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Is it really true that “the U.S. death rate in 2020 was the highest above normal since the early 1900s—even surpassing the calamity of the 1918 flu pandemic”?

tl;dr. No, it’s not true. The death rate increased by 15% from 2019 to 2020, but it jumped by 40% from 1917 to 1918.

But, if so, why would anyone claim differently? Therein lies a tale.

A commenter pointed to a news article with the above graphs and the following claim:

The U.S. death rate in 2020 was the highest above normal since the early 1900s — even surpassing the calamity of the 1918 flu pandemic. . . .

In the first half of the 20th century, deaths were mainly dominated by infectious diseases. As medical advancements increased life expectancy, death rates also started to smooth out in the 1950s, and the mortality rate in recent decades — driven largely by chronic diseases — had continued to decline.

In 2020, however, the United States saw the largest single-year surge in the death rate since federal statistics became available. The rate increased 16 percent from 2019, even more than the 12 percent jump during the 1918 flu pandemic.

Our commenter wrote:

If one takes the “normal” death rate to be that of the year prior to a pandemic and one assumes that the total population doesn’t change all that much from one year to the next, then this sub-headline seems to be seriously incorrect. If one eyeballs the “Total deaths in the U.S. over time” chart in the article and then compares the jumps due to the 1918 pandemic and the 2020 pandemic, it seems pretty clear that the percentage increase in the number of deaths (and thus the death rate, assuming a roughly constant population) from 1917 to 1918 is much greater than the percentage increase from 2019 to 2020. The jump from 1917 to 1918 looks to be around 40% while the jump from 2019 to 2020 looks to be around 15% (based on measurements of a screenshot of the graph using Photoshop’s ruler tool).

I was curious so I took a look. The above graphs include a time series of deaths per 100,000 and a time series of total deaths. (As an aside, I don’t know why they give deaths per 100,000, which is a scale that we have little intuition on. It seems to me that a death rate of 2.6% is more interpretable than a death rate of 2600 per 100,000.) Here’s what they have for 1917 and 1918 (I’m reading roughly off the graphs here):

1917: 2300 deaths per 100,000 and a total of 1 million deaths
1918: 2600 deaths per 100,000 and a total of 1.4 million deaths.

This is an increase of 13% in the rate but an increase of 40% in the total. But I looked up U.S. population and it seems to have been roughly constant between 1917 and 1918, so these above numbers can’t all be correct!

According to wikipedia, the U.S. population was 103 million in 1917 and 1918. 1 million deaths divided by 103 million people is 1%, not 2.3%. So I’m not quite sure what is meant by “death rate” in that article.

The problem also arises in other years. For example, the article says that 3.4 million Americans died in 2020. Our population is 330 million, so, again, that’s a death rate of about 1%. But the 2020 death rate in their “Death rate in the U.S. over time” chart is less than 1%.

I’m guessing that their death rate graph is some sort of age-adjusted death rate . . . ummmm, yeah, ok, I see it at the bottom of the page:

Death rates are age-adjusted by the C.D.C. using the 2000 standard population.

Compared to 1918, the 2000 population has a lot of old people. So the age-adjusted death rate overweights the olds (compared to 1918) and slightly underweights the olds (compared to 2020). The big picture here is that it makes 1918 look not so bad because the 1918 flu was killing lots of young people.

Also, one other thing. The note at the bottom of the article says, “Expected rates for each year are calculated using a simple linear regression based on rates from the previous five years.” One reason why 1918 is not more “above normal” than it is, is that there happens to be an existing upward trend during the five years preceding 1918, so the implicit model would predict a further increase even in the absence of the flu. I’m not quite sure how to think about that.

Anyway, the answer to the question in the title of this post is No.

Age adjustment can be tricky!

P.S. This is just a statistical mistake, but I wonder if there’s a political component too. There seems to be a debate about whether coronavirus is a big deal or not, epidemiologically speaking. I think coronavirus is a big deal: an increase of 15% in the death rate is a lot! But for some people, that’s not enough; it has to be the biggest deal of all time, or at least bigger than the 1918 flu. Hence you get this sort of headline. I have no reason to think this is deliberate political manipulation; rather, it’s just that when people make a mistake that yields a result that aligns with their preconceptions, they don’t always notice.

