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Covid Deaths Are Real: Rebutting Dr. Briand
I write to rebut the claims of Dr. Genevieve Briand, a senior lecturer at Johns Hopkins who holds a PhD in Economics and recently released a study questioning the Covid death statistics. The paper was subsequently withdrawn by Johns Hopkins, quite properly in my view. Dr. Briand’s analysis is deeply flawed.
Misleading and erroneous analyses like these have serious effects. It led our friend iWe to author a post yesterday titled Covid – Just A Big Hoax?, which cited Dr. Briand’s study as supporting the assertion “that the total death rates HAVE NOT CHANGED.”
This is false information. This is not entirely iWe’s fault; though everyone should be very careful about information sources at this time.
I have decided to rebut Dr. Briand’s erroneous analysis. The article summarizing her analysis is here; the Johns Hopkins explanation of its withdrawal is here, and an hour-long video explaining her results is here. My data sources and methods will be set forth in the technical note at the bottom of this post.
I. Age Distribution Analysis
The lead graph in Dr. Briand’s analysis relies upon this chart, showing weekly deaths in the US from February to September 2020:
This graph is color-coded by age category, with reported deaths of older people at the top, showing the percentage of total deaths in each age category — for example, the light blue bar at the top shows that about 30% of all reported deaths in the US have occurred among people aged 85 and up. This graph includes all reported deaths, from all causes, not just Covid.
This does not show the absence of an increase in the number of deaths. It shows that the proportion of deaths by age category was not noticeably changed by Covid. The article setting forth Dr. Briand’s analysis claims:
Surprisingly, the deaths of older people stayed the same before and after COVID-19. Since COVID-19 mainly affects the elderly, experts expected an increase in the percentage of deaths in older age groups. However, this increase is not seen from the CDC data. In fact, the percentages of deaths among all age groups remain relatively the same.
Who are these “experts”? Why would this be at all surprising?
We know that Covid mostly kills old people. What about other causes of death? Do you think that other causes of death affect mostly young people? Of course not. Most people who die are old, thank God. The alternative is for the young to die in large numbers, which would be tragic. Something’s gotta get us all in the end.
But to rebut Dr. Briand’s claim requires empirical evidence, so I consulted two sources: (1) the CDC page for Covid deaths, which reports deaths by age category for (approximately) February-November 2020, and which lists both Covid-involved deaths and total deaths, and (2) the CDC report on final death figures for 2017, which reports all 2017 deaths by age category. This allowed me to calculate the total percentage of reported deaths, for each age bracket, for the following 3 periods:
- All deaths in 2017
- Covid deaths in 2020 (approx. February-November)
- Non-Covid deaths in 2020 (approx. February-November)
Here is the result:
It’s hard to tell the difference between the periods, isn’t it? Unsurprisingly, Covid deaths and non-Covid deaths occur mostly among the old — roughly 30% among people aged 85 and over, another 24-27% among people aged 75-84, and another 19-22% among people aged 65-74.
Thus, we would not expect Covid to significantly change the distribution of deaths by age category.
Remember the quote from the article presenting Dr. Briand’s analysis: “[E]xperts expected an increase in the percentage of deaths in older age groups.” Again, what experts? None are cited. Their hypothesis is just plain silly. We all know that deaths occurred overwhelmingly among the old, even before Covid.
I find it both surprising and disturbing that people would be misled by such nonsense. This is the sort of ridiculous claim that a thoughtful, critical reader should immediately recognize as implausible. Proving it to be incorrect takes additional work — for example, you need to find the data on the CDC website, and you need to know how to use Excel or a similar program to analyze and graph the data.
Fortunately for you, dear reader, I happen to know how to do both of these things. :)
But seriously, the real danger is the uncritical acceptance of implausible and unsubstantiated claims. This seems particularly common when the erroneous conclusion is congenial to one’s political or moral position. Be careful about this. There is very, very bad information coming from the Leftist media, and there is very, very bad information promoted by alternative conservative sites.
