During these sad and trying times, in the middle of the SARS-CoV-2 pandemic, it is easy to be confused. Classical medias and social media channels do not help minimize the confusion; indeed they do help increase the confusion.

Beforehand, I want to say that Anthony S. Fauci was one of my youth heroes. I still remember that, in the middle of the HIV/AIDS pandemic, I was taking a train to go attend class at my University; during those long train commutes, I was reading, in Science, Nature, and Scientific American, the epic deeds of Fauci and Luc Montaigner, to save humankind from a pandemic; as we will see, one that was (when untreated) much worse than the current one. Other train travelers around me were reading news and people’s magazine. There was no twitter, snapchat, or goggling at that time.

Even Dr. Fauci has fallen into the fallacy of interchangeably using Case Fatality Rate (CFR) and Mortality Rate (MR), also called Death Rate. There is a video, widely available in every social media channel, where Fauci states, “[…] while influenza has a mortality of 0.1%, [Covid-19 infection derived SARS] carries a mortality of 1%”.

Although those figure are roughly correct for the early phase of the pandemic, those are Case Fatality Rates, not Mortality Rates. The difference is subtle, but, improper use of quantities leads to incorrect conclusions.

Mortality Rate is the number of people, who died of a certain disease, divided by the number of people that live in a geographical area (usually a country), in a defined interval of time (usually a year)¹

As an example, the 2018 flu virus was particularly lethal. In the US (geographical area), during the solar year 2018 (interval of time) there were (estimated) 80,000 deaths due to flu. Thus the mortality rate, in the US and in 2018, for flu, was:

or 0.024 %, or 24 per 100,000 people living in the US during 2018. The MR indicates that 24 people every 100,000 inhabitants died of flu, or flu consequences, irrespective of the flu virus ability to spread across the population.

Case Fatality Rate measures the lethality of a disease. CFR is the number of deaths due to a disease divided by the number of people affected by the same disease².

Exact CFR for flu is not known. Reason being many have flu during the fall, winter season, but they do not report it, not even to their personal doctor. They cuddle at home, watching TV, with grandma’s remedies passed down for generations. They wait it out.

We do not really know the exact or approximate CFR for flu. We do not know how many people are subject to flu every flu season. The often cited figure of 0.1% is out best guess based on adjustments and extrapolation.

When Dr. Fauci cites 0.1% as “mortality” of flu, he actually means CFR.

It has been widely reported, including by Dr. Fauci, that the CFR for Covid-19 (Co-Sars-2) is 1%.

Based on current data, I estimated unasjusted CFR for Covid-19 (SARS-CoV-2) infections to be around 1.8% for the month of September 2020, nation-wide; 1.5% for the month of October 2020. This is a crude CFR, based solely on counts of deceased patients and positive individuals. The 1% figure reflect adjustments made due to the fact that there are individuals who contract the SARS-CoV-2, with minimal or no symptoms. They never go seek a PCR test, thus, they are not counted among the positive individuals.

1.8% crude, unadjusted CFR mean 0.4% adjusted CFR. 1.3% crude, unadjusted CFR mean 0.333% adjusted CFR.

CFR, crude or adjusted, measures the leathality of a disease. Howe does SARS-CoV-2 stack up to other diseases?

The 1% figure for SARS-Cov-2 has to be taken into a context of data that is continuously varying and being updated. Also, it represents somewhat of a global average. Once the SARS-CoV-2 pandemic will be over, we will take an epidemiological look back and we will know the real and definitive CFR for the disease.

In another post I’ve calculated the adjusted CFR for the month of October to be around 0.33%

Grand averages do not, however, describe an evolving situation, and do not help making timely and data guided decisions.

For that we need to look at daily evolving data.

1. Robert H. Friis , “Epidemiology 101”, Jones & Bartlett Learning [↩]
2. Robert H. Friis , “Epidemiology 101”, Jones & Bartlett Learning [↩]