# Prevalence

> Mediated Wiki article. Canonical URL: https://mediated.wiki/source/Prevalence
> Markdown URL: https://mediated.wiki/source/Prevalence.md
> Source: https://en.wikipedia.org/wiki/Prevalence
> Source revision: 1291964340
> License: Creative Commons Attribution-ShareAlike 4.0 International (https://creativecommons.org/licenses/by-sa/4.0/)

In [epidemiology](/source/Epidemiology), **prevalence** is the proportion of a particular population found to be affected by a medical condition (typically a disease or a risk factor such as smoking or seatbelt use) at a specific time.[1] It is derived by comparing the number of people found to have the condition with the total number of people studied and is usually expressed as a fraction, a percentage, or the number of cases per 10,000 or 100,000 people. Prevalence is most often used in [questionnaire](/source/Questionnaire) studies.

## Difference between prevalence and incidence

See also: [Incidence (epidemiology)#Incidence vs. prevalence](/source/Incidence_(epidemiology)#Incidence_vs._prevalence)

Prevalence is the number of disease cases *present*in a particular population at a given time, whereas [incidence](/source/Incidence_(epidemiology)) is the number of new cases that *develop*during a specified time period.[2] Prevalence answers "How many people have this disease right now?" or "How many people have had this disease during this time period?". Incidence answers "How many people acquired the disease [during a specified time period]?". However, mathematically, prevalence is proportional to the product of the incidence and the average duration of the disease. In particular, when the prevalence is low (<10%), the relationship can be expressed as:[3]

- Prevalence = incidence \times duration

Caution must be practiced as this relationship is only applicable when the following two conditions are met: 1) prevalence is low and 2) the duration is constant (or an average can be taken).[3] A general formulation requires [differential equations](/source/Differential_equation).[4]

## Examples and utility

In science, *prevalence* describes a [proportion](/source/Ratio) (typically expressed as a [percentage](/source/Percentage)). For example, the prevalence of obesity among American adults in 2001 was estimated by the U. S. [Centers for Disease Control (CDC)](/source/Centers_for_Disease_Control_and_Prevention) at approximately 20.9%.[5]

Prevalence is a term that means being widespread and it is distinct from [incidence](/source/Incidence_(epidemiology)). Prevalence is a measurement of *all* individuals affected by the disease at a particular time, whereas incidence is a measurement of the number of *new* individuals who contract a disease during a particular period of time. Prevalence is a useful parameter when talking about long-lasting diseases, such as [HIV](/source/HIV), but incidence is more useful when talking about diseases of short duration, such as [chickenpox](/source/Chickenpox). [citation needed]

## Uses

### Lifetime prevalence

**Lifetime prevalence** (**LTP**) is the proportion of individuals in a population that at some point in their life (up to the time of assessment) have experienced a "case" (e.g., a disease, a traumatic event, or, a behavior, such as committing a crime). Often, a 12-month prevalence (or some other type of "period prevalence") is provided in conjunction with lifetime prevalence. *Point prevalence* is the prevalence of disorder at a specific point in time (a month or less). *Lifetime morbid risk* is "the proportion of a population that might become afflicted with a given disease at any point in their lifetime."[6][7]

### Period prevalence

**Period prevalence** is the proportion of the population with a given disease or condition over a specific period of time. It could describe how many people in a population had a cold over the cold season in 2006, for example.[citation needed] It is expressed as a percentage of the population and can be described by the following formula:

Period prevalence (proportion) = Number of cases that existed in a given period ÷ Number of people in the population during this period[citation needed]

The relationship between incidence (rate), point prevalence (ratio) and period prevalence (ratio) is easily explained via an analogy with photography. Point prevalence is akin to a flashlit photograph: what is happening at this instant frozen in time. Period prevalence is analogous to a long exposure (seconds, rather than an instant) photograph: the number of events recorded in the photo whilst the camera shutter was open. In a movie each frame records an instant (point prevalence); by looking from frame to frame one notices new events (incident events) and can relate the number of such events to a period (number of frames); see [incidence rate](/source/Incidence_(epidemiology)).[citation needed]

### Point prevalence

**Point prevalence** is a measure of the proportion of people in a population who have a disease or condition at a particular time, such as a particular date. It is like a snapshot of the disease in time. It can be used for statistics on the occurrence of [chronic diseases](/source/Chronic_diseases). This is in contrast to period prevalence which is a measure of the proportion of people in a population who have a disease or condition over a specific period of time, say a season, or a year. Point prevalence can be described by the formula: Prevalence = Number of existing cases on a specific date ÷ Number of people in the population on this date [8]

## Limitations

It can be said that a very small error applied over a very large number of individuals (that is, those who are *not affected* by the condition in the general population during their lifetime; for example, over 95%) produces a relevant, non-negligible number of subjects who are incorrectly classified as having the condition or any other condition which is the object of a survey study: these subjects are the so-called false positives; such reasoning applies to the 'false positive' but not the 'false negative' problem where we have an error applied over a relatively very small number of individuals to begin with (that is, those who are *affected* by the condition in the general population; for example, less than 5%). Hence, a very high percentage of subjects who seem to have a history of a disorder at interview are false positives for such a medical condition and apparently never developed a fully clinical [syndrome](/source/Syndrome).[citation needed]

A different but related problem in evaluating the public health significance of psychiatric conditions has been highlighted by [Robert Spitzer](/source/Robert_Spitzer_(psychiatrist)) of [Columbia University](/source/Columbia_University): fulfillment of [diagnostic criteria](/source/Diagnostic_criteria) and the resulting [diagnosis](/source/Medical_diagnosis) do not necessarily imply need for treatment.[9]