II. The “Excess Deaths” Analysis
Dr. Briand’s analysis does not specifically analyze the “excess deaths” information, but the article reporting her findings claims:
Briand also noted that 50,000 to 70,000 deaths are seen both before and after COVID-19, indicating that this number of deaths was normal long before COVID-19 emerged. Therefore, according to Briand, not only has COVID-19 had no effect on the percentage of deaths of older people, but it has also not increased the total number of deaths.
This conclusion is absolute nonsense, though the first part of the first sentence is correct. The number of weekly deaths generally ranged from 50,000 to 70,000 throughout 2017, 2018, 2019, and 2020. This is immaterial. It is the sort of thing that is meant to mislead.
There is a good graph from the CDC that rebuts this claim (link here):
But perhaps you don’t trust this one. I haven’t personally verified the information, and when you look closely, it’s not actually reporting death counts. The blue bars are “Predicted number of deaths from all causes,” and if you follow the link and point to an individual data bar, it reports three numbers: “Average expected number of deaths,” “Upper bound threshold for excess deaths,” and “Predicted (weighted) number of deaths.”
I don’t think that the CDC is playing games with us. The notes explain that there is a lag in the reporting of deaths. I deduce that this particular graph uses averages to predict what the total number of reported deaths will be for each week once reporting is complete.
Also, the orange line is the “upper bound threshold for excess deaths,” which appears to be a sort of “trip-wire” for determining whether there is a serious problem. As you can see, the orange line runs quite a bit above the actual reported deaths.
I decided to so my own analysis. I was able to download data from the CDC for actual reported weekly deaths, from 2017 to 2020. The data file included both the “upper bound threshold for excess deaths” and the “average expected count.” In order to check the plausibility of the CDC’s “average expected count,” I separately calculated the weekly average deaths for 2017, 2018, and 2019, on a week-by-week basis — that is, I averaged the reported deaths for the first week in January 2017, 2018, and 2019; then for the second week in January for each such year, and so on. (One caveat — the data set did not include the first week in January 2017, for that one week, my calculated average includes only 2018 and 2019 data). Here is the result:
The red line is the actual reported deaths for each week in 2020. Note the spike starting around Week 13 — mid-March. That’s Covid. Important caveat: Recent deaths are significantly under-reported, as the data is not yet in. Do not interpret the decline at the right side of this graph as an actual decline in deaths. It is almost certainly a result of the lag in reporting.
I have two lines for the “normal death” threshold. The blue line is the CDC’s “average expected count.” The orange line is the actual weekly average for 2017, 2018, and 2019, calculated by me. As you can see, the blue line and the orange line are virtually identical, giving me high confidence in the CDC’s calculation of the “average expected count.”
The green and yellow lines are “excess deaths.” The yellow line shows the excess of actual reported deaths in 2020 compared to the CDC’s “average expected count” for each week, while the green line shows the excess of actual reported deaths for 2020 compared to the weekly average from 2017, 2018, and 2019.
This graph demonstrates that Covid is real. Its effect shows up in a sharp spike in reported deaths, starting in mid-March 2020. This is entirely in accord with Covid death figures reported elsewhere.
I performed one more calculation — my own estimate of “excess deaths,” using the green line — i.e. the increase in weekly deaths reported in 2020, compared to the average weekly death figure for the corresponding week in 2017, 2018, and 2019.
For the period from Week 12 to Week 44 — i.e. the week ending March 21, 2020 through the week ending October 31, 2020 — my calculation indicates 316,800 excess deaths. I did not include reported deaths in November because the data is evidently incomplete.
This rebuts Dr. Briand’s claim that Covid has not increased the total number of deaths in the US. That claim is demonstrably incorrect.