Or maybe I just made a mistake and I’m misunderstanding everything here. Could be; it’s happened to me before.


  1. David W Hogg says:

    I agree that it’s hard. Related naive question: If the population isn’t growing fast (and I think it’s not) and if the death rate is 1 percent, is the mean lifespan 100 years? Because that seems long.

    • Andrew says:


      The absolute growth rate of the population doesn’t have to be large for there to be noticeable demographic effects. Last year there were about 4 million births and 3 million deaths in the U.S. Setting aside migration, that would correspond to a mere 0.3% population increase. But it’s still a lot more births than deaths, implying that we’re far from any demographic equilibrium.

      That said, estimating yearly #births or #deaths as (1/80)*population will get you pretty close, at least by astronomer’s standards.

    • D.O. says:

      A person who dies young contributes 1 count to total deaths, but a lot of (negative) years to the average age of death.

  2. Joshua says:

    It seems likely that “normal” deaths is yhe average over the previous five years, as decribed here:

    > 2. How is excess mortality measured and who measures it?
    National statistical agencies publish actual weekly deaths and averages of past ‘normal’ deaths. For example, the Office for National Statistics (ONS) reports ‘normal’ deaths for England and for Wales as the average of the previous five years’ deaths.

  3. MARK PALKO says:

    Another reminder of how useful Wikipedia is. Probably a good time to click on the support button.

  4. paul alper says:

    Do the above graphs include adjustment for 1959 when Hawaii and Alaska became States? Not enough inhabitants to make a difference anyway?
    And, what is special about 1933? Each of the above graphs states in very light-blue lettering, “Data before 1933 do not include all states.” Should everything before 1933 be ignored?

  5. TPassin says:

    Very noticeable but not mentioned so far is the large drop in the death rate for the year after the 1918 pandemic year. Is that because those who would have died the next year instead died in the pandemic, leaving a shortfall in the following year? It looks as if the average over those two years would not be much different from the “normal”.

    • Andrew says:


      Nah, I don’t think so. I think what you’re seeing is an artifact of the data manipulation. Look at the raw data—the third graph above—and you don’t see a dip in 1919. The number of deaths does drop a bit in 1921, but not nearly as much as it jumped in 1918.

      • Kaiser says:

        Another “irreconcilable” difference between 1918 and 2019! Every excess death is ultimately an accelerated death. Because the current pandemic affects mostly older people, those deaths are likely moved forward by only a year or a few years. So some kind of reversal will be seen. We may even see negative excess deaths by other diseases after the pandemic. This effect would not be seen after 1918 if that pandemic killed a lot of younger people.

  6. Unanon says:

    I’m trying to understand the critique here. The age-adjustment is an attempt to assess the overall (excess) death rate for the 1918 flu vs 2020 COVID for an identical–in terms of age distribution–population. A population most readers would be familiar with is a current, or recent one. It may not make sense to compare naive death rates from 1918 vs 2020, because the populations were very different. The comparison attempts to answer the question: if the (yr 2000) population experienced the 1918 flu, and had similar within-age strata death rates compared to 1918, would the overall death rate be higher or lower than if the same (yr 2000) population experienced COVID?

    I guess they could have done an age-adjustment the other way: adjust to the 1918 population distribution? And the conclusions from this age adjustment would be very different–the death rate ratio between flu and COVID would be different (greater, I guess?). Maybe this is the critique, but I’m not sure how relevant this sort of analysis would be. The mortality ratio would differ across any number of standard populations used to perform the age adjustment. But this would be true for any age-adjusted comparison.

    It’s very common to report incidence and mortality rates per 100,000. Not all numerators are in the thousands, to make the quotient tidy. For example, colorectal cancer incidence rates for 20-49 year-olds is about 7 per 100,000. This seems easier to interpret than 0.007%.

