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Prevalence in Statistics & Incidence: Simple Definition

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Statistics Definitions > Prevalence in statistics

Prevalence is the number of disease cases in a population; incidence is number of new cases that develop.

  1. What is Incidence in statistics?
  2. What is Prevalence in statistics?

1. Incidence Definition

Incidence is the number of newly diagnosed cases of disease at a specified time. For example, let’s say over the last year, five new cases of Ebola emerge from a village population of 200 (where all people in the group were free of Ebola symptoms prior to this date). Then the incidence for this population is 0.025 (2,500 per 100,000 women-years of study).

Knowing the incidence of a disease in a population is extremely useful in health statistics, as it gives you any person’s probability of getting diagnosed with a disease during a certain period of time.

2. What is Prevalence in statistics?

Prevalence in statistics is defined as the proportion of a population which has a particular characteristic during a specified time period. It is often reported as a percentage, or as the number of cases per 10,000 / 100,000.

For example, if 7 percent of people in Anchorage, Alaska had the flu on July 1, 2018 the prevalence of people in Anchorage with the flu, on July 1 2018, would be 7 percent.

prevalence in statistics

Prevalence of any oral HPV among adults aged 18–69, by race and Hispanic origin and sex: United States, 2011–2014.

The above image shows the time period (2011–2014) along with the percentages (y-axis) of oral HPV among adults aged 18–69. In order to come up with this estimate, the researchers would have used sampling.


New York State Department of Health (1999). Basic Statistics: About Incidence, Prevalence, Morbidity, and Mortality – Statistics Teaching Tools. Retrieved July 9, 2019 from:
Saracci, R. (2010). Epidemiology: A Very Short Introduction 1st Edition. Oxford University Press.

Stephanie Glen. "Prevalence in Statistics & Incidence: Simple Definition" From Elementary Statistics for the rest of us!

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