8 ms·

Visualizing observed deaths using polar coordinates

93 points by mcculley 5y ago

taeric 5y ago
Visualizations are tough. It seems there is always a visualization you can use to show the story you are trying to tell, almost like "p-hacking", but "chart searching." For this data, I'm not at all clear on why a standard line chart isn't better. I'll confess, I don't find these charts bad; I just don't see them as clearer than the standard charts. What is the specific advantage? The commentary on lag of reporting being a surprise is, itself, surprising at this point. That was a big point of contention earlier, but I'm not sure I have seen it pan out in a way that matters. I'm torn on the commentary of the failure of governments. Policy choices have been very hard with more emotion driving choices than analyzed results. I'm personally in the bend of "be overly cautious," but I also get an uneasy feeling in just how little control there is in comparisons. About the only thing I know not to do now, is get cocky for any region and assume that anyone is already through this.
- breck 5y ago
  “Chart hacking” is a great term, thanks. I’m gonna start using that.
- nixpulvis 5y ago
  Years are cyclic, no? EDIT: Months to be precise.
  - taeric 5y ago
    But a year over year line chart already shows trends well enough. Splitting not by month, but by season, would be neat to see. But I'm sceptical there are any learnings to be had here.
    - deleted 5y ago
      [deleted]
    - nixpulvis 5y ago
      > I'm not at all clear on why a standard line chart isn't better. > ... well enough.
      - taeric 5y ago
        I'm not clear on what you are trying to say. My, "shows trends lines well enough" should be assumed as followed with "such that I do not see anything new in the post charts."
- kiberium 5y ago
  I don't know if this makes it better but my mental model of the calendar year is a circle divided into quarters.
- mcculley 5y ago
  Author here. Maybe I am too strident in my commentary on the failure of governments. I firmly believe there have been many failures. We should have implemented testing at scale in March of 2020. Now we are doomed to have partisan arguments about vaccinations and masks after having spent trillions on handouts.
  - taeric 5y ago
    I wish I knew how the partisan debate became the debate. :( For myself, I am not convinced we know what the world would have looked like given any alternative response. I do not think we should give up. I just don't know what has actually worked. Hard to argue against more testing, though. Edit: also, to be clear, I am not trying to argue you shouldn't do the charts this way. Rather, saying I probably need some training to align to what you think this makes more clear. And I believe it could just be different licks, and all that.
    - mcculley 5y ago
      I think that there is any confusion at all is more an indication that I have failed to make a good case for this being more useful. I found it more useful for my own needs looking at my state and trying to understand the normal expected seasonal variation versus 2020-2021. This is the kind of feedback I was looking for. Thank you.
      - taeric 5y ago
        Thanks for sharing! I see you got pointed suggestions for moving the legend and changing the scale. Looking forward to seeing them after those changes.
        mcculley 5y ago
        I have regenerated the graphs to use the square root of the count as the radius to keep the area constant, as others have suggested. I appreciate the feedback.
- belltaco 5y ago
  >It seems there is always a visualization you can use to show the story you are trying to tell, almost like "p-hacking", but "chart searching." Is there a visualization that tells the story that deaths due to covid weren't a big issue? The only way(other than just making up numbers) I have seen this done is to look at the last few months and use the reporting lag to mislead people into thinking there were fewer deaths than past years.
  - taeric 5y ago
    Fair. There are some stories that can't be told with the data anymore. That said, I haven't seen that one attempted. Unless it is to get and show good non uniform the risk involved is. The main question/story seems to be around just how preventable this was. And on that one, stories are all over the place.
    - deleted 5y ago
      [deleted]
  - deleted 5y ago
    [deleted]
  - PennRobotics 5y ago
    Three such visualizations: data that are confusing to the layperson, and data that minimize personal danger, and data that bend the brain's ability to comprehend. A plot of Case Fatality Rate would go down over time as the number of cases goes up. A somewhat related, slightly confusing example is cumulative deaths on a log plot. A handful of people would look at the line without much focus on the axes or title. A plot of Covid deaths by age group could make it more likely that young people engage in riskier activities, since it downplays the risk for "most" people---well, except someone else's grandparents who were gonna die soon anyway. And, in the WTF category: https://images.theconversation.com/files/330304/original/file-20200424-163098-1myrevx.png https://images.theconversation.com/files/330304/original/fil...