    • Andrew says:


      I agree that there are difficulties in comparing raw death rates from 1918 and 2020. But nobody’s talking about doing that. The point is that we’re comparing 1917 to 1918 and 2019 to 2020. Deaths went up by 40% from 1917 to 1918 but only 15% from 2019 to 2020. No disagreement that a 15% increase is huge—but it’s still a lot smaller than 40%. Unless I’m misunderstanding something in the analysis, the only way they could get that 40% down to 12% is by reweighting the data so as to give a huge weight to the over-75 population, of which there were not so many back in 1918.

      I think it would be more accurate to say that the death rate increased by 15% from 2019 to 2020, which is a lot, but not as much as the increase in death rate from the 1918 flu.

      • Martha (Smith) says:

        Andrew said,
        “The point is that we’re comparing 1917 to 1918 and 2019 to 2020. “

        Might this be problematical because WW1 was going on in 1917 and (most of) 1918?

        • Rahul says:

          To quantify an event doesn’t it make much more sense to compare a point value to a baseline?

          Wouldn’t it make more sense to compare the flu spikes to say the average of the past decades!

        • confused says:

          When I saw this claim (and assumed it to be true if misleading) I assumed the 1917 numbers must have been hugely inflated by WWI.

          If the increase really was 40% from 1917 to 1918, yeah, it might have been even more than that “above baseline”.

          • Ryan S says:

            Although the U.S. declared war in early 1917, it took almost a year to mobilize its military and most American soldiers did not enter combat until 1918. I have not been able to quickly find casualties by year; there were around 116,000 U.S. military deaths total and I would guess the vast majority were in 1918 (which probably includes deaths from influenza).

      • Unanon says:

        “Unless I’m misunderstanding something in the analysis, the only way they could get that 40% down to 12% is by reweighting the data so as to give a huge weight to the over-75 population, of which there were not so many back in 1918.”

        I guess maybe I’m misunderstanding something! Isn’t that exactly what was done, and what was meant by: “Death rates are age-adjusted by the C.D.C. using the 2000 standard population?”

        Here is the age-adjustment process and rationale:

        I tend to agree with CDC that comparisons are more meaningful when death rates from different eras are compared to the same (standard) population. Part of the reason this is done is to create less confusion in mainstream reports–not more!

        • Andrew says:


          I agree—but we’re not comparing 1918 to 2020. We’re comparing the 1917-1918 change to the 2019-2020 change. For that, direct comparisons suffice.

          To put it another way, it seems kinda weird for them to say that the 1918 flu wasn’t so bad because it killed lots of young people, and young people get downweighted in their adjustment. To use the 2000 population to assess the impact of the 1918 flu would be like using a modern weighting of the Consumer Price Index and then saying that inflation in 1918 was really low because the prices of computers weren’t going up at all back then.

      • Navigator says:


        From what I remember the flu strain that was ‘trending’ in 1918 was a novel virus going through a naive population, for all but those of age 74 and up (not sure about exact age). Basically, for very old folks then it was just a common flu as they had been exposed to it previously.

        It may not have been a weighting issue after all.

        When you mentioned that there was an upward trend five years prior, I couldn’t help but speculate that in the absence of vaccines (or anything else) the virus was mutating much more for a few years and finally in 1918 reached its full potential. Not unlike what covid is doing these days.

    • Steve says:

      I think the basic criticism is that when you conclusion probably depends on weighting you should look into it and comment on the (lack of?) robustness. I think deaths among 75+ dropped 10% in 1918 while deaths for people 1-44 increased by 50-150% depending on the weighting. You can’t look at that and think the weighting is irrelevant.

    • Steve Sailer says:

      It’s curious to age-adjust away some of the tragedy of the fact that the 1918 Spanish Flu tended to kill young adults, thus orphaning many small children and depriving society of the victims’ potential contributions.

      I would think that a more comprehensive comparison of the two pandemics would find that, beyond the simple death toll, the 1918 one was worse than the 2020 one due to the former striking hardest at young adults.

      For some reason, I almost never hear the current pandemic discussed in terms of Quality-Adjusted Life Years lost or similar standard measures.

      To see who the covid pandemic targets worst, I occasionally check in on Wikipedia’s List of COVID-19 Deaths:

      This seems to be a list of people prominent enough to have their own Wikipedia page: not a high bar, but high enough that I can look up information about the American fatalities, such as, say, baseball players.

