<P> Incidence proportion (also known as cumulative incidence) is the number of new cases within a specified time period divided by the size of the population initially at risk . For example, if a population initially contains 1,000 non-diseased persons and 28 develop a condition over two years of observation, the incidence proportion is 28 cases per 1,000 persons per two years, i.e. 2.8% per two years . </P> <P> The incidence rate is the number of new cases per population at risk in a given time period . When the denominator is the sum of the person - time of the at risk population, it is also known as the incidence density rate or person - time incidence rate . In the same example as above, the incidence rate is 14 cases per 1000 person - years, because the incidence proportion (28 per 1,000) is divided by the number of years (two). Using person - time rather than just time handles situations where the amount of observation time differs between people, or when the population at risk varies with time . Use of this measure implies the assumption that the incidence rate is constant over different periods of time, such that for an incidence rate of 14 per 1000 persons - years, 14 cases would be expected for 1000 persons observed for 1 year or 50 persons observed for 20 years . </P> <P> When this assumption is substantially violated, such as in describing survival after diagnosis of metastatic cancer, it may be more useful to present incidence data in a plot of cumulative incidence, over time, taking into account loss to follow - up, using a Kaplan - Meier Plot . </P> <P> Consider the following example . Say you are looking at a sample population of 225 people, and want to determine the incidence rate of developing HIV over a 10 - year period: </P>

How to calculate the incidence rate of a disease