What is Case Fatality Rate (CFR)?

Case Fatality Rate (CRF) measures the severity of a particular disease by defining the total number of deaths as a proportion of reported cases of a specific disease at a specific time.

Case Fatality Rate

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How is CFR Determined?

CFR is presented as a percentage (0%-100%) or a ratio (between 0-1) and measures the number of confirmed deaths among the number of confirmed diagnosed cases of a particular disease at a given time.

This is different from general mortality rates which are the number of general deaths that occur within a population (normalized to the population) at any given time.

For example, if 15 people die from seasonal flu (in that particular winter) out of 1000 confirmed diagnoses, then the CFR would be 1.5% or 0.015. This is not the percentage of deaths from seasonal flu in the whole population, as that would be far lower.

However, CFR (as with most epidemiological statistics) heavily relies on confirmed cases and deaths and may not accurately reflect the total picture within the population due to unreported cases and subsequent deaths.

CFR can vary considerably for the same disease across different cities and countries. Much of this can depend on the population's characteristics – such as average age, as well as access to robust and free healthcare systems, levels of previous immunity (e.g. vaccinations), and treatment strategies.

Also, the infection fatality rate (IFR) refers to the proportion of people being infected by a disease-causing agent (in the case of COVID-19, the SARS-CoV-2 virus), including asymptomatic and undiagnosed infections (such as in care homes), who die from the disease; and is much lower than the CFR. The IFR is often very difficult to establish due to the variable estimates of asymptomatic and undiagnosed infections within a population.

CFR of Common Diseases

Specific CFRs of particular diseases if left untreated or unvaccinated for include:

  • Bubonic Plague – 60%
  • Spanish Flu (1918) – 2.5%
  • Ebola – 90%
  • Naegleriasis – >99%
  • Smallpox – 95%
  • Seasonal Influenza – 0.1%
  • HIV/AIDS – 80%
  • Dengue Fever – 26%
  • Malaria – 0.3%
  • Typhoid – 10-20%
  • SARS – 9-11%
  • MERS – 34.4%
  • COVID-19 – ~0.8-9.6* (variable estimates due to ongoing pandemic – see below)

CFR and COVID-19

SARS-CoV-2 Virus

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The coronavirus disease-2019 (COVID-19) pandemic caused by the SARS-CoV-2 virus (first identified in Wuhan, China) had brought the world to a standstill with national lockdowns in force throughout the world to combat cases and fatalities.

Worldwide confirmed cases have exceeded 6 million, with approximately 370,000+ deaths from COVID-19 resulting in a worldwide death-to-case ratio (the number of deaths divided by the number of diagnosed cases) of 6% of all confirmed cases, although this varies considerably.

Several nations experienced high numbers of deaths relative to the affected population (higher CFR). One such country was Italy, which has an overall CFR of 14.3% for COVID-19, compared to China which has a CFR of 5.3%. This could be due to the mean age differences in Italy, where people aged 70 or over account for 37.6% of the population, compared to China where only 11.9% are over 70.

In the UK, there are approximately 276,000+ confirmed cases with 39,000+ deaths (end of May 2020) resulting in a CFR of 14.1%. Germany on the other hand has 183,765 confirmed cases with 8,618 deaths thus a CFR of 4.7%. Singapore has had 35,836 confirmed cases with only 24 deaths thus a CFR of 0.07%. However, it is important to note that the overall fatality rate across the entire population is estimated to be around 0.2-1%.

The variability of such estimates also depends on the levels of testing (reflecting a more accurate diagnosis and prevalence of the disease within a population), as well as strict lockdown measures from early on and strict adherence to such measures.

In the UK, testing is not routine or that prevalent (as of June 2020) thus the actual CFR may be a lot lower due to the unreported cases of COVID-19. Germany has had much better testing routines than the UK and thus the CFR of 4.7% is more in line with the average reported.

The emerging evidence suggests that the overall CFR or COVID-19 is in the region of 1-9% depending on population and demographic characteristics. This is much lower than the CFR for SARS and MERS, but potentially much higher than seasonal influenza.

Furthermore, CFR amongst specific populations within a population e.g. black and Asian ethnic minorities, are much more disproportionately affected than the general population in the UK, for example. The presumed IFR of SARS-CoV-2 is in the region of 0.1-1.08% whereas the IFR for seasonal influenza is 0.1%.

In summary, CFR measures the severity of a particular infectious disease within a particular environment at a specific time. Specifically, it refers to the total number of deaths due to a specific disease as a percentage of the total number of confirmed diagnoses of that disease. Different diseases have different CFRs, and many biological, social, political, and environmental factors can alter the CFR within a population.

A disease can be very infectious (spreads easily) but have a low CFR due to the nature of the disease as well as the presence of vaccinations and treatments, whilst other diseases are not as infectious (not as easily spread) but are more deadly.

New disease outbreaks (such as COVID-19) can lead to significantly higher CFR in the first wave, but a lower CFR in subsequent peaks due to ‘herd immunity’ in addition to the development of potential vaccinations and effective treatments.

However, if vaccinations and treatments are not in place before a second peak, then the CFR will remain as high (if not higher), unless strict measures are brought in place promptly.

Sources:

Further Reading

Last Updated: Jun 8, 2020

Osman Shabir

Written by

Osman Shabir

Osman is a Neuroscience PhD Research Student at the University of Sheffield studying the impact of cardiovascular disease and Alzheimer's disease on neurovascular coupling using pre-clinical models and neuroimaging techniques.

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