Case fatality rate

In epidemiology, a case fatality rate (CFR) — sometimes called case fatality risk or case-fatality ratio — is the proportion of deaths from a certain disease compared to the total number of people diagnosed with the disease for a certain period of time. A CFR is conventionally expressed as a percentage and represents a measure of disease severity.[1] CFRs are most often used for diseases with discrete, limited time courses, such as outbreaks of acute infections. A CFR can only be considered final when all the cases have been resolved (either died or recovered). The preliminary CFR, for example, during the course of an outbreak with a high daily increase and long resolution time would be substantially lower than the final CFR.

Terminology

A mortality rate — often confused with a CFR — is a measure of the number of deaths (in general, or due to a specific cause) in a population scaled to the size of that population per unit of time.[2] A CFR, in contrast, is the number of dead among the number of diagnosed cases.[3]

Technically, CFRs, which take values between 0 and 1 (or 0% and 100%, i.e., nothing and unity), are actually a measure of risk — that is, they are a proportion of incidence. They are not rates, incidence rates, or ratios (none of which are limited to the range 0-1). Hence, even though the terms “case fatality rate” and “CFR” appear often in the scientific literature, if one wishes to be very precise, they are incorrectly used, because they do not always, in every instance, 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. Case fatality ratio is the comparison between two different case fatality rates, expressed as ratio. It also can be used to compare different diseases or to assess the impact of an intervention.[6]

Infection fatality rate

The term infection fatality rate (IFR) also applies to infectious disease outbreaks, and represents the proportion of deaths among all the infected individuals. It is closely related to the CFR, but attempts to additionally account for all asymptomatic and undiagnosed infections.[7] The IFR differs from the CFR in that it aims to estimate the fatality rate in all those with infection: the detected disease (cases) and those with an undetected disease (asymptomatic and not tested group).[8] (Individuals who are infected, but always remain asymptomatic, are said to have "inapparent" — or silent, or subclinical — infections.) The IFR will always be lower than the CFR as long as all deaths are accurately attributed to either the infected or the non-infected class.

Example calculation

100 people in a community are diagnosed with the same disease; subsequently 9 of them die from the effects of the disease. The CFR at this point in time, therefore, 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.

Real-world examples

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

  • The CFR for the Spanish (1918) flu was >2.5%,[9] but about 0.1% for the Asian (1956-58) and Hong Kong (1968-69) flus,[10] and <0.1% for other influenza pandemics.[9]
  • Legionnaires' disease has a CFR of ≈15%.
  • Yellow fever has a CFR of about 3–7.5%.
  • Bubonic plague has the best prognosis of the three main variants of plague, but if left untreated, has a CFR >60%.
  • Ebola virus is among the deadliest viruses, with a CFR as high as 90%.
  • Naegleriasis (also known as primary amoebic meningoencephalitis), caused by the unicellular Naegleria fowleri (a.k.a. the brain-eating amoeba), nearly always results in death, and so has a CFR >99%.
  • Rabies virus is almost invariably fatal if left untreated, and so has a CFR approaching 100%; however, patients generally respond well to prompt post-exposure prophylaxis.
  • Prion diseases are progressive and always fatal, regardless of treatment.

See also

References and notes

  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. (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.
  5. Hennekens, Charles H. and Julie E. Buring (1987), Epidemiology in Medicine, Little, Brown and Company, p. 63.
  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. "Infection fatality rate". DocCheck Medical Services GmbH. Retrieved 25 March 2020.
  8. "Global Covid-19 Case Fatality Rates". Centre for Evidence-Based Medicine. Retrieved 25 March 2020.
  9. 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 2009-10-01. Retrieved 2009-04-17.
  10. 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. Retrieved 2009-04-29.
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