# Case fatality rate

In epidemiology, case fatality rate (CFR) – or sometimes more accurately case-fatality risk – is the proportion of people diagnosed with a certain disease, who end up dying of it. Unlike a disease's mortality rate, the CFR does not take into account the time period between disease onset and death. A CFR is generally expressed as a percentage. It represents a measure of disease lethality and may change with different treatments.[1] CFRs are most often used for with discrete, limited-time courses, such as acute infections.

## Terminology

The mortality rate  –  often confused with the CFR  –  is a measure of the relative number of deaths (either in general, or due to a specific cause) within the entire population per unit of time.[2] A CFR, in contrast, is the number of deaths among the number of diagnosed cases only, regardless of time or total population.[3]

From a mathematical point of view, by taking values between 0 and 1 or 0% and 100%, CFRs are actually a measure of risk  (case fatality risk) – that is, they are a proportion of incidence, although they don't reflect a disease's incidence. They are neither rates, incidence rates, nor ratios (none of which are limited to the range 0–1). They do not take into account time from disease onset to death.[4][5]

Sometimes the term case fatality ratio is used interchangeably with case fatality rate, but they are not the same. A case fatality ratio is a comparison between two different case fatality rates, expressed as a ratio. It is used to compare the severity of different diseases or to assess the impact of interventions.[6]

Because the CFR is not an incidence rate by not measuring frequency, some authors note that a more appropriate term is case fatality proportion.[7]

## Example calculation

If 100 people in a community are diagnosed with the same disease, and 9 of them subsequently die from the effects of the disease, the CFR would be 9%. If some of the cases have not yet resolved (neither died nor fully recovered) at the time of analysis, a later analysis might take into account additional deaths and arrive at a higher estimate of the CFR, if the unresolved cases were included as recovered in the earlier analysis. Alternatively, it might later be established that a higher number of people were subclinically infected with the pathogen, resulting in an IFR below the CFR.

A CFR may only be calculated from cases that have been resolved through either death or recovery. The preliminary CFR, for example, of a newly occurring disease with a high daily increase and long resolution time would be substantially lower than the final CFR, if unresolved cases were not excluded from the calculation, but added to the denominator only.

${\displaystyle {\text{CFR in }}{\%}={\frac {\text{Number of deaths from disease}}{\text{Number of confirmed cases of disease}}}\times 100}$[8]

## Infection fatality rate

Like the case fatality rate, the term infection fatality rate (IFR) also applies to infectious diseases, but represents the proportion of deaths among all infected individuals, including all asymptomatic and undiagnosed subjects. It is closely related to the CFR, but attempts to additionally account for inapparent infections among healthy people.[9] The IFR differs from the CFR in that it aims to estimate the fatality rate in both sick and healthy infected: the detected disease (cases) and those with an undetected disease (asymptomatic and not tested group).[10] Individuals who are infected, but show no symptoms, are said to have inapparent, silent or subclinical infections and may inadvertently infect others. By definition, the IFR cannot exceed the CFR, because the former adds asymptomatic cases to its denominator.

${\displaystyle {\text{IFR in }}{\%}={\frac {\text{Number of deaths from disease}}{\text{Number of infected individuals}}}\times 100}$[8]

## Examples

A half dozen examples will suggest the range of possible CFRs for diseases in the real world:

## References

1. ^ Rebecca A. Harrington, Case fatality rate at the Encyclopædia Britannica
2. ^ For example, a diabetes mortality rate of 5 per 1,000 or 500 per 100,000 characterizes the observation of 50 deaths due to diabetes in a population of 10,000 in a given year, resulting in a yearly diabetes mortality rate of 0.5%, far below the actual diabetic individual's fatality risk. (See Harrington, Op. cit..)
3. ^ "Coronavirus: novel coronavirus (COVID-19) infection" (PDF). Elsevier. 2020-03-25. Archived from the original (PDF) on 2020-03-27. Retrieved 2020-03-27.
4. ^ Entry “Case fatality rate” in Last, John M. (2001), A Dictionary of Epidemiology, 4th edition; Oxford University Press, p. 24.[ISBN missing]
5. ^ Hennekens, Charles H. and Julie E. Buring (1987), Epidemiology in Medicine, Little, Brown and Company, p. 63.[ISBN missing]
6. ^ Bosman, Arnold (2014-05-28). "Attack rates and case fatality". Field Epidemiology Manual Wiki. ECDC. Archived from the original on 2020-03-25. Retrieved 2020-03-25.
7. ^ Peter Cummings: Analysis of Incidence Rates. In: CRC Press (2019).
8. ^ a b "Estimating mortality from COVID-19". www.who.int. Retrieved 2021-12-13.
9. ^ "Infection fatality rate". DocCheck Medical Services GmbH. Retrieved 25 March 2020.
10. ^ "Global Covid-19 Case Fatality Rates". Centre for Evidence-Based Medicine. Retrieved 25 March 2020.
11. ^ a b Taubenberger, Jeffery K.; David M. Morens (January 2006). "1918 influenza: the mother of all pandemics". Emerging Infectious Diseases. Coordinating Center for Infectious Diseases, Centers for Disease Control and Prevention. 12 (1): 15–22. doi:10.3201/eid1201.050979. PMC 3291398. PMID 16494711. Archived from the original on 2009-10-06. Retrieved 2009-04-17.
12. ^ Li, F C K; B C K Choi; T Sly; A W P Pak (June 2008). "Finding the real case-fatality rate of H5N1 avian influenza". Journal of Epidemiology and Community Health. 62 (6): 555–559. doi:10.1136/jech.2007.064030. ISSN 0143-005X. PMID 18477756. S2CID 34200426. Retrieved 2009-04-29.
13. ^ Heymann DL, ed. (2008). Control of Communicable Diseases Manual (19th ed.). Washington, D.C.: American Public Health Association. ISBN 978-0-87553-189-2.
14. ^ "Yellow fever". Fact sheets. World Health Organization. 7 May 2019.
15. ^ USAMRIID (2011). USAMRIID's Medical Management of Biological Casualties Handbook (PDF) (7th ed.). U.S. Government Printing Office. ISBN 9780160900150.
16. ^
17. ^ Prentice, Michael B.; Rahalison, Lila (April 7, 2007). "Plague". Lancet. 369 (9568): 1196–1207. doi:10.1016/S0140-6736(07)60566-2. PMID 17416264. S2CID 208790222 – via PubMed.
18. ^ King, John W (April 2, 2008). "Ebola Virus". eMedicine. WebMd. Retrieved 2008-10-06.
19. ^ "Rabies Fact Sheet N°99". World Health Organization. July 2013. Retrieved 28 February 2014.