On coronavirus vs the seasonal flu

Let me preface this post by making clear that COVID-19 isn’t the flu. It seems to spread much faster, is likely more fatal, and clearly can wreak more havoc on hospitals. That said, for the purpose of establishing some perspective, I do think it’s sometimes helpful to compare something novel to something familiar, especially in a time of crisis and panic.

To that end, I’ve pulled and analyzed data from the US National Center for Health Statistics, a division of the CDC, which conveniently reports weekly statistics on COVID-19, influenza, and all-cause fatality in the US by age range.

My goal is to leverage my background in market research and statistics to quantitively compare one’s odds of dying from a COVID-19 infection vs the seasonal flu by age range. I hope that this helps provide a bit of sanity in what feels like an insane world.

What’s nice about this analysis is that I didn’t need to estimate how many new COVID-19 or seasonal flu infections and fatalities might occur, because all that matters for this analysis is the relative distribution of fatalities across age ranges at different Infection Fatality Rate (IFR) scenarios.

Since we don’t yet know the IFR for COVID-19 (for the flu it’s 0.1%) I provided various IFR scenarios from 0.1% to 0.5%, which seems to be a probable range based upon the latest published serological population study results. It’s also worth noting that IFR can vary a lot by geography, since demographics, underlying health conditions, smoking rates, air pollution, hospital quality, and more can influence it. Some cities will end up with lower or higher IFRs than others.

If you compare the population fatality rates of the seasonal flu to the population fatality rates of COVID-19 by age category, an interesting phenomenon emerges: Assuming the same Infection Fatality Rate (IFR), the distribution of these fatalities across age ranges is nearly identical, and if you assume that COVID-19 has a higher fatality rate, they simply increase linearly in each age range.

You can see my work here.

The dotted blue line is the flu at 0.1% IFR and the other colored lines are COVID-19 at various IFR scenarios. Notice how the blue dotted line is nearly identical to the red line, which is COVID-19 at a 0.1% IFR.

One key implication is how much more worried you should be about COVID-19 than the flu is an exact function of how much higher its IFR turns out to be, regardless of your age. In other words, if COVID-19’s IFR turns out to be twice as high, you should be twice as worried no matter your age.

Another key implication is that both the flu and COVID-19 fatality risk increase exponentially with age, much more so then I believe most people realize. To illustrate, here are the fatality odds of COVID-19 by age group at each IFR scenario above, based upon the CDC data:

Only the 0.1%, 0.3%, and 0.5% scenarios are labeled for legibility

These numbers show how many people in each age group would need to get infected with COVID-19 before we’d expect one death statistically, based upon currently-reported CDC fatality data. For example, at the 0.3% IFR scenario, we see that:

If any grandparents are worried about their grandchildren dying from COVID-19, they really shouldn’t be. And while grandparents themselves face much higher risk of COVID-19 fatality, it may be only 2x or 3x higher than the flu.

Note that for the sake of simplicity, I didn’t account for the variable of underlying health conditions, but healthier people at all ages have a lower fatality risk than above, and less healthy people have a higher one. I also didn’t account for gender, but will note that COVID-19 seems to be more dangerous for males than females for some reason. Other variables that also seem likely to affect individual risk include smoking behavior, weight, cardiovascular fitness, psychological stress levels, genetics and more.

When thinking about these COVID-19 fatality odds, remember that getting older is quite dangerous in general. From the same CDC data, here are the fatality odds for “all causes” by age range over this ~2 month reporting period:

So for someone my age, even though getting infected with COVID-19 might give me a 1 in 2,063 chance of dying at a 0.3% IFR, I already had a 1 in 2,608 chance of dying from something over this time period anyway. So while my fatality risk could almost double if I’m infected, it wasn’t that high to start.

Also note that 1) this increased fatality risk is temporary — once my infection is over, it will return to baseline, and 2) it’s really more deterministic than these probability statistics imply… most people will definitely recover and some will definitely not depending on their risk factors (i.e., it’s not a Vegas-style roll of the dice). The ‘unlucky’ 1 in 2,063 person in my age category who doesn’t recover is — by definition — the least healthy when it comes to COVID-19 fatality risk.

Another interesting way of thinking about COVID-19 vs seasonal flu risk is equating the former to each year one doesn’t get vaccinated for the latter. For example, if COVID-19 is 3x as fatal as the seasonal flu at any given age, then getting infected with COVID-19 carries equivalent risk as choosing not to get vaccinated for the flu for 3 years in a row (assuming 100% immunity per year for the flu shot for simplicity)

My intention here is arm you with data, logic, and statistics when making decisions that affect your physical and mental health, and those of your loved ones. In a hyper-political and hyper-sensationalized world, this is more important than ever.

Techie and investor. Founder at Rebel Fund and previously Pioneer Fund. Chairman of Infosurv/Intengo and CrowdMed (YC W13). Former Bain consultant. Data nerd.

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