III. My comments
After initially taking down the article without explanation, Johns Hopkins posted an explanation, and re-posted the original article. My initial impression is to think that this response by Johns Hopkins is admirable, though on reflection, this is a sad commentary on the state of our academic and public discourse. Johns Hopkins acted properly and honorably, but this should not be surprising. This is how everyone should behave, all of the time. Still, they deserve kudos for doing the right thing.
I will anticipate an objection (which was made to my initial rebuttal, in the comments to iWe’s post). Some may claim that they do not trust the CDC figures. I see no basis for such suspicion. This is a particularly troubling response by anyone who found Dr. Briand’s flawed analysis to be convincing, as she relied on CDC data.
I am critical of one thing that Johns Hopkins stated in its explanation of its withdrawal of Dr. Briand’s study. “As assistant director for the Master’s in Applied Economics program at Hopkins, Briand is neither a medical professional nor a disease researcher.” Fair enough, but Dr. Briand (here) holds a PhD in Economics and, for years, has taught econometrics and statistics. She doubtless knows far more about statistical analysis and mathematical modeling than 99% of medical professionals. So do I, it turns out, which makes me pretty weird (even among lawyers).
A final note. There is clear empirical evidence of a significant spike in total deaths in the US, precisely corresponding to the Covid pandemic. However, it is not necessarily the case that all of those deaths were the direct result of Covid. Some may have been the result of the response to Covid, ranging from deaths of despair (such as suicide) to deaths from other causes due to failure to seek medical care. Sorting out the precise impact of Covid itself, as distinguished from its secondary effects, with require further work. Actually, I think that this is the sort of thing that Dr. Briand was trying to do, but the details got lost due to her top-line errors.
I hope that this analysis proves helpful.
IV. Technical Notes
My data source for 2020 reported deaths by age group, both Covid and total, is the CDC (here). I calculated the non-Covid total as the difference between all deaths and Covid-involved deaths. This page will be updated periodically, so here is the screenshot:
My data source for 2017 deaths by age category is the National Vital Statistics Reports, Vol. 68, No. 9, “Deaths: Final Data for 2017” (here). The relevant data is in Table 2 on page 23.
Note that in both cases, I had to combine certain age categories to match the 10-year increments reported in Dr. Briand’s analysis.
My data source for reported deaths and excess death calculations, 2017-2020, is also the CDC (here). This is the same page as the blue-bar excess-deaths graph reproduced above. To access the data, scroll down to the “Options” section, “Download Data” subsection, “CSV Format” column, and click on “National and State Estimates of Excess Deaths.” This will allow you to download a .csv file that can be opened by Microsoft Excel.
Published in Healthcare
Jerry,
Terrific post. I was critical of Johns Hopkins for initially withdrawing the article with the comment it did; I’ll withdraw that criticism if it turns out that their subsequent explanation, which I thought more appropriate, was produced at the same time, and not in response to push-back to the withdrawal.
I do think that the article should have been rebutted in print. If in fact the errors are transparent, that should have been easy. That dialog would have both explained the error and increased confidence that reporting is unbiased. It would also have provided the author an opportunity to defend the work in the same forum, which I think is important.
Per the original (now withdrawn) article:
Is this a reporting error, a misinterpretation of data, or otherwise explained by your analysis?
And thanks for your efforts.
– Hank
Very good analysis. I noticed the same thing.
My first thought on reading the article was that of course deaths from other (medical) causes are down:
For the same reasons, I predict that we are going to have a very mild flu season this year. Everyone who is susceptible to flu has already died of the Wuhan Virus.
Thank you for your work.
I think perhaps if you considered this fact about Johns Hopkins, you might not be so quick to label Dr Briand’s work as a fraud.
That fact is: Bill and Melinda Gates Foundation “donated” 1. 2 billion dollars to Johns Hopkins since 2005.
How do we in the public know for certain this fact about the Gates/Hopkins symbiotic relationship has influenced the Johns Hopkins personnel?