      Generally, the current death toll has fallen on people past the primes of their careers. I suspect 1918 was the opposite: we lost a lot of people who would have done something noteworthy with their lives if they hadn’t died in 1918.

      • Andrew says:


        I agree that a plague that kills younger people is worse, and I think this has been covered a lot in the news media, with much discussion of the fact that Covid-19 kills mostly old people, whereas the 1918 flu killed younger people. Maybe the reason this is not usually expressed in qualys is that the differences are so clear.

        • Steve Sailer says:

          I’ve seen very little discussion of the loss of what we might call “social contribution” from the two epidemics.

          In 1918, lots of people in young families that looked forward to decades of income from the head of the household suddenly found themselves to be widows or orphans.

          In contrast, one possible contributing factor to why so many people at the moment seem to have so much cash to spend on houses, bitcoin, Non-Fungible Tokens, fireworks, and the like could be that more people have gotten their inheritances over the last year than normal. Heirs who expected most of their potential inheritances to be dissipated by the cost of keeping aged loved ones in assisted living facilities have suddenly found themselves with unexpected windfalls.

          I’m sure the government’s vast concoction of money is the main reason for these various bubbles, but excess inheritances may play a role as well.

        • Rahul says:

          It would be interesting to see an actual mortality distribution by age cohort curve of covid compared to the Spanish flu.

          I hear this hypothesis a lot but haven’t seen the actua comparison.

  7. Joshua says:

    > This is just a statistical mistake, but I wonder if there’s a political component too. There seems to be a debate about whether coronavirus is a big deal or not, epidemiologically speaking. I think coronavirus is a big deal: an increase of 15% in the death rate is a lot! But for some people, that’s not enough; it has to be the biggest deal of all time, or at least bigger than the 1918 flu.

    I’m assuming you know this, but there’s a political aspect more broadly – even if I wouldn’t assume anything politically focused about this article specifically.

    Early on in the pandemic, one side in the COVID wars tried to say the death counts were inflated and in reality the pandemic was no big deal. To refute that argument, the other side pointed to excess deaths as a way to make the case that if anything, the “COVID deaths” count was an undercount.

    More recently, as excess mortality anomolies have tended towards leveling out over the course of yhe pandemic’s full trajectory – particularly in the COVID wars battleground of Sweden – now the “no big deal” side is pointing to excess deaths to support their argument that Sweden did just fine and it’s no big deal in other countries where excess deaths have stabilized.

    Personally, I think that excess deaths is a pretty limited metric for measuring the impact of the pandemic – just like straight up COVID deaths counts. P-scores and Z-scorrs are somewhat more informative but even there, there’s so much uncertainty (e.g., what adjustments should be made for the drop in flu deaths or fewer deaths because of less mobility or more deaths from overdoses, etc.?), and anyway, what about all the hospitalizations and illnesses and lost productivity and medical costs, and the cost of stress to medical workers, and who the hell knows whether or how to attribute specific costs to the pandemic itself or the interventions implemented to mitigate the pandemic?

    • Steve Sailer says:

      Interestingly, during the first wave of March-May 2020 in the U.S., total excess deaths substantially exceeded official COVID deaths, suggesting, contrary to the argument that the public health establishment was inflating the death counts by including people who died with rather than from COVID, that the pandemic was worse than the official stats suggested. In the early weeks, apparently, thousands died from COVID without the novel disease being recognized for the official records.

      After the first wave, this phenomenon largely went away.

      • confused says:

        Is this because systems weren’t ready for it in March-May (but they were in later waves) so there was much more misdiagnosis, or is it because deaths weren’t so much “misdiagnosed” as “reporting was massively delayed” and the ‘accounting’ has now caught up?

  8. jim says:

    Maybe I’m missing something, this seems to simple to be overlooked:

    Suppose we had a pandemic in 1851 when there was virtually no effective healthcare. It seems obvious that, because many more people died of common diseases and conditions that aren’t deadly today, that the increase in deaths, excess deaths, and any kind of death rate or death statistic due to a pandemic would be much smaller, since the background death rate is much higher.

