Mathematics of the Flu vs. COVID-19

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The World Health Organization has advice about how to deal with the flu. They also have some articles that compare and contrast the flu with COVID-19. (For a recent interview, click here.)

Likewise, the CDC have information on the flu. (And here.) They also have articles that compare and contrast the flu with COVID-19.

We are all aware of how deadly Coronavirus can be. I wrote an article here. Three weeks later, the CDC produced their own article here. The table below compares/contrasts the results of the two articles. My article (labelled in the table as BT/NY) relied on New York data. The CDC’s estimate appears to be nationwide. From here on, in this article, when I refer to the survival rate of COVID-19, I am referring to the CDC’s figures.

The CDC provides recommendations on how to deal with the situation, as does the World Health Organization. (The World Health Organization also has a myth buster section.) I am providing no additional guidance on how to deal with the COVID-19; I only reference the CDC’s estimate of the COVID-19 survival rate to provide context.

Having said that, how deadly is the flu?

The CDC provides estimates of how many people will show symptoms of the flu and, of these, how many will die as a result. The table below is an image from their website. (Note that “95%Ul” means the upper 95% percentile and lower 5% percentile of their estimate.)

We can take the ratio of symptomatic illnesses to deaths to estimate the survival rate of those who have symptoms.

The above table shows the survival rate for those having symptoms of the flu.

Please note, that this is for all Americans and 40 to 60% of Americans receive the flu vaccination, as the chart below shows. One can only guess what the flu death rates would be without a vaccine.

You may be wondering about the frequency of asymptomatic carriers of the influenza virus. This is difficult to answer. I believe this article, published by the National Institute of Health, provides the best overview of knowledge on this topic. The article shows that academic studies which attempt to estimate this value have a very wide range. The estimates of asymptomatic fraction range from 0% to 100%. For purposes of this article, let’s assume that the asymptomatic fraction is 50%. This would imply that for every symptomatic case of the flu, there is an additional person who is infected with the influenza virus who could theoretically be passing it on to others.

If we adjust our table by this ratio, our mathematics look like this.

Because of the massive coverage of the ongoing COVID-19 pandemic, most people are aware of the lethality of COVID-19. However, many people may not be aware of corresponding data on the flu. The table below compares/contrasts these statistics.

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You can compare the survival and death rates of various age ranges using the table above.

Post script:

You may be wondering how often individuals contract the influenza virus. The image below, copied from Oxford Academic, provides an estimate of the frequency of flu symptoms of 8.3% for all ages (which takes into account the flu vaccine). If we assume a yearly rate of 8.3% of Americans contracting symptomatic flu and 8.3% contracting asymptomatic flu (consistent with our assumption of 50% asymptomatic above), then we are assuming 16.6% of Americans will contract the influenza virus each year. If we assume this 16.6% is constant across the population from year to year, then using a Kaplan-Meier estimate, the median American (assuming 50% asymptomatic) will contract the influenza virus approximately every 4 years (although symptoms may appear on average only every 8 years). (You see this by multiplying (1-.166) until you get below .5)

Some sources on the flu vs COVID-19 can be seen by John Hopkins here, and the CDC here. Note that the CDC says that both the flu and COVID-19 can spread prior to a person becoming symptomatic.

If you found this information useful, please consider reposting.

How to Calculate the Mortality of Joe Biden

Written by Benjamin Turner

This article was published on 10/9/202 on 7:15 am on LinkedIn. It was removed on 9:15 am of the same day by LinkedIn.

Fraudspotters, LLC, nor its employees express any opinion about this article. We are publishing it out of solidarity with an employee.

As an actuary, I’m asked how long to expect Joe Biden to live.

This is a morbid question but relevant. We just experienced a VP debate which may have actually been our presidential debate, and this is a good opportunity to teach people about actuarial mathematics. And, as an actuary, this type of stuff is literally what I do, so it is not morbid to me; it is common place.

So, without further ado…

To calculate the mortality rate go to a published actuary table. An obvious one is found here, and I will reference this table. You should see a webpage that looks like the image below. This is a table produced by the Social Security Administration to project how long people will live for purposes of understanding how much will be paid from Social Security (at a younger age, I worked as a pension actuarial analyst for Mercer Consulting).

The place that says “select a year for period life table: 2016” is referencing the data / time period used for estimation. We are going to use 2016 as this is the latest year offered at this website; however, if you select slightly different years you won’t see much of a change as the mortality rate is not changing much for Americans.

