Here's a group of 200 students. We'll test them all for Covid-19.
Before we do that, we need to know their pre-test risk of infection. On campus, 11% of the population has coronavirus. We'll use this as their baseline risk, for now.
Choose a different pre-test risk of infection. Use these presets, which are rough estimates, or enter your own.
Assume all 200 students have a mild cough
Assume all students have serious Covid-19 symptoms
Now, let's simulate a diagnostic test. On average, this test correctly identifies % of people who K are infected (sensitivity) and it correctly identifies % of people who T aren't infected (specificity).
Try a type of test currently in use:
PCR or molecular tests are the most accurate. In general, they’ll have a sensitivity around 97% and a specificity of 100%.
Rapid tests are generally less accurate than PCR tests. An antigen test might have a sensitivity of 70% and a specificity of 99.5%.
Rapid molecular tests have an average sensitivity of 95% and an average specificity of 99%.
people tested positive.
people tested negative.
Our test correctly identified C with Covid-19, but said K had the virus when they actually didn’t.
Our test correctly identified P without Covid-19 but F with the virus were incorrectly told they were uninfected.