Updated Cochrane review assesses how accurate rapid #tests are for detecting #COVID-19 | EurekAlert! Science News
There are large differences in the accuracy of different brands of test, with very few meeting the World Health Organization (WHO) minimum acceptable performance standards.
The percentage of people with COVID-19 who were correctly identified varied between brands and also depended on whether manufacturers’ instructions for using the tests were followed. For people with symptoms of COVID-19, correct identification across test brands ranged from 34% (Coris Bioconcept assay), to 58% (Innova assay), and up to 88% (SD Biosensor STANDARD Q assay) of infected people. The WHO have established performance standards for tests that identify infection in people with symptoms. To meet these standards, a test must be able to correctly identify at least 80% of people with infection and correctly exclude infection in 97% of people who are not infected.
To illustrate their results the researchers looked at the effect of two of the better performing brands of test (Abbott Panbio and SD Biosensor STANDARD Q ) in people with symptoms (75% to 88% of COVID-19 cases correctly identified) and in people who did not have symptoms (49% to 69% of COVID-19 cases correctly identified).
In a population of 1000 people with symptoms where there are 50 people with COVID-19, we would expect that about 40 people would be correctly identified as having COVID-19 by rapid tests, and between 6 and 12 cases of COVID-19 would be missed. Between 5 and 9 positive test results would turn out to be false positives.
The true number of cases of COVID-19 is likely to be lower in mass testing of people without symptoms. In a population of 10,000 people with no symptoms, where 50 people really had COVID-19, between 24 and 35 people would be correctly identified as having COVID-19, and between 15 and 26 cases would be missed. We would expect the tests to return between 125 and 213 positive results and between 90 and 189 of those positive results would be false positives.