We know it because if that 1.2 billions of dollars had not influenced them in a major way, half their doctors, scientists and researcher would be on the TV shouting to the heavens that it is beyond imagining, and that a deep hot place in hell should be reserved for everyone at the CDC and the NIH who
Here is a question for you to answer: Who would have paid Dr Briand to conduct such a “flawed study” to bring about a truth that the PTB have clearly let everyone with a brain know is not to be mentioned? Dr Briand must be intelligent – the only reason I can see for the study to be released, even though even mentioning such thoughts on FB or twitter will bring that social media user to be banned, must be because she wants to have the truth via her research to be revealed.
I have known many legitimate, thinking scientists who ware independent.
They often bring out studies that fly in the face of the “logical and truthful” science-y stuff we have been force fed for the last 60 years.
I think I am even mor eamazzed that you wrote this, when it is obvious that you are totally aware that the nonsense we are fed about the recent election is all controlled by the forces of Communism, hiding behind the mask of the Democrat Party.
When you research the COVID situation, that too is an affair that has
Hank, I didn’t focus on the portion of Dr. Briand’s analysis addressing the details of death by various causes. The portion of the article that you quote references an “expected drastic increase across all causes.” I don’t know why one would expect to see such an increase, in April 2020 (the period at issue in Dr. Briand’s analysis). I suspect that she is correct in some of this portion of her analysis — i.e. that some non-Covid deaths have been classified as Covid-related.
Oh come on. We have tens of millions of elderly and people with multiple risk factors for covid death who are 50+ years old. Plenty of people left to potentially get infected and die either of Covid or the flu. Despite a vast improvement treatment since March we are now seeing people dying every day in the 1-2 thousand range and its climbing. This is the most upsetting part of all this to me.
However I suspect we are going to have a mild flu season because lots of people are wearing masks, keeping their distance and washing their hands. The flu just can’t compete this year.
Jerry, that seems reasonable. The question of attribution of cause isn’t particularly relevant to the overall question of whether or not we have seen excess mortality — we clearly have. But the cause of that excess mortality could matter quite a lot, in that two unusual things, medically speaking, happened simultaneously in America this year: the SARS-CoV-2 virus spread through the population; and normal medical care was dramatically disrupted and curtailed. It’s likely that both of those factors have contributed to excess mortality. Understanding the relative contributions of each may be important.
The title of your post begins with “COVID Deaths are Real.” It may be that “Excess Deaths are Real” is more closely supported by the data you cite.
This is quite a post. Deeply thought out and well reasoned, based on the facts at issue, with conclusions limited to the topic at hand. We could use a lot more of this around here. Thanks for taking the time to put it together.
I agree that increased hygiene will also be a component of a mild flu season. You’ve got to admit that a large proportion of the people most susceptible to dying of flu have already died of the Wuhan Virus.
The thing is, many experts are saying the current flu death numbers don’t compute. At all.
Unless most flu cases are simply being reported as COVID cases, as anyone who is sick with the flu is then tested with the faulty PCR tests and then labeled a COVID patient.
Thank you for this post and the hard work you put into it.
I think your conclusions are compelling. Whether it matters or not, they do conform better to my personal knowledge of numerous people dead from Covid, and many others (4-5X that number) dead from lockdown-related causes – being in terrible shape leading to heart attacks, missing cancer appointments, suicide, etc.
I am still glad that I posted as I did – because all of these topics benefit from an argument for the sake of getting things right, instead of merely relying on “the consensus.”
I don’t agree. Only a tiny fraction of those susceptible have died. Again. tens of millions of elderly, hypertensive, diabetic, cardiac, immunocompromised, fat, etc etc etc people in the US.
We are testing flu all the time. Just not seeing it. But nice try.
I have run into this problem repeatedly, even when working on other mortality stats problems. It should be pretty simple for someone with basic math skills to solve, but I never had the persistence to come up with the solution, the Excel equations. Have you made an effort and if so, had any luck?
