALENCE WAS 1 in 50 IN ENGLAND MAKING THE ACCURACY OF THE TEST MUCH BETTER WITH A POSITIVE TEST BEING THREE TIMES MORE LIKELY TO BE A TRUE POSITIVE RATHER THAN A FALSE POSITIVE.**

**This is because the false positive rate has stayed much the same but the true positive rate has increased ten-fold as many more people are affected by the virus which in turn means a positive test is now more likely to be a true one.**

__This is how it works out:__

*Testing 100,000 people in September would have found 200 people who tested positive had a genuine active Covid 19 infection.*

*But it would also find 800 people will had a false positive test. They would not have an active Covid infection but would be told they do.*

** **(See below for maths as the figures may surprise you).

**IN SEPTEMBER A POSITIVE TEST WOULD BE A A TRUE POSITIVE IN 200 CASES AND A FALSE POSITIVE IN 800 CASES.**

**BY DECEMBER A POSITIVE TEST WOULD BE A TRUE POSITIVE IN 1000 CASES AND A FALSE POSITIVE IN 792 CASES.**

** BY JANUARY 2021 A POSITIVE TEST WOULD BE A TRUE POSITIVE IN 2000 CASES AND A FALSE POSITIVE IN 784 CASES.**

*What this means is that if you tested positive for Covid in September then it was far more likely that you do not have a Covid infection than you did. As you can see this has now changed.*

*It also means that in autumn when viral infections naturally go up then figures for Covid will also falsely rise (due to other viruses increasing) causing unnecessary alarm.*

For the Moonshot testing the government has purchased large amounts of the AbC-19 test. The British Medical Journal has found the clinical sensitivity of this test varies between 84.7 and 92.5%. In other words its accuracy is very poor. The number of false positives will greatly outweigh true positives (far greater than the ratio of false to true positives noted above). In simple terms it is not fit for purpose.

__HERE’S THE MATHS (using September prevalence):__

TRUE POSITIVES = 100,000 X 0.002 (incidence of disease is 0.2%) = 200 cases

FALSE POSITIVES = 99,800 (the people without the disease) X 0.008 (that is because 0.8% have a false positive) = approximately 800 people

TRUE NEGATIVES = 99,800 X 0.992 (the 99.2% of people for whom the test is accurate) = 99000

FALSE NEGATIVES: 0