The FDA Website officially explains,
“Remember that positive predictive value (PPV) varies with disease prevalence when interpreting results from diagnostic tests. PPV is the percent of positive test results that are true positives. As disease prevalence decreases, the percent of test results that are false positives increase. Health care providers should take the local prevalence into consideration when interpreting diagnostic test results.
- For example, a test with 98% specificity would have a PPV of just over 80% in a population with 10% prevalence, meaning 20 out of 100 positive results would be false positives.
- The same test would only have a PPV of approximately 30% in a population with 1% prevalence, meaning 70 out of 100 positive results would be false positives. This means that, in a population with 1% prevalence, only 30% of individuals with positive test results actually have the disease.
- At 0.1% prevalence, the PPV would only be 4%, meaning that 96 out of 100 positive results would be false positives.
The Merriam Webster Dictionary describes prevalence as “the percentage of a population that is affected with a particular disease at a given time”.
Prevalence = no. of cases / population size
a. Prevalence can be measured in an closed cohort or in an open population.
b. Prevalence in cross-sectional.
c. “Old” cases and “new” cases are counted in the numerator.
d. Can be measured at a particular point (point prevalence) or over a period (period prevalence).
In Canada as of November 22nd, 2020, we had:
in Canada as of November 22nd, 2020 (since we started tracking in March), we had UNDER 1%.
Even if you add up all of those percentages… we are only just over.
So, I think it might be safe to assume that at least 70% of the Rapid Tests have, in fact, been False Positives based on our Prevalence.