Incidence and prevalence are terms used in epidemiological research that have been used as interchangeable words in our general conversations. But they are not the same thing.

Incidence is defined as the number of
*new* cases of a condition over a given period of time (typically one year) in a percentage of the population. It may be expressed as either a number per 100,000 people (as is often the case in news reports) or as a percentage. For example, if every year in a practice of 1,000 people, you diagnose 15 of them with Meniere’s disease, the yearly incidence would be 1.5% (or, 1500 per 100,000).

Prevalence is the number of
*existing* cases of a condition at either a single point in time (point prevalence) or over a given period of time (period prevalence). For example, at the time of study 90 people in a practice of 1000 patients were suffering from Meniere’s disease (15 who were diagnosed this year and 75 who were diagnosed in past years). The prevalence here would be 9% (or 9,000 per 100,000).

It should be clear that with chronic diseases, such as diabetes mellitus, the incidence will be lower than the prevalence. Here, each new case adds to the large number of already existing cases. With a short-term illness, such as the common cold, the opposite will be true. Over the course of a year, maybe 50% of a population will have a cold, but at any given time (point prevalence), the number with a cold will be low, perhaps at 2%.

One final thought. It is important to note the relationship of incidence to the concept of
*risk*. Risk, such as is calculated in epidemiological cohort studies, looks to see how many new cases develop as new follow a group of people forward in time to see if exposure to some risk factor leads to the condition of interest. We start with a group of people, none of whom have the condition of interest. As we follow the patients, some will then develop that condition. Since they are all new cases, we can calculate true incidence rates in a population, and from that determine risk (the probability that an event will occur, which is calculated by dividing the number of events- new cases- by the number of people at risk- the population).