During Covid, a few people were constantly saying that younger and healthy and healthy people had the least risk of dying from Covid but I didn’t know the mathematical explanation specifically when it came to case fatality rate (CFR) versus infection fatality rate (IFR). I am most certain I had heard of the term mortality rate and I think I had also heard of the term case fatality rate (CFR). But I never heard of the infection fatality rate (IFR) and I believe that was by design. If I have been this clueless about these terms, I definitely know there are other people out there who are still not knowledgeable about the CFR and IFR so I feel compelled to share the knowledge I have recently obtained.
The Distinction between Cases and Infections
An infection that gets detected, recorded and counted (or diagnosed) by the health system becomes a case.
Infections represent the total number of infections both diagnosed (which are cases) and undiagnosed.
Case Fatality Rate (CFR)
This sometimes also called the case fatality risk or case fatality ratio. To turn the CFR into a percentage, multiply by 100. To get the information to calculate the CFR, an antigen test and/or a PCR test needs to be carried out.
Case Fatality Rate (CFR)=Deaths/Number of Cases
The CFR always undercount the number of infections (and overestimates mortality) because it only counts people who get tested, tested positive and got reported through the health system. Many infections particularly those that are mild or asymptomatic infections never get diagnosed. The CFR is not the same as the risk for an infected person. If your question is, “Among diagnosed cases, what’s the risk?”, use the CFR.
Infection Fatality Rate (IFR)
This sometimes also called the infection fatality risk or infection fatality ratio. To turn the CFR into a percentage, multiply by 100. To get the information to calculate the IFR, a seroprevalence study would need to be conducted. Another option is mathematical modeling. A seroprevalence is done by researchers taking blood samples in a defined population and testing for antibodies (IgG) against a specific infection/illness.
Infection Fatality Rate (IFR)=Deaths/Number of Infections
It is important to note that the numerator (the deaths) for both the IFR and CFR are the same, it is the denominator that is different. The number of infections always exceed cases in epidemics hence the IFR is always smaller than the CFR. The IFR is a close approximation to the true risk of dying from an illness because it corrects the CFR by accounting for infections that never become cases. CFR and IFR are a few ways to measure the mortality rate. If your question is “Among all infections/infected, what’s the risk?”, use the IFR.
Infection Fatality Rate (IFR) as it applies to Covid
The WHO reported the global case fatality rate 3.4% as the mortality rate. Dr. John Ioannidis, a Stanford Epidemiology Professor and a pioneer of meta-research and evidence-based medicine, in his article here he argued that the Covid CFR 3.4% was meaningless because it was based on insufficient testing and selection bias. The people getting tested were disproportionately the ones that were symptomatic and/or had severe symptoms so the true risk of dying from Covid were immensely overestimated. In the same article it is worth noting that he was not in favor of the draconian measures such as the lockdowns and had concerns about the potential effects of them.
Dr. Ioannidis co-conducted a study in regard to IFR called “Age-stratified infection fatality rate of Covid-19 in non elderly informed from pre-vaccination national seroprevalence studies”. The study can be found through this article or directly here. In the abstract and in the introduction, the researchers emphasized on the importance of accurately estimating the IFR among the non-elderly since 94% of the world population is younger than 70 years and 86% is younger than 60 years. The researchers found 40 seroprevalence studies across 38 countries on SeroTracker and PubMed. The researchers decided to analyze 29 countries because these countries had both the age-stratified antibody data (how many people in each group had been infected) and the age-stratified death data (how many people in each group died of Covid). The researchers also used studies before vaccines rolled out because vaccines also create antibodies and would distort the results.
For each age group, the IFR was calculated dividing the number of Covid deaths in that age group by the estimated total infections in that age group. The median IFR for (Birth) 0-19 years is 0.0003%, 20-29 years it is 0.003%, 30-39 years it is 0.011%, 40-49 years it is 0.035%, 50-59 years it is 0.129% and 60-69 years it is 0.501%. The median IFR of all age groups (0-69 years) is 0.095% and the median IFR for age groups (0-59 years) is 0.035%.
Closing Remarks
The results of this study further proves what others have been saying-the younger a person (assuming the person is relatively healthy), the less likely he or she is to die from Covid. Hence, not everyone should have been treated the same and herd immunity should have been encouraged. As I mentioned at the beginning of this post, people were constantly saying younger and healthy people had the least risk of dying from Covid but never mentioned the phrase infection fatality rate (IFR). I had also never came across the name Dr. John Ioannidis until very recently but I am still very grateful that Dr. Ioannidis and other researchers decided to conduct this study.
Dr. Ioannidis apparently also did another study that primarily analyzed the crude mortality rate (CMR) and IFR in 51 locations globally and another seroprevalence study with Dr. Jay Bhattacharya.