In order to create a head-to-head comparison when arbitrary age groupings are different, you have to disaggregate one or both data sets, back into to year-by-year data. (The bastards never let you download the original data ;-) This is a simple problem of interpolation. You need a smooth annual function for each data set that also produces the grouped average data. The slope at the end of each group has to match the slope at the beginning of the next.
Here is a webpage with the pertinent and most interesting comment that “Note that the Johns Hopkins’ personnel did not state that Briand’s numbers are inaccurate, as they retracted the study.”
The comments in the comment section are of interest as well:
https://www.lucianne.com/2020/11/28/johns_hopkins_study_saying_covid-19_has_relatively_no_effect_on_deaths_in_us_deleted_after_publication_49201.html
It will be interesting to see how our response to this virus changes the reporting procedures. My understanding of influenza reporting is that the annual reporting is heavily model-based, with relatively little actual sampling. It makes me wonder how much of our public health data is approximated, how consistently health care providers report data, how much slop and ambiguity there is in that data.
Year-on-year retrospective analysis is going to be fascinating.
Mark, in this case, it was pretty easy. Dr. Briand used 0-14, and 10 year increments thereafter through 84, with a final category of 85+. The 2020 CDC data used the same age categories for ages 15 and up, and split the younger ages into under 1, 1-4, and 5-14, so I was able to easily combine these into a 0-14 category by simple addition. Similarly, the 2017 data used under 1, 1-4, and 5-year increments thereafter (e.g. 15-19), again with a final 85+ category, so I just had to combine them by simple addition.
I agree with your general method, if you wanted to create a year-by-year estimate, if I understand you properly. Basically, you could do a regression of the results for each age category, using the midpoint of the age category as the age variable, and then estimate the figure for each individual year. This wouldn’t be perfect, and there’s probably a better way to do it, but I think that this would give a fairly accurate result.
In general, as you point out, the more detailed the data, the better.
Well here is hoping that the vaccines make these discussions wither in comparison to the vaccines effectiveness. Exit 2020, go 2021. Hope we can tell COVID-19 to go to hell.
The only hard data on flu is the requirement that fatalities in children be reported. Everything else is modeling – cases and deaths. When I looked into this at the start of covid, I was surprised how dependent all the flu data was on modeling. My own assessment as I dug further into it, was that flu deaths are probably substantially overestimated. The mortality figures you see for the Asia flu of the late 50s and the epidemic in 68-69 are also purely estimates.
Covid is unique for a major pandemic in that countries around the world are attempting, in real time, to track cases and deaths.
It would be surprising because if elders are especially threatened this year by disease then their share of all deaths should be greater than normal. If their share of total deaths remains constant, then it would mean that other age groups experienced excess deaths in equal proportion.
I had not read Briand’s article and have no investment in it. But data should show that elders are dying at a greater rate than normal or else COVID is only killing the usual number by different means.
I tried to find total excess deaths of all causes earlier today, but Google only returned excess deaths attributed to COVID (an estimation full of unprovable asumptions).
I would state that COVID is unique first and foremost for being an infection that had there been the use of the actual remedies, then there would have been far fewer deaths – yet the public was more interested in wearing masks, sheltering at home, and complying with other restrictions set out by those who seek to control us. The public complied rather than to demand that Fauci be driven from his top spot at the NIH (and possibly tarred and feathered on his way out of the Beltway.)
As far as tracking cases and deaths, the PCR test is an abysmal failure. If you are a member of the COVID 19 group, you can read a recent posting that comprises the entire reason why that test cannot be relied upon at all.
The antigen test might be the way to go, but then the case numbers, hospitalizations and deaths from COVID would all start to decline. So it is probably not gonna happen on a large scale, even though in a sane world, the public would demand only antigen tests be performed.
Only a tiny fraction of those susceptible to the flu die every year. I would bet that the Venn diagrams of both populations have a large overlap.
