Incidence and Prevalence

Question 1

Define prevalence

What are the different types?

Answer 1

A measure of how common a disease is as a proportion. 3 types:

• Point prevalence: the proportion of people with a specific condition at a given point in time
• Period prevalence: the proportion of people with a specific condition within a specified time interval
• Lifetime prevalence: the proportion of people who will develop a condition at some point during their lifetime

Question 2

How is prevalence calculated?

Answer 2

Number of people with the condition number of people in total X years observed

Question 3

How is prevalence used?

How may it be affected?

Answer 3

Used to:

• Gauge the burden of a disease

Affected by:

• Duration of disease (i.e. common cold may have low point prevalence in a sample but is actually very common- high incidence)

Question 4

Define incidence

Answer 4

The rate at which new events occur in a population over a defined period of time

Question 5

How is incidence expressed?

Answer 5

• Per n people per time period OR
• Per n person-years

eg 100 cases per 1000 people

or 100 cases per 1000 person years

Question 6

Give an example of a condition with:

High incidence but low prevalance

High incidence and high prevalence

Low incidence but high prevalence

Low incidence and low prevalence

Answer 6

High Incidence Low Incidence

High Prevalence Common cold T1DM (common, not brief) (uncommon, LT)

Low Prevalence Nose bleeds Pancreatic ca. (common, brief) (uncommon, ST)

Question 7

What factors affect prevalence?

Answer 7

Adds to:

• Incidence

Reduces:

• Mortality
• Cure rate
• Migration

Question 8

What is statistical inference?

Answer 8

Best guess based on data from a sample (point estimate)

Level of uncertainty also given

Question 9

What is a sample error?

What is the standard error?

What do high and low standard errors indicate?

Answer 9

Samplng error: The difference between the truth and the point estimate

Standard error: Numerical value that represents the sampling error.

• High standard error = inaccurate best guess
• Low standard error= more accurate best guess

Question 10

What can reduce the standard error?

Answer 10

Large sample size

Question 11

What is a confidence interval?

Answer 11

A range of plausible values to represent uncertainty.

E.g. 95% confidence interval:

if the finding is 80%, the true proportion is plausibly between 75% and 85%

Question 12

How are 95% confidence intervals calculated?

Answer 12

Lower bound = point estimate - (1.96 x standard error)

Upper bound= point estimate + (1.96 x standard error)