    So it wouldn’t surprise me at all if, with the generally very good health care we have today, a pandemic would cause a much larger jump in mortality that the same pandemic a century ago.

    What did I miss?

    • Andrew says:


      I guess that could happen in theory, but what actually happened was that the death rate increased by 40% from 1917 to 1918.

      Another way of looking at it is that epidemics of infectious disease were sweeping the world all the time back then; this was part of the background level of deaths. The 1918 flu was particularly bad in that it killed all sorts of people who weren’t dying for other reasons.

      • Adam says:

        In a story that is ultimately comparing the deadliness of two diseases, to Jim’s point, it does seems relevant to consider healthcare effectiveness.

        We wouldn’t expect the death rate to increase by 40% from 1917 to 1918 if all of today’s medicine, technology and infrastructure was in place. Obviously, the story would need other experts to assess primary cause of death during the Spanish flu and current treatments if we were going to add that aspect to the tale.

        I think at the end of the day, the comparison is apples and oranges. At some point, data analysis will need to be done to make some semblance of a sensical comparison. Some will be better than others, but all will be fall short. Yes, they are round, yes they are edible, but an orange is not an apple.

        • Andrew says:


          I agree. There are all sorts of analyses that could be done. I just don’t think they should have a headline, “the U.S. death rate in 2020 was the highest above normal since the early 1900s—even surpassing the calamity of the 1918 flu pandemic,” when actually the death rate rose by 15% in 2020, compared to rising by 40% in 1918. I really don’t like that sort of misrepresentation of the facts. I can only assume it was accidental—they just had these CDC numbers and didn’t think them through—but I don’t like this sort of statistical mistake, even when it’s not on purpose.

          • Michael Nelson says:

            They clearly thought it through, and probably over-thought. They might argue that their analysis, tautologically, defines what they mean by death rate, and that their definition is somehow more useful or relevant or interesting that your straightforward definition. But then they’d have to defend not using the straightforward definition, which they don’t, at least not adequately. Perhaps the best version of the article answers the question with “It depends on what you mean by death rate.” Then it shows the straightforward interpretation, a couple other interpretations, why each might contribute some insight to the conversation, etc. Their biggest sin, in fact, is in presupposing that there is a single, context-free definition with an associated, natural choice of analysis. They need to put a (figurative) uncertainty interval around that headline.

    • Michael Nelson says:

      If I understand your point, one reason we can ignore baseline death rate is the limiting nature of the function of death rate. If death rate is higher to begin with, then yes, many people who die of the new virus would have died anyway. That number of people is essentially a constant from one year to the next, assuming relative stability. But the number of new deaths–viral deaths of people who otherwise would’ve lived–is an exponential function, because viruses spread exponentially. In big O notation, you’d drop the constant, so what you call a “much larger jump” turns out to be negligible–which would be what you’re missing.

      Also, individual differences make the comparison (as others have said) apples and oranges. For example, the Spanish flu and COVID have their highest death rates in very different populations–kids and elderly, respectively–with very different (non-pandemic) life expectancies.

      • confused says:

        >>For example, the Spanish flu and COVID have their highest death rates in very different populations–kids and elderly, respectively

        I don’t think this is quite right. The really weird thing about the 1918 flu is that it had a *3-peaked* mortality curve: infant / ~30s / very old. I don’t know that it was necessarily highest death rate among the youngest. But that prime-of-life peak is *extremely* odd.

  9. Dale Lehman says:

    The “below normal” deaths are also worth exploring, 1919 in particular. I do think that having several graphs of the raw data would be better than burying the data in the “age adjusted” rates. The age distribution of the population has shifted considerably – certainly due to aging and health improvements, but also with some big impacts of young people dying in the 1918 flue and WWI and WWII. So, showing age shifts and death rates in separate graphs would provide a clearer picture than what is shown.

    • Brent Hutto says:

      One could also, of course, present age-stratified death rates.

      • Andrew says:

        Or you could renormalize to the 1918 age distribution, in which case the 2020 coronavirus would look pretty trivial.

