What Is the Prevalent Incidence That I Will Understand Biostatistics?

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Podcast: What Is the Prevalent Incidence That I Will Understand Biostatistics?
Length: 3 min 39 seconds
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Incidence is a rate, and as such, it measures risk. We calculate it by taking as the number of new cases of disease and dividing it by the population at risk over a given period of time. Incidence answers the question, “how fast?”

Prevalence is a ratio and measures burden. We divide the total number of individuals with the disease by the total population at a specific point in time. Prevalence answers the question “How much?”

From the standpoint of small animal veterinary medicine, we do not have the denominators. Without the resources, small animal medicine often fails to capture the figures of total population and the defined population at risk. And without denominators, true prevalence and incidence values remain elusive specters. Like ghosts in our peripheral vision, we recognize the presence of threat but struggle to properly quantify it. The numbers rematerialize with livestock and then vanish again into the mists of speculation with many wildlife scenarios.

The bathtub analogy provides clarity to the relationship between these two terms. The water in the tub describes the current number of cases and represents the prevalence. New cases pouring into the bathtub would be incidence. The water leaving the tub via the drain represents either patients that were cured or cases that died.

Like a jigsaw puzzle, incidence and prevalence represent tiles that help fit in with those of the disease process, available diagnostics, treatments, and preventions in place. With a more complete picture, we then interpret the numbers and learn that a dramatic rise in a number doesn’t always indicate a problem. For example, imagine that the advent of a new diagnostic test allows for much earlier diagnosis of a disease. As doctors begin using the test, they start diagnosing many more patients with this disease and consequentially, both the incidence and prevalence rise.

In another example, think of a deadly chronic disease where a new treatment comes along. The incidence may not change, but the prevalence will dramatically rise from the increased survival times of the patients.

Neils Bohr said, “Clarity through breadth.” When looking at actual prevalence and incidence data, we must take the entire picture into view. In biostatistics, these two values form a background from which we can define other values such as positive predictive value, attack rate, and relative risk. Collectively, these direct medicine and even our individual actions towards a safer existence.

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