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No. of persons with senile dementia at a given time
Pre v a l e nc e = ———————————————————————————
No. in study population at risk for senile dementia
175
= ―――― = 0.10 = 10%
1,750
Optional aside – Assessing precision of an estimated prevalence.
Since prevalence is a proportion, a confidence interval can be obtained using the binomial
distribution or, where there are at least 5 cases, the normal approximation to the binomial
distribution. The variance of a point binomial random variable is pq (where p is the
probability of a “success” and q=1―p), so the standard error for the estimated probability is
√(pq/n). Thus, the 95% confidence interval for a prevalence estimate p is: p ± 1.96
√[p(1―p)/n]. For the preceding example, the 95% confidence limits are 0.10 ±
1.96√[(0.10)(0.90)/1750] = (0.086, 0.114). When there are fewer than 5 cases, an exact
procedure is required.
Prevalence has three components:
1. Existing cases
2. Population “at risk” to have the condition
3. Point (or sometimes a period) in time to which the prevalence applies
Incidence – the occurrence of new cases
New cases
Inc i de nc e = ——————————————
Population-at-risk over time
Incidence – a “motion picture” – describes what is happening in a population. Incidence is defined
as the number of new cases divided by the population at risk over time. Incidence therefore
includes three components:
1. New cases
2. Population at risk.
3. Interval of time.
Note that:
• Incidence involves the passage of time.
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www.epidemiolog.net, © Victor J. Schoenbach 5. Measuring disease and exposure - 92
rev. 10/15/2000, 1/28/2001, 8/6/2001