        • Kaiser says:

          So glad to see this discussion here. I’ve been trying to explain this issue in the context of regression adjustments. It’s the same problem. It is supposed to answer the question of “what if factor X did not matter”. Here, age adjustment is supposed to answer “what if age did not matter”. Of course, we just showed that making age not matter requires assuming some standard age distribution which creates the problem described here.
          A recent example, similar to this, is how CDC estimates real-world vaccine effectivness – they said they did “study site adjustment”, which basically means both groups are evaluated under a standardized distribution across study sites. They only report the site-adjusted average VE. The problem was unvaccinated people were vastly more concentrated in sites that had the highest infection rates.

        • confused says:

          Yeah. I think the much older populations of the modern era US/Europe make COVID especially hard-hitting.

          Although many places in Latin America have been hit quite hard – OTOH, say, Brazil’s population isn’t really that young in historical terms.

  10. John Thacker says:

    “I think coronavirus is a big deal: an increase of 15% in the death rate is a lot!”

    Yes, and it gets even stranger with some other polling because most people’s numerical intuitions don’t work quite right, especially for small numbers or rates. If you ask people “what percentage of people who get COVID-19 will be hospitalized/be admitted to the ICU/die from it?” then on average people who have the correct qualitative understanding that it’s really bad will estimate far too large numbers, and the average person who gets the numbers correct will have a poor qualitative understanding and think it’s not that bad.

  11. Steve says:

    I suspect the reason for showing deaths per 100,000 is that this is traditionally how mortality tables are built. I couldn’t tell you why that is, or why NYT didn’t convert to a %, but convention in mortality data has always been to show deaths per 100,000.

  12. chrisare says:

    Why would you weight old people more than young people? Am I missing something? Shouldn’t it be the opposite, at least according to the sensible (IMO) logic of DALYs and QALYs?

  13. zbicyclist says:

    “expected rates for each year are calculated using a simple linear regression based on rates from the previous five years”

    Buried deep in the fine print, rather than highlighted. We might take a multiverse approach to this and imagine how many possible ways one could determine the expected rate — and how many of them would be worthy of being plastered at the top of the NYT webpage.

    One of the quirks of this curious method is that big dip in 1919 (gray bar). That makes it look like 1918 just had premature deaths that were made up with lower mortality in 1919, which is not the case.

    • Does this include war deaths? Because WWI ended Nov 1918 so we’d expect some reduction in mortality in the years following.

      • zbicyclist says:

        We’d anticipate a reduction in mortality, but not relative to “expectations” in a non-war, non-pandemic year. Those Americans dying in war are primarily young men who would be expected to otherwise not do much dying.

        Again, this depends on how you define “expectations”. For 1919, they seem to be fitting a linear regression for the 5 years 1914-1918. We didn’t enter the Great War until April 1917, so there’s going to be a big upward trend from 1914 to 1918 due to war and pandemic.

        • NU says:

          It looks like 1918 was excluded from expectations: “Expected rates for each year are calculated using a simple linear regression based on rates from the previous five years. The death rate in 1918 was excluded when calculating expected rates.”

  14. Mark says:

    I’m perplexed by a couple of things. First, does the death rate show loss of life for the various wars? I cannot discern any noticeable spikes for WWI and WW2, etc. Maybe they didn’t really harm the US population. Russia certainly didn’t experience this nor did Germany WWII.

    Be interesting to look at expected versus actual per trend.

    Be interesting to estimate estimated impact on GDP and GDP per capita. How would a pure sociopath look at the data? I’m fascinated by looking at data as dispassionately as possible and being honest about it. Not easy but valuable IMO.

  15. Russ Lyons says:

    Thanks for having this discussion, Andrew. I had noticed the screwy figures a couple of days ago and intended to do my own analysis, but this saved me a lot of time. BTW, the comments in the NYT on this article have some debate about the meaning of these graphs; it is easy to see why.

  16. Josh says:

    Very disappointed in the New York Times for this one. I had seen the headline without look at the entire article and was definitely misled. I completely agree with you Andrew that the relevant comparison is the percentage change (adjusted for age).