  - UncleMeat 5y ago
    > Is there a visualization that tells the story that deaths due to covid weren't a big issue? Yes, sort of. There was a great paper in CHI this year discussing how heterodox communities use visualizations (https://dl.acm.org/doi/fullHtml/10.1145/3411764.3445211 https://dl.acm.org/doi/fullHtml/10.1145/3411764.3445211). The rough conclusion is that visualizations do not just empower people to express the truth but are also used in skilled ways by heterodox communities.
phil-martin 5y ago
Interesting idea! I wonder if this provides additional visualisation than just a line graph with a horizontal axis of Jan-Dec. Wouldn't it show the same differences year to year? I looked for a CSV of the data that created the chart, but I failed. And perhaps the polar chart gives a false impression of higher values being much worse than they are, because the area is skewed so large the further out it is.
- mcculley 5y ago
  Author here. The CSV[0] comes from the CDC website[1] and you can find it in the code[2]. [0]: https://data.cdc.gov/api/views/xkkf-xrst/rows.csv?accessType=DOWNLOAD&bom=true&format=true%20targe https://data.cdc.gov/api/views/xkkf-xrst/rows.csv?accessType... [1]: https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm [2]: https://github.com/mcculley/ObservedDeathVisualizer/blob/main/src/main/java/org/enki/odv/ObservedDeathVisualizer.java#L336 https://github.com/mcculley/ObservedDeathVisualizer/blob/mai...
  - mcculley 5y ago
    I realized I should have anchored the line in the source code to a particular commit: https://github.com/mcculley/ObservedDeathVisualizer/blob/f29f7dd194b71f4ec4eb5995ba906ccf1606b977/src/main/java/org/enki/odv/ObservedDeathVisualizer.java#L381 https://github.com/mcculley/ObservedDeathVisualizer/blob/f29...
- mcculley 5y ago
  I originally was doing this just for Florida. Because Florida generally has the most deaths during the dry, cold weeks at the end of January, it made it harder for me to see and show that trend on the horizontal chart as it wrapped across both ends.
dahart 5y ago
I feel like one perceptual problem with this polar plot is that the area under the excess deaths is misleadingly large - - it feels like the proportion of excess deaths is much larger than it really is, because the area between the 2020/21 line and 2018/19 line is almost as much area as under the 2018/19 line, even though the average ratio is (eyeballing) more like 20%. > Using this kind of graph one can more easily see how changes year-to-year in total observed deaths have been affected by COVID-19. It’s important to look at and account for the number of deaths directly attributed to COVID, isn’t it? Is there some discrepancy between the excess YoY deaths implied here and the number directly attributed to COVID? Also would be good to normalize per-capita, just to fully factor out population growth? > Using total observed deaths, one can disregard the (mis)attribution of deaths to COVID-19 and more clearly see the failure of federal and state governments. Out of curiosity, what are the misattributions and failures being referred to? Just confused a little since the source data is federal (CDC) and has this exact same graph showing the excess death rate this year, just on a horizontal plot.
- antattack 5y ago
  > It’s important to look at and account for the number of deaths directly attributed to COVID, isn’t it? Is there some discrepancy between the excess YoY deaths implied here and the number directly attributed to COVID? Also would be good to normalize per-capita, just to fully factor out population growth? If that's important to you than just use Cartesian graph. Polar graph shows better seasonal patterns as it does not cut abruptly at the end of the each year.
- nixpulvis 5y ago
  I was thinking about that while reading these plots too. But I also wonder if readers will understand the slopes.
- icegreentea2 5y ago
  Misattributions could be referring to two possible things: A) Uncertainty about how deaths are effectively false positives, and how many "deaths due to COVID" weren't counted. This is a combination of plain uncertainty, not having testing available for everything, all the way up to people fudging numbers (perhaps by choosing not to test categories of deaths). B) It's unclear (as in people will argue, on both sides) if "deaths with COVID" vs "deaths due to COVID (with some definition of 'due')" is the right measure. The failures is just shit talking (shit talk can be both deserved and undeserved) the government responses. The basis of the shit talking is that the red and green lines should be far closer to the previous baselines.
tantalor 5y ago
Nightingale rose diagram https://en.wikipedia.org/wiki/Pie_chart#Polar_area_diagram https://en.wikipedia.org/wiki/Pie_chart#Polar_area_diagram
- sn9 5y ago
  Someone mentioned how the area under the curve could be misleading, and this link addresses how to correct for that: "The radius of each sector would be proportional to the square root of the death count for the month, so the area of a sector represents the number of deaths in a month."
