Case fatality rate

Not to be confused with mortality 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 do not 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.^{[citation needed]}

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

Main article: List of human disease case fatality rates

Some examples will suggest the range of possible CFRs for diseases in the real world:

• The CFR for the Spanish (1918) flu was greater than 2.5%, while the Asian (1957-58) and Hong Kong (1968-69) flus both had a CFR of about 0.2%.^[11][12][13]
• As of 23 Nov 2023, coronavirus disease 2019 has an overall CFR of 0.9%, while the CFRs for original SARS and MERS are about 11% and 34%, respectively.^[14][15][16]
• The CFR for yellow fever is about 5-6% (but 40-50% in severe cases).^[17][18][19]
• Legionnaires' disease has a CFR of about 15%.^[20]: 665
• Left untreated, bubonic plague will have a CFR of up to 60%.^[21]: 57 With antibiotic treatment, the CFR for bubonic plague is 17%, pneumonic 29% and septicaemic 45%.^[22][23]
• Active tuberculosis, the infection with the highest mortality rate, has a CFR of 43% in the absence of HIV.^[24][25]
• Ebola virus disease, one of the infections with the highest lethality, has a CFR as high as 90%.^[26]
• Naegleriasis (also known as primary amoebic meningoencephalitis), has a CFR greater than 95%, with a few of the survivors having been treated with heroic doses of amphotericin B and other off-label drugs.^{[citation needed]}
• Rabies has a CFR greater than 99% in unvaccinated individuals.^[27] A few people have survived either by being vaccinated (but after symptoms started, or else later than ideal), or more recently, by being put into a medically induced coma.^{[citation needed]}

See also

•  Medicine portal

• List of human disease case fatality rates
• Mortality rate – Deaths per 1000 individuals per year
• Pandemic severity index – Proposed measure of the severity of influenza

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. (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 0-19-514168-7
5. Hennekens, Charles H. and Julie E. Buring (1987), Epidemiology in Medicine, Little, Brown and Company, p. 63. ISBN 0-316-35636-0
6. Bosman, Arnold (2014-05-28). "Attack rates and case fatality". Field Epidemiology Manual Wiki. ECDC. from the original on 2020-03-25. Retrieved 2020-03-25.
7. Peter Cummings: Analysis of Incidence Rates. In: CRC Press (2019).
8. "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. "Report of the Review Committee on the Functioning of the International Health Regulations (2005) in relation to Pandemic (H1N1) 2009" (PDF). 2011-05-05. p. 37. (PDF) from the original on 14 May 2015. Retrieved 1 March 2015.
12. Taubenberger, Jeffery K.; David M. Morens (January 2006). . 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.
13. 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.
14. Ritchie, Hannah; Mathieu, Edouard; Rodés-Guirao, Lucas; Appel, Cameron; Giattino, Charlie; Ortiz-Ospina, Esteban; Hasell, Joe; Macdonald, Bobbie; Beltekian, Diana; Dattani, Saloni; Roser, Max (2020–2022). "Coronavirus Pandemic (COVID-19)". Our World in Data. Retrieved 2023-11-23.
15. Chan-Yeung, Moira; Xu, Rui-Heng (November 2003). "SARS: epidemiology". Respirology. 8 (s1): S9–S14. doi:10.1046/j.1440-1843.2003.00518.x. ISSN 1323-7799. PMC 7169193. PMID 15018127.
16. "MERS situation update, January 2020". World Health Organization - Regional Office for the Eastern Mediterranean.
17. "Yellow fever". Fact sheets. World Health Organization. 7 May 2019.
18. Johansson, Michael A.; Vasconcelos, Pedro F.C.; Staples, J. Erin (June 30, 2014). "The whole iceberg: estimating the incidence of yellow fever virus infection from the number of severe cases". Transactions of the Royal Society of Tropical Medicine and Hygiene. 108 (8): 482–487. doi:10.1093/trstmh/tru092. PMC 4632853. PMID 24980556 – via Oxford University Press.
19. Servadio, Joseph L.; Muñoz-Zanzi, Claudia; Convertino, Matteo (August 16, 2021). "Estimating case fatality risk of severe Yellow Fever cases: systematic literature review and meta-analysis". BMC Infectious Diseases. 21 (819): 819. doi:10.1186/s12879-021-06535-4. PMC 8365934. PMID 34399718. S2CID 237056056.
20. Heymann DL, ed. (2008). Control of Communicable Diseases Manual (19th ed.). Washington, D.C.: American Public Health Association. ISBN 978-0-87553-189-2.
21. USAMRIID (2011). (PDF) (7th ed.). U.S. Government Printing Office. ISBN 9780160900150. Archived from the original (PDF) on 2015-02-09. Retrieved 2021-11-25.
22. WHO guidelines for plague management: revised recommendations for the use of rapid diagnostic tests, fluoroquinolones for case management and personal protective equipment for prevention of post-mortem transmission [Internet]. World Health Organization. 2021.
23. 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.
24. Lozano, Rafael; et al. (December 2012). "Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010". The Lancet. 380 (9859): 2095–2128. doi:10.1016/s0140-6736(12)61728-0. ISSN 0140-6736. PMID 23245604. S2CID 1541253.
25. Tiemersma, Edine W.; van der Werf, Marieke J.; Borgdorff, Martien W.; Williams, Brian G.; Nagelkerke, Nico J. D. (4 April 2011). "Natural History of Tuberculosis: Duration and Fatality of Untreated Pulmonary Tuberculosis in HIV Negative Patients: A Systematic Review". PLOS ONE. 6 (4): e17601. Bibcode:2011PLoSO...617601T. doi:10.1371/journal.pone.0017601. ISSN 1932-6203. PMC 3070694. PMID 21483732.
26. King, John W (April 2, 2008). "Ebola Virus". eMedicine. WebMd. Retrieved 2008-10-06.
27. "Rabies Fact Sheet N°99". World Health Organization. July 2013. Retrieved 28 February 2014.

External links