    • Andrew says:


      I doubt they did it on purpose. It’s just easy to get confused by statistical adjustments. (Remember, it was age and sex adjustment of death rates that tripped up a Nobel-prize-winning economist a couple years ago.) I do think, though, that because the result fit their existing story, they were less careful about checking it.

  17. Jonathan Carmel says:

    What I think is interesting is the huge negative excess death rate in 1919. This is not what one would expect from a disease that killed younger people. With COVID we had a large number die from the disease that “had one foot in the grave and the other on a banana peel.” The data listed on the CDC website is incomplete yet for excess deaths in the last 1-8 weeks according to the site. I believe that we have pulled forward a number of deaths that we would have seen in the next 12-36 months anyway.

    • Andrew says:


      There was no “huge negative excess death rate in 1919”! That statement, derived from the top graph above, is an artifact of some weird statistical adjustment they were doing to make that graph. Look at the third graph above, which shows actual deaths. In 1919, deaths returned roughly to the 1917 rate.

  18. Tim says:

    Why would anyone waste time on that NYT article?

    • Andrew says:


      It’s easy to say in retrospect that this newspaper article was wrong. But the point is that most people would just look at the headline or the first graph and not realize what was going on. That was the point of my post! And we can’t ignore the news in general, as this is how we learn a lot about the world. The existence of many bad news articles should not be taken as a reason to disbelieve everything in the newspaper!

      • Brent Hutto says:


        You probably can’t afford to ignore the news in general as your work has so much to do with politics and current events.

        But I assure you, it is possible to lead a very healthy and well-adjusted life by ignoring not only the NY Times but approximately 99.9385% of the rest of the “news” and news media. And social media. I heartily recommend it, in fact!

    • Andrew says:


      Given that there was a jump of 15% in deaths this past year, I guess the Johns Hopkins article really was wrong. I don’t know whether the university should’ve retracted it or just put a big watermark on it saying it was in error, but based on your link above, it seems that it really was being used to support false and dangerous inaccuracies about the impact of the pandemic, so it’s good they did something about it so that people didn’t think Johns Hopkins was endorsing these false claims.

      The link you gave above is problematic. On the plus side, the post has an update at the end from an expert from the National Center for Health Statistics saying why the retracted article was wrong. On the minus side, the post begins with the ridiculous statement, “Conventional wisdom is that COVID-19 has caused thousands of deaths in the United States and nearly 1.5 million worldwide.” I mean, sure, conventional wisdom says that because it’s true. OK, now the numbers were higher but that was in November 2020. What’s ridiculous is calling this “conventional wisdom” as if we’re supposed to disagree with it. The usual way of writing the sentence would be, “COVID-19 has caused thousands of deaths in the United States and nearly 1.5 million worldwide.” We don’t say, “Conventional wisdom is that a water molecule is composed of two hydrogen atoms and one oxygen atom.” It’s just a fact.

    • JFA says:

      Here’s a reply I wrote to someone else promoting Brand’s shoddy work (I saved the reply because people keep referencing it):

      Briand is a hack who didn’t think Covid caused any excess deaths. Her story was that there were no excess deaths in 2020. Her story was that there was a decrease in the number of deaths by cause group that didn’t have Covid-19 that nearly perfectly matched the increase of death certificates that had those cause groups listed along with Covid-19.

      First, the causes that did not include Covid-19 either remained flat or increased relative to previous years, so there were no decrease in those cause groups (see here:… click on the “Weekly Number of Deaths by Cause Group” toggle and then update dashboard).

      Second, anyone with eyes could see that the total number of deaths was increasing and coincided with Covid-19. In fact, if you plot the number of deaths from Covid-19 and the number of excess deaths, they are highly correlated, even within state (lockdown or no lockdown). She says: “No evidence covid-19 creates any excess deaths. Total death numbers are not above normal death numbers”.

