It also means that a test that is highly sensitive and highly specific may be very useful for estimating what proportion of the population have had the disease, but may be less reliable at determining whether any particular individual has or has not already been infected. The upshot is that the reliability of the test is not just dependent on properties of the test itself – it depends on the prevalence of the disease in the population being tested. This is a difficult concept to get your head around, but it basically means that when antibody tests are used in a population where infection levels are low, the results cannot be taken at face value. If more people have the disease, people who test positive are more likely to have actually had it and therefore the PPV is higher. The PPV varies depending on how prevalent the disease is in the population. This percentage, called the ‘ positive predictive value’ or PPV, is the probability that people who receive a positive test result have actually had the disease. This means that only 70% of the 64 people who received a positive result would actually have antibodies against SARS-CoV-2. If the test is 90% sensitive, it would pick up 45 of these “true positives.” However, because the test is not 100% specific, it would also give a false positive result for 19 people who do not have antibodies – based on 2% of the 950 people who haven’t been infected. This means that in Spain, if 1,000 people were to be tested, 50 of those would be expected to be carrying COVID-19 antibodies. For example, a recent study in Spain suggested that 5% of the population have currently been exposed to SARS-CoV-2, the virus that causes COVID-19. If most people have not yet had the disease, as is currently thought to be the case in many parts of the world, this 2% could make up a large proportion of the people who receive a positive result. However, a specificity of 98% means that 2% of people who have not had the disease will also have a positive test result, a false positive. This sounds impressive, but what does this really means for individuals? For those with a positive screening test, what is the probability that they have actually had the disease? To answer this we need to look more closely at the numbers.Ī sensitivity of 90% means that 90% of people who have had the disease will receive a positive test result, while 10% of them will get a false negative result. According to a recent Cochrane review, current COVID-19 antibody tests are around 90% sensitive and 98% specific. Sensitivity, specificity and predictive valuesĪs with any good diagnostic test, COVID-19 antibody tests need to be highly sensitive, which means that most people who have had the disease get a positive result and highly specific, which means that most people who have not had the disease get a negative result. Fortunately, or unfortunately, it is a bit more complicated than that. Maybe you have received a positive test result and are now resting easy in the knowledge that you cannot get COVID-19 again. Maybe you are convinced that you have had COVID-19 but your antibody test result has come back negative. Widespread antibody testing has long been hailed as key to getting back to “normality,” by providing a way of determining who has already contracted COVID-19 and is potentially no longer at risk.
0 kommentar(er)
