Skip to main content
Library homepage
 

Text Color

Text Size

 

Margin Size

 

Font Type

Enable Dyslexic Font
Medicine LibreTexts

6.10: Outbreaks and Epidemics

( \newcommand{\kernel}{\mathrm{null}\,}\)

The hypothetical case study above is an example of a point-source outbreak - or an outbreak caused by a single source. An outbreak is defined as a number of cases of a particular disease that is higher than what is normally expected (Houlihan & Whitworth, 2019). This definition can also be used for the term epidemic - an unusually large number of cases of a specific infection during a specific amount of time. The term outbreak is more often used to describe a local epidemic in a small geographic area - and is probably how we would categorize a foodborne illness that could be traced back to a single restaurant or meal as in the previous hypothetical example.

The use of the term epidemic can range from infectious diseases to behavioral issues or chronic conditions. For example, obesity was recognized as an epidemic in the U.S. in the late 1970’s, as more and more people were reporting higher weight-to-height ratios above the cut-off body mass index (BMI) for obesity - which is 30kg/m2. This upward trend in obesity prevalence has continued over the years, so that the rates of obesity are still higher than would be expected prior to the 1980s. If we are interested in the body mass index of American adults, we cannot possibly ask every single U.S. citizen what their height and weight is. Instead, a random sample is taken and a survey is sent out to this population which is assumed to be representative of the whole U.S. population. Obesity rates are typically calculated from surveys like the National Health and Nutrition Examination Survey (NHANES), (see Chapter 5 on more about study designs and longitudinal surveys like NHANES). Let’s say for example that 8,300 adults were surveyed, and 3,403 of them reported a BMI above 30. Those 3,403 adults make up 41% of the population surveyed, so the rate of obesity is inferred to be 41% for the entire population. The larger a randomized survey like this is, the more accurate it is to apply it to the entire population. Back in the years 1976-1980 the obesity rate was only 15% (Temple, 2022), (Bryan et al., 2021). This example is an oversimplification of the statistical analysis performed in studies like NHANES, which are far more nuanced and beyond the scope of this text. However, this example demonstrates the use of surveys and rates to define an epidemic.


6.10: Outbreaks and Epidemics is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts.

Support Center

How can we help?