Since Joe Biden is male and will be 78 in November, we are going to obtain data relevant to that age and gender. Below is the data I will be using. In the first column, the first value, which is .047826, is the chance of dying in that age. I will be focused on this column because if we do 1-X on this column we get the survival rate. So, for example, the chance of surviving from age 78 to age 79 is 1-.047826 = 0.952174 = 95.2174% This is similar to the chance of surviving Covid-19 if you are over 70, which is 94.6%.

If we perform the 1-X calculation on all of the relevant ages we obtain the following table shown below. The survival probability is the chance of living to the next age, given that you survived to the given age. So, for example, if Joe Biden lives to age 86 he has an 89.1% chance of making it to age 87.

If we want to calculate the chance of making it several years than we combine the survival rates by multiplying them together. For example, the chance of making it from age 78 through age 79 to age 80 is 95.2% X 94.7% = 90.2%

If we perform this type of mathematics from age to age, we obtain Joe Biden’s chances of making it to a given age. As the table below shows, if Joe Biden serves two terms, his expected chance of surviving to the end is 49.8%. In other words, over a two-term time period, there is a 50.2% chance that Joe Biden’s VP has to be sworn-in. In addition to mortality, there is the chance of becoming disabled, but that is not the purpose of this post.

If you have read this far, you probably are wondering Donald Trump’s chances of making it to the end of four years. Donald Trump is male and turned 74 back in June, so we’ll use male and age 74. As the table below shows, there is a 85.7% chance of survival. In other words, there is 14.3% chance that over the next term, Donald Trump’s VP would need to be sworn- in. (Please note, the purpose of this article is not to compare/contrast Donald Trump’s chance of survival to that of Joe Biden. There are other factors besides their ages that affect their probability of survival. I am not a privy to those factors. This article is to teach the reader the basic concepts of how to calculate the chances of survival.)

Final thoughts/changing topics.

LinkedIn censored my last article about the mortality rate of infectious diseases on the grounds of “misinformation”. They removed it. When I challenged their removal, they gave a “second look” and affirmed their ban of my article. All data in that article was from the reputable sources such as the CDC or the Social Security Administration; I provided no original research. My only contribution was that I simply explained to the reader how to do the math, like I am doing in this article. That article can be seen here.

To LinkedIn, I’d like to coin a phrase by saying the following, “True science never censors, it only counters with the truth.” If you believe something I say is untrue, please counter with something you believe is true.

You Can Compare and Contrast Covid-19 to the Flu

By Benjamin Turner

Published on 2020-10-05 16:53 on LinkedIn



Fraudspotters, LLC, takes no position with regards to this article. Furthermore, this article does not reflect the opinion of all employees.

However, in solidarity with our lead analyst, and in the interest of freedom of information on the Internet, we are posting the article below….


There seems to be a lot of buzz on the web about Covid-19 vs. the flu, so I thought I’d provide some thoughts.

Before I do, let me take a victory lap.

On August 21, 2020, I wrote an article teaching readers how to compute survival rate of those infected with the disease by using New York data. At the time, I think my estimates seemed overly optimistic to most people.

However, on September 10, 2020, the CDC itself came out with something similar to what I had written.

In fact, their numbers are a little more optimistic than mine, reflecting a nationwide estimate and not just New York. Here is a comparison; you can see we are very close for ages 49 and under:

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So, how does this compare to the flu?

Well, the main difficulty is that people typically aren’t tested for flu antibodies to see if they had it, while there is a massive effort underway to understand who has had Covid-19.

For example, you, the reader have probably already had the flu in your life. Are you going to get tested to see if you had it in the last 12 months but were not symptomatic? And, if so, how reliable would such a test be?

But, you the reader, probably will know if you have covid-19, because you will likely have a blood test sometime in the future (if you haven’t already) to assess if you should get vaccinated.

So, given that you will find out if you had Covid-19, and you probably will find out if you have symptomatic flu, but probably not asymptomatic flu, how do your chances of survival compare: a) COVID-19 if you are infected vs b) the flu if you have symptoms?

I have already shown you the survival rate for COVID-19, so all we need is the survival rate for symptomatic flu. To calculate this, look up the chance of death for flu if you have symptoms.

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Calculate survival rate by comparing the deaths to those with symptoms and the changing it from a death rate to survivor rate by performing 1-X.

