If you are starting to feel like the coronavirus epidemic will never end, then you may be correct. A statistical quirk in testing means that Britain may never hit zero cases, even if the virus is wiped out entirely.
The reason lies in the large number of false positives that are almost certain to creep in once case numbers drop very low, yet testing remains very high.
Testing is never 100 per cent accurate, and scientists must factor in the false positive and negative rates when determining infection prevalence. The problem is, nobody knows what those rates are.
The best guess at present is that coronavirus tests pick up around 80-85 per cent of positive cases, and around 99.9 per cent of negative cases.
Antibody tests may be missing large numbers of people who contracted Covid-19 because they don’t work for people who had a mild infection, new research from Oxford University suggests.
A study of more than 9,000 healthcare workers suggested significant numbers of people were getting ‘negative’ test results, despite probably having had the virus.
No test gives a 100% accurate result; tests need to be evaluated to determine their sensitivity and specificity, ideally by comparison with a “gold standard.” The lack of such a clear-cut “gold-standard” for covid-19 testing makes evaluation of test accuracy challenging.
A systematic review of the accuracy of covid-19 tests reported false negative rates of between 2% and 29% (equating to sensitivity of 71-98%), based on negative RT-PCR tests which were positive on repeat testing. The use of repeat RT-PCR testing as gold standard is likely to underestimate the true rate of false negatives, as not all patients in the included studies received repeat testing and those with clinically diagnosed covid-19 were not considered as actually having covid-19.
Further evidence and independent validation of covid-19 tests are needed. As current studies show marked variation and are likely to overestimate sensitivity, we will use the lower end of current estimates from systematic reviews, with the approximate numbers of 70% for sensitivity and 95% for specificity for illustrative purposes.
However, new research from Johns Hopkins University (MD, USA) has found that the chance of these tests giving a false negative – stating no infection when the individual actually is infected – is greater than 1 in 5, at times being far higher. The study, which analyzed seven previously published studies that evaluated RT-PCR performance, calls into question the accuracy of the predictive value of such tests.Biotechniques, 29 May 2020