COVID epidemiology explained: sensitivity and specificity

With the middle of October among us, the signs of the fall season are presenting themselves. Temperatures are dropping, leaves are falling, and we are in the final week of first module courses. Despite a very different academic year and college experience for 2020-2021, some things remain the same. For instance, it is time to make a trip back up to Williams Field House for another round of COVID tests. To avoid further health challenges in an already turbulent year, Obies are required to get a flu shot. Both are being offered at the field house throughout the month of October.

With everything that is being asked of our community for a safe reopening, it’s worthwhile to delve into the rationale behind public health decision-making. Doing so warrants dialogue that goes beyond the number of cases and deaths that you see on the news. Two epidemiological topics relate to testing and vaccination: sensitivity and specificity.

Sensitivity and specificity are measures that are critical for all diagnostic tests. Sensitivity measures how often a test correctly generates a positive result for the condition being tested. Specificity, on the other hand, measures a test’s ability to correctly generate a negative result for people who do not have the condition being tested. Every diagnostic test aims to get as close to perfection as possible with each of these measures.

Let’s put these measures into the context of COVID-19. A COVID test of high sensitivity accurately identifies positive cases where patients can be advised and treated appropriately. A positive result can require isolation, home treatment for asymptomatic individuals and those with mild or moderate symptoms, or possible hospitalization for more severe symptoms.

Unfortunately, no test is perfect, and there’s the possibility of a “false positive“—a test result that indicates a patient is positive even though they don’t actually have the condition. This also pertains to tests with high specificity. Here, a test correctly identifies negative cases, but the possibility of a false negative exists. This is when the test result is negative but the person actually has the condition. The concern here is that someone may falsely believe that they’re negative and will not quarantine or seek treatment. Accurately identifying cases and non-cases is critical to pandemic response. Poor test sensitivity and specificity can lead to unnecessary use of health care resources and increased infection spread.

Oberlin is using polymerase chain reaction (PCR) tests to gauge the presence of the virus that causes COVID-19. This test uses a nasal swab to detect genetic material of the virus. PCR tests have high specificity, which means they can return fewer false negatives than the other types of available testing.

We can have confidence in the data we see in our community regarding new cases, but that does not mean we can be complacent. The 2020-2021 academic year is more of a marathon than a sprint in navigating the pandemic. Consider the continued testing and ObieSafe guidelines to be a mile marker as we progress to a return to normalcy.