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Next, simply compare this survival rate to the Covid-19 infected survival rate.


You can do the same thing for the 2017-2018 flu year.

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You can also do it for the 2019-2020 estimate of flu.

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As you can see, if you are 49 years old, or younger, and you have Covid-19 (symptomatic or asymptomatic), your chances of death are not materially different than if you have symptoms of the flu.

For those aged 50-69, the difference is noteworthy, but also note that the flu age group is 50-64, whereas the Covid-19 age group is 50-69. There may be a big difference for those age 65-69 with less of a difference for ages 50-64.

And, there is a larger difference for those aged 70 and older.

94.6% survival rate vs 99.2% survival rate is noteworthy. Perhaps the improving treatment protocols will narrow this gap in the future.

Asymptomatic Flu

Everyone who reads this article asks about asymptomatic flu. Since we don’t really know how much asymptomatic flu actually occurs, the only thing I can do is provide estimates.

If we assume 16% of flu cases are asymptomatic, the numbers become (which probably doesn’t change any conclusions you have made in reading this article):

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If we assume 75% of flu cases are asymptomatic (meaning there are 4X more cases–note this is an update to my article), then the numbers become.

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I provide more details in the appendix.

I also think it is worth reiterating that a survival rate of 94.6% vs. a survival rate of somewhere in 99% range (the survival rates shown for 70+ years) is a pretty big difference. If you switch it back to death rates, we are saying about 5% of people who are over 70 who get covid-19 will die but only about 0.2% to 0.9% of people over 70 who get the flu will die.

On the other hand, people often believe it is a “death sentence” for older people who get Covid-19. That is not a valid belief and will become less and less so as treatments improve.

With regards to the comparative risk among individuals in the other age brackets, I will let you draw your own conclusions.

End of article.


Appendix / Additional Thoughts

1) Asymptomatic flu.

You may be wondering how many people are asymptomatic with regards to the flu. I’m not sure if it is relevant. You have likely already had the flu in your life. Having asymptomatic flu simply means you got it again but didn’t notice. (This is different than the Covid-19 scenario–you have not had it in the past, and if you have it asymptomatically, you likely WILL know you had it when taking a blood test prior to being vaccinated.)

I found this to be the best summary of available data, and as you can see the results are so wide I did not know how to apply them to analysis. The paper appears to be saying that estimates range from 4% to 28%, 0% to 100%, and 65% to 85%. Seeing the wide array of estimates and knowing that all that it means is that you got it again but didn’t notice, I abandoned trying to incorporate asymptomatic flu data into my main article but provide some what-if analysis at the end.


We conducted a systematic review and meta-analysis of published estimates of the asymptomatic fraction of influenza virus infections. We found that estimates of the asymptomatic fraction were reported from two different types of studies: first, outbreak investigations with short-term follow-up of potentially exposed persons and virologic confirmation of infections; second, studies conducted across epidemics typically evaluating rates of acute respiratory illness among persons with serologic evidence of infection, in some cases adjusting for background rates of illness from other causes.


Most point estimates from studies of outbreak investigations fell in the range 4%–28% with low heterogeneity (I2=0%) with a pooled mean of 16% (95% CI: 13%, 19%). Estimates from the studies conducted across epidemics without adjustment were very heterogeneous (point estimates 0%–100%; I2=97%), while estimates from studies that adjusted for background illnesses were more consistent with point estimates in the range 65%–85% and moderate heterogeneity (I2=58%).

2) How many people get the flu in a given year?

I found this to be a good source of info. It is saying that about 9% of people get it each year, except people over age 65 have a lower rate of infection at about 4%. The overall average is about 8%, which means the average person will experience symptoms every 11 to 12 years (even though we have a widely distributed vaccine program).

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3) What was the survival rate in a given age for older people prior to Covid-19?

In the article above, I demonstrated that the CDC says the survival rate for someone age 70 or higher is 94.6%, meaning 5.4% die.

You may be wondering, what percentage of people age 70 or higher die in a given year due to age or other causes not related to Covid-19. I present the table below which shows the death percentage and the survival percentage by age for the USA in a given year computied using 2017 data. For males, living a year at age 80 is more dangerous than getting COVID-19 for the age group of 70+. The equivalent benchmark for females is age 82.

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Finally, the end. BTW, if you read this far and enjoyed this information, please consider reposting it while you still can!

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