A well-known statistical problem arises when ascertaining rates for disorders and conditions with a relatively low population prevalence or [base rate](/source/Base_rate). Even assuming that lay interview diagnoses are highly accurate in terms of [sensitivity](/source/Sensitivity_(tests)) and [specificity](/source/Specificity_(tests)) and their corresponding area under the [ROC curve](/source/ROC_curve) (that is, [AUC](/source/Area_under_the_curve), or area under the [receiver operating characteristic](/source/Receiver_operating_characteristic) curve), a condition with a relatively low prevalence or base-rate is bound to yield high [false positive](/source/Type_I_and_type_II_errors) rates, which exceed [false negative](/source/Type_I_and_type_II_errors) rates; in such a circumstance a limited [positive predictive value](/source/Positive_predictive_value), PPV, yields high [false positive](/source/False_positive) rates even in presence of a specificity which is very close to 100%.[10]

## See also

- [Denominator data](/source/Denominator_data)
- [Rare disease](/source/Rare_disease)
- [Base rate fallacy](/source/Base_rate_fallacy)

## References

1. ["Prevalence statistics"](https://www.health-ni.gov.uk/articles/prevalence-statistics#:~:text=Prevalence%20is%20a%20measure%20of,within%20a%20particular%20time%20period).). 26 August 2015. Retrieved 15 March 2022.

1. ["Definition of Prevalence"](https://www.medicinenet.com/script/main/art.asp?articlekey=11697). *MedicineNet*. Retrieved 2019-12-03.

1. Bruce, Nigel; Pope, Daniel; Stanistreet, Debbi (29 November 2017). *Quantitative methods for health research : a practical interactive guide to epidemiology and statistics*. Second ed. Hoboken, NJ. p. 16. ISBN 978-1-118-66526-8. [OCLC 992438133](https://www.worldcat.org/oclc/992438133)

1. Brinks, Ralph (2018). "Illness-Death Model in Chronic Disease Epidemiology: Characteristics of a Related, Differential Equation and an Inverse Problem". *Computational and Mathematical Methods in Medicine*. **2018**: 1–6. [doi:10.1155/2018/5091096](https://doi.org/10.1155/2018/5091096). [PMC 6157110](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157110). [PMID 30275874](https://pubmed.ncbi.nlm.nih.gov/30275874)

1. ["Overweight and Obesity: Obesity Trends | DNPA | CDC"](https://www.cdc.gov/nccdphp/dnpa/obesity/trend/prev_reg.htm). [Archived](https://web.archive.org/web/20060624145234/http://www.cdc.gov/nccdphp/dnpa/obesity/trend/prev_reg.htm) 2006-06-24 at the Wayback Machine. Retrieved 2017-09-10.

1. Kenneth J. Rothman (21 June 2012). [*Epidemiology: An Introduction*](https://books.google.com/books?id=tKs7adtH-_IC&pg=PA53). Oxford University Press. p. 53. ISBN 978-0-19-975455-7.

1. Kruse, Matthew & Schulz, S. Charles (2016). "Chapter 1: Overview of schizophrenia and treatment approaches". *Schizophrenia and psychotic spectrum disorders*. New York: Oxford University Press. p. 7. ISBN 978-0-19-937806-7.

1. Gerstman, B.B. (2003). *Epidemiology Kept Simple: An Introduction to Traditional and Modern Epidemiology (2nd ed.)*. Hoboken, NJ: Wiley-Liss.

1. Spitzer, Robert (February 1998). ["Diagnosis and need for treatment are not the same"](http://archive.wikiwix.com/cache/20110705210403/http://archpsyc.ama-assn.org/cgi/pmidlookup?view=long&pmid=9477924). *Archives of General Psychiatry*. **55** (2): 120. [doi:10.1001/archpsyc.55.2.120](https://doi.org/10.1001/archpsyc.55.2.120). [PMID 9477924](https://pubmed.ncbi.nlm.nih.gov/9477924). Archived from [the original](http://archpsyc.ama-assn.org/cgi/pmidlookup?view=long&pmid=9477924) on 2011-07-05.

1. Baldessarini, Ross J.; Finklestein S.; Arana G. W. (May 1983). "The predictive power of diagnostic tests and the effect of prevalence of illness". *Archives of General Psychiatry*. **40** (5): 569–73. [doi:10.1001/archpsyc.1983.01790050095011](https://doi.org/10.1001/archpsyc.1983.01790050095011). [PMID 6838334](https://pubmed.ncbi.nlm.nih.gov/6838334)

## External links

- [PlusNews, the UN's HIV/AIDS news service provides HIV prevalence rates for nearly 60 countries worldwide](http://www.plusnews.org/country-profile.aspx)
- [Synopsis of article on "How Prevalent Is Schizophrenia?" from Public Library of Science](https://web.archive.org/web/20071117234209/http://medicine.plosjournals.org/perlserv/?request=get-document&doi=10.1371%2Fjournal.pmed.0020146)
- [Prevalence of COVID-19 outbreak](https://www.europeanreview.org/article/20379)
- [https://www.prevalenceuk.com/](https://www.prevalenceuk.com/)

---
Adapted from the Wikipedia article [Prevalence](https://en.wikipedia.org/wiki/Prevalence) by Wikipedia contributors ([contributor history](https://en.wikipedia.org/wiki/Prevalence?action=history)). Available under [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/). Changes may have been made.