  - mcculley 5y ago
    Author here. Yes, I didn't think of that. I will change the code to do that. Thanks.
- erk__ 5y ago
  Numberphile made a video about them 5 months ago for the same use as presented here https://youtu.be/VTdVPNvwULM https://youtu.be/VTdVPNvwULM
antattack 5y ago
I think looking at individual state charts bring more meaning and accuracy. What caught my eye was that while many states almost returned to pre-pandemic death rate, Florida and Texas have been running above average while their governor's are fighting masking mandates.
- deleted 5y ago
  [deleted]
syntaxfree 5y ago
In Microsoft Excel: “radar chart”.
aaron695 5y ago
The reason you are not apes in tress is because you can turn data into lower dimensions. Which this shows. A bar graph or line graph would be better. Trying to use the data in this 2.5D it looks like is skews North North East. But that seems to be an optical illusion due to the darker colors. Not sure, need less dimensions like a number. These are good for news articles, the more ape like you make people the more they tend to click. Some higher dimensions work like maps. But you can see how AR will always fail and VR has a long road because their added dimensions are too much in most circumstances.
n8ta 5y ago
"Using this kind of graph one can more easily see" False, I cannot tell what is happening in this graph. It's hard to go back and forth between the graph and the legend to tell what year it is. One way to improve the readability is to have the color shift uniformly between one PAST color and one PRESENT color so I can follow the line from the past to the present. While animation rarely improves graphs, it really can if time is the 3rd dimension your 2d visualization (image) needs. Something like this http://www.climate-lab-book.ac.uk/spirals/ http://www.climate-lab-book.ac.uk/spirals/ (first gif)
- vletal 5y ago
  It would be enough if the legend was closer to the point when the color changes.
  - mcculley 5y ago
    Author here. I had not thought of doing that. I will try that. Thanks.
willsoon 5y ago
Uhu. April is the cruelest month.
vletal 5y ago
What caused the excess death in early 2018?
- icegreentea2 5y ago
  Maybe flu? 2017-2018 flu season was relatively rough.
- whoopdedo 5y ago
  Cyclonic blizzard over the East coast.
stardenburden 5y ago
In Germany less people died through the pandemic than died in normal years. At least in 2020. What happened was that people were overly careful - in all parts of life, e.g. meeting people, wearing masks (less of a flu season = less deaths) and going to a doctor when sick - hospital s greatly increased their capacity and afaik Germany never had the dramatic situations where people couldn't get oxygen or staff was at the edge of quitting.
- beervirus 5y ago
  This does not seem to be true, at least based on a quick googling.
  - jeffbee 5y ago
    Even just eyeballing the Euromomo.eu graphs, I can see no time at which deaths in Germany were below the long-term average rate during 2020, and many times where they are far above it.
  - s9w 5y ago
    It's still true. At least when taking population changes into account.
d--b 5y ago
The only benefit of this compared to overlapping yearly line charts is to connect December with January, which does not justify losing the ability to quickly compare values on a straight linear axis.
Elzear 5y ago
There are a lot of very nice articles showing the mortality in France during Covid-19 compared to other years and events (epidemics, heat waves), good reads. https://www.insee.fr/en/statistiques/5359584 https://www.insee.fr/en/statistiques/5359584
jamessb 5y ago
See also this similar plot for the UK: https://www.cebm.net/covid-19/covid-19-florence-nightingales-daigrams-for-deaths/ https://www.cebm.net/covid-19/covid-19-florence-nightingales...
argvargc 5y ago
Is this just number of deaths without population context? If so, it's falsely accumulating. Probably not a huge deal given the period and growth rate, but still, not hard to adjust. USA population growth is about 0.6%/year. Adjust total population on a per month basis and show the deaths per population instead of the total deaths. Would love to see a bunch of age-stratified versions.
- MatteoFrigo 5y ago
  https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm has the age-stratified data for the US you are looking for. I think they adjust for population growth, but I am not sure. https://euromomo.eu/graphs-and-maps/ https://euromomo.eu/graphs-and-maps/ has similar data for most of Europe and Israel, and they adjust for population growth and a seasonal component (looks like a sine wave of period 1 year).
zigradett 5y ago
From this it looks like "April May June July 2021" are almost back to the "normal" number of deaths, and not too much excess. Wonder what that means. Maybe that everyone who was gonna die from COVID-19 exposure already did. Maybe something else. We can be sure that "December January February 2022" will show some excess.