      Again, from the earliest days, the number of deaths were not normal and anyone with eyes could see that the total number of deaths had increased. Any claim to the contrary is absurd. The lower bound estimate on excess deaths for April 2020 is ~70k. Not sure how that squares with no excess deaths and covid deaths being offset by a decrease in other deaths (which didn’t actually happen… just go look at the data yourself).You keep on saying that the mortality rate just bounces around. I have included the data since 2010 below. Mortality rate steadily increased from 799 per 100,000 (0.799 percent) in 2010 to 870 per 100,000 in 2019. Then in 2020, the mortality rate was 1014 per 100,000.Average percent increase in the number of deaths per year from 2010 to 2019 was 1.6%. Deaths increased 17.6 percent in 2020 relative to 2019. It was a 16.6% increase in the mortality rate. There was nothing normal about the death rate in 2020.

      Year Deaths Population Mortality Rate % Change in deaths
      2010 2,468,435 308,745,538 800
      2011 2,515,458 311,591,917 807 1.9
      2012 2,543,279 313,914,040 810 1.1
      2013 2,596,993 316,128,839 822 2.1
      2014 2,626,418 318,857,056 824 1.1
      2015 2,712,630 321,418,820 844 3.3
      2016 2,744,248 323,127,513 849 1.2
      2017 2,813,503 325,100,000 865 2.5
      2018 2,839,205 327,200,000 868 0.9
      2019 2,855,000 328,200,000 870 0.6
      2020 3,358,814 331,000,000 1015 17.6

      One big issue with Briand’s analysis (which went through the end of September 2020) is that she bases her expectations of the April 2020 peak on the December 2017/January 2018 peak, which makes absolutely no sense. When she asks “Where have all the heart attacks gone?” She highlights Yr4Wk46 – Yr5Wk12 (winter 2017 – early spring 2018) and compares it to Yr7Wk13 – Yr7Wk31 (spring 2020 – midsummer 2020). Well December 2017/January 2018 was the peak of deaths from diseases of the heart, just like every other December/January that she presented data for. And 2020 was following the same trend until… guess what… Covid hit. Why on earth would it make sense to compare winter deaths in one year to spring deaths in another year. What she has actually highlighted is how different deaths were in 2020 but somehow sold it as business as usual.

      Here’s her working paper: Here’s a representative paragraph:

      “March 24th 2020 is the date the new International Classification of Diseases (ICD) code issued by the World Trade Organization (WHO) for COVID-19 was introduced and implemented in the United States. Up until then, the CDC’s deaths data provided a treasure trove of information, with easily recognizable seasonal patterns and the U.S. weekly deaths were following those historical patterns, exactly. On week ending March 28th 2020, the U.S. weekly deaths sharply departed from them. Are the unfamiliar patterns seen since due to COVID-19 or the reoccurring fear campaigns?”

      You know… I’m gonna bet that the change in seasonal death patterns was due to the pandemic spread of a virus that increased mortality risk for the whole population and that it was not due to the introduction of a new ICD-10 code.

      • Diana Petitti says:

        Death data for the United States for the period 1890 through 1938 are available at

        In the period before 1933, not all states registered deaths nationally. During the period 1914 through 1918, several states began reporting deaths for the first time. Kansas was added in 1914; South Carolina in 1916; Tennessee and Hawaii in 1917; Illinois, Louisiana and Oregon in 1918. States “joined” the national registration piecemeal from then on. Because of the incompleteness of death reporting to the national system, the number of deaths in the years leading up to 1918 and after are not easily interpreted. Don’t know what the NYT did to address this.

        The following data on number of deaths and death rates for the four years leading up to 1918 and the three following years (1919-1921) were extracted from the 1921 report posted at the CDC/NCHS website sited above (Table C, Page 10).

        The data are as follows:

        Year N of Deaths Deaths per 1,000
        1914 898,059 13.6
        1915 909,155 13.6
        1916 1,001,921 14.0
        1917 1,068,932 14.3
        1918 1,471,367 18.1
        1919 1,096,436 12.9
        1920 1,142,558 13.1
        1921 1,032,009 11.6

        Death rates per 1,000 use denominators for the states that registered deaths in the corresponding year.

        The 1918 Mortality Report (available at the website) has an interesting analysis of mortality due to pneumonia or influenza comparing 1918 and 1915. It gives the ratio of deaths due to pneumonia or influenza comparing 1918 to 1915 (ancient epidemiology). These range from 0.8 (age 80-89) and 0.9 (age 90-99) to 22.0 (age 20-29).

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