![]() ![]() A positive test means we can be pretty certain someone has COVID-19. Of these people, 80 actually have COVID-19. However, let’s say 100 people experiencing symptoms like Jane have a swab test. Based on her symptoms, the probability that Jane has COVID-19 will be high – perhaps 80%. Or is it?ĭoctors use their experience to recognise patterns in symptoms, risk factors, and signs to estimate the likelihood of infection before testing. However, after getting a swab test, the result comes back negative for COVID-19. She checks her temperature to see it’s 38.5☌. After noticing a loss of smell for a few days, she wakes up one night feeling shivery, with a dry cough. ![]() Jane works for the NHS as a receptionist in a GP surgery in London, in an area of high rates of coronavirus infection. This was described mathematically by Thomas Bayes and later explained by Siddhartha Mukherjee as the law that “a strong intuition is much more powerful than a weak test”. The meaning of a test result for an person depends not only on the accuracy of the test, but also on the estimated risk of disease before testing. We don’t know for sure how often these false negatives occur in the UK, but evidence from China suggests up to 30 out of every 100 people with coronavirus might test negative. Early on in the novel coronavirus outbreak, doctors started reporting cases of people who had coronavirus which had been missed by swab tests – also known as “false negatives”. ![]()
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