93 points by mcculley 5y ago

Visualizations are tough. It seems there is always a visualization you can use to show the story you are trying to tell, almost like "p-hacking", but "chart searching." For this data, I'm not at all clear on why a standard line chart isn't better. I'll confess, I don't find these charts bad; I just don't see them as clearer than the standard charts. What is the specific advantage? The commentary on lag of reporting being a surprise is, itself, surprising at this point. That was a big point of contention earlier, but I'm not sure I have seen it pan out in a way that matters. I'm torn on the commentary of the failure of governments. Policy choices have been very hard with more emotion driving choices than analyzed results. I'm personally in the bend of "be overly cautious," but I also get an uneasy feeling in just how little control there is in comparisons. About the only thing I know not to do now, is get cocky for any region and assume that anyone is already through this.

breck 5y ago
“Chart hacking” is a great term, thanks. I’m gonna start using that.
nixpulvis 5y ago
Years are cyclic, no? EDIT: Months to be precise.
- taeric 5y ago
  But a year over year line chart already shows trends well enough. Splitting not by month, but by season, would be neat to see. But I'm sceptical there are any learnings to be had here.
  - deleted 5y ago
    [deleted]
  - nixpulvis 5y ago
    > I'm not at all clear on why a standard line chart isn't better. > ... well enough.
    - taeric 5y ago
      I'm not clear on what you are trying to say. My, "shows trends lines well enough" should be assumed as followed with "such that I do not see anything new in the post charts."
kiberium 5y ago
I don't know if this makes it better but my mental model of the calendar year is a circle divided into quarters.
mcculley 5y ago
Author here. Maybe I am too strident in my commentary on the failure of governments. I firmly believe there have been many failures. We should have implemented testing at scale in March of 2020. Now we are doomed to have partisan arguments about vaccinations and masks after having spent trillions on handouts.
- taeric 5y ago
  I wish I knew how the partisan debate became the debate. :( For myself, I am not convinced we know what the world would have looked like given any alternative response. I do not think we should give up. I just don't know what has actually worked. Hard to argue against more testing, though. Edit: also, to be clear, I am not trying to argue you shouldn't do the charts this way. Rather, saying I probably need some training to align to what you think this makes more clear. And I believe it could just be different licks, and all that.
  - mcculley 5y ago
    I think that there is any confusion at all is more an indication that I have failed to make a good case for this being more useful. I found it more useful for my own needs looking at my state and trying to understand the normal expected seasonal variation versus 2020-2021. This is the kind of feedback I was looking for. Thank you.
    - taeric 5y ago
      Thanks for sharing! I see you got pointed suggestions for moving the legend and changing the scale. Looking forward to seeing them after those changes.
      - mcculley 5y ago
        I have regenerated the graphs to use the square root of the count as the radius to keep the area constant, as others have suggested. I appreciate the feedback.
belltaco 5y ago
>It seems there is always a visualization you can use to show the story you are trying to tell, almost like "p-hacking", but "chart searching." Is there a visualization that tells the story that deaths due to covid weren't a big issue? The only way(other than just making up numbers) I have seen this done is to look at the last few months and use the reporting lag to mislead people into thinking there were fewer deaths than past years.
- taeric 5y ago
  Fair. There are some stories that can't be told with the data anymore. That said, I haven't seen that one attempted. Unless it is to get and show good non uniform the risk involved is. The main question/story seems to be around just how preventable this was. And on that one, stories are all over the place.
  - deleted 5y ago
    [deleted]
- deleted 5y ago
  [deleted]
- PennRobotics 5y ago
  Three such visualizations: data that are confusing to the layperson, and data that minimize personal danger, and data that bend the brain's ability to comprehend. A plot of Case Fatality Rate would go down over time as the number of cases goes up. A somewhat related, slightly confusing example is cumulative deaths on a log plot. A handful of people would look at the line without much focus on the axes or title. A plot of Covid deaths by age group could make it more likely that young people engage in riskier activities, since it downplays the risk for "most" people---well, except someone else's grandparents who were gonna die soon anyway. And, in the WTF category: https://images.theconversation.com/files/330304/original/file-20200424-163098-1myrevx.png https://images.theconversation.com/files/330304/original/fil...
- UncleMeat 5y ago
  > Is there a visualization that tells the story that deaths due to covid weren't a big issue? Yes, sort of. There was a great paper in CHI this year discussing how heterodox communities use visualizations (https://dl.acm.org/doi/fullHtml/10.1145/3411764.3445211 https://dl.acm.org/doi/fullHtml/10.1145/3411764.3445211). The rough conclusion is that visualizations do not just empower people to express the truth but are also used in skilled ways by heterodox communities.

