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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 The paper was subsequently withdrawn by Johns Hopkins, quite properly in my view.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
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