I don’t think that Dr. Briand’s numbers are inaccurate; they are simply irrelevant.
That may be true but, if so, we would not be unique, as there are currently about 3 dozen countries experiencing about the same per capita death rate on a daily basis as the U.S. You keep wanting to use other country data when it helps your allegations, as with that absurd chart used by Frontline Doctors purporting to compare death rates in countries using HCQ and those that don’t, but ignoring such context when it does not help you. There is a lot of information regarding Covid that cuts in both directions.
I am very aware of the problems with the PCR test. My comment went to the fact this pandemic is unique in countries trying to track cases daily for the first time. The accuracy of the PCR test has nothing to do with my point, since I made no claims for the accuracy of the case count.
This fact has become the most interesting microbiological event this year. The number of flu cases in South America this year has been extremely low. It’s very low in Massachusetts so far this year too. No one knows why. The experts in this field all seem to be speculating that it is the controls countries have enacted to prevent the spread of the covid-19 virus. Although that may be part of it, especially with people not being in social situations as often as they would be normally, it doesn’t explain the difference completely, at least not in my mind. People are trying hard to wear masks, wash their hands, and keep six feet from other people, but it’s still a hit-or-miss strategy. My suspicion is that the reason has something to do with the way the coronaviruses interact with the influenza viruses.
What do you think explains it?
All true. It’s been true for years.
We are never going back to a healthy society ever again, are we?
They are going to use this information to turn us into anti-social micro-pods of insulated familial groups.
Aaron, here is where I am curious about your thinking:
You state: It would be surprising because if elders are especially threatened this year by disease then their share of all deaths should be greater than normal.
But if one thing carries a person off before another, it might not really matter.
83 year old Celeste Smith is in bad shape. She has just recovered from surgery for a hip replacement, fought off a bad case of shingles, and has newly diagnosed COPD and heart problems.
In any given year, someone like Mrs Smith might not have very good odds of surviving to the end of the year. This year she may get COVID and succumb to it. But she also might simply get a bad cold, experience it becoming pneumonia and then die of the pneumonia. So although there are two possible manners of death for her this year, statistically there is not any difference.
Jerry Garcia once wrote about this phenomena: “If the thunder don’t get ya, then the lightning will.”
So basically there is no need to worry about excess deaths. For many of the elderly people who die from it, COVID is simply taking away those who would have gotten aboard the fatality train at a different train station.
One of the children who died of COVID happened to be someone with cystic fibrosis, a disease that might have caused their death any way and which certainly contributed to the patient not surviving their bout of COVID.
What I think is the worst thing about this event is all the fear that has been induced, and all the various economic shut downs and restrictions such that there is a lack of ability to lead normal lives.
I don’t get it. Are these points correct?
* there are excess deaths in the weekly data compared with other years
* the proportion of deaths by age band by month didn’t change much
* covid is much deadlier for the elderly than the young
Therefore, there are excess deaths for the elderly (in proportion with other age groups) and those might be caused by Covid and excess deaths for other ages may be caused by Covid or something else.
I thought the hypothesis of the original article was that Covid accelerated the deaths of some elderly folks by a short period (months), but over the long run, the number of deaths is about the same.
I don’t think we’ll ever have enough data to answer these questions. Give me 5 years of records with cause of death, age, date (14 million records) and I could probably find something in the data. Is there even a cause code on death certificates for excessively aggressive use of ventilator?
I would not argue that COVID is a hoax. It is not. People have died from COVID. It is a dangerous disease for many if not treated promptly, even though most rational and effective treatments have been discouraged. That said due to the incredibly politicized manner that American Health Care Authorities have dealt with this disease, I do not think that anyone can now or in even five years give anything close to an accurate analysis of how many deaths are due to COVID. It is clearly not as much as 260,000 or so, but how many is not really that clear. It is also clear that deaths are down significantly from their peak rates not that the Health Care Authorities want to recognize that.