phil-martin 5y ago

Interesting idea! I wonder if this provides additional visualisation than just a line graph with a horizontal axis of Jan-Dec. Wouldn't it show the same differences year to year? I looked for a CSV of the data that created the chart, but I failed. And perhaps the polar chart gives a false impression of higher values being much worse than they are, because the area is skewed so large the further out it is.

mcculley 5y ago
Author here. The CSV[0] comes from the CDC website[1] and you can find it in the code[2]. [0]: https://data.cdc.gov/api/views/xkkf-xrst/rows.csv?accessType=DOWNLOAD&bom=true&format=true%20targe https://data.cdc.gov/api/views/xkkf-xrst/rows.csv?accessType... [1]: https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm [2]: https://github.com/mcculley/ObservedDeathVisualizer/blob/main/src/main/java/org/enki/odv/ObservedDeathVisualizer.java#L336 https://github.com/mcculley/ObservedDeathVisualizer/blob/mai...
- mcculley 5y ago
  I realized I should have anchored the line in the source code to a particular commit: https://github.com/mcculley/ObservedDeathVisualizer/blob/f29f7dd194b71f4ec4eb5995ba906ccf1606b977/src/main/java/org/enki/odv/ObservedDeathVisualizer.java#L381 https://github.com/mcculley/ObservedDeathVisualizer/blob/f29...
mcculley 5y ago
I originally was doing this just for Florida. Because Florida generally has the most deaths during the dry, cold weeks at the end of January, it made it harder for me to see and show that trend on the horizontal chart as it wrapped across both ends.

dahart 5y ago

I feel like one perceptual problem with this polar plot is that the area under the excess deaths is misleadingly large - - it feels like the proportion of excess deaths is much larger than it really is, because the area between the 2020/21 line and 2018/19 line is almost as much area as under the 2018/19 line, even though the average ratio is (eyeballing) more like 20%. > Using this kind of graph one can more easily see how changes year-to-year in total observed deaths have been affected by COVID-19. It’s important to look at and account for the number of deaths directly attributed to COVID, isn’t it? Is there some discrepancy between the excess YoY deaths implied here and the number directly attributed to COVID? Also would be good to normalize per-capita, just to fully factor out population growth? > Using total observed deaths, one can disregard the (mis)attribution of deaths to COVID-19 and more clearly see the failure of federal and state governments. Out of curiosity, what are the misattributions and failures being referred to? Just confused a little since the source data is federal (CDC) and has this exact same graph showing the excess death rate this year, just on a horizontal plot.

antattack 5y ago
> It’s important to look at and account for the number of deaths directly attributed to COVID, isn’t it? Is there some discrepancy between the excess YoY deaths implied here and the number directly attributed to COVID? Also would be good to normalize per-capita, just to fully factor out population growth? If that's important to you than just use Cartesian graph. Polar graph shows better seasonal patterns as it does not cut abruptly at the end of the each year.
nixpulvis 5y ago
I was thinking about that while reading these plots too. But I also wonder if readers will understand the slopes.
icegreentea2 5y ago
Misattributions could be referring to two possible things: A) Uncertainty about how deaths are effectively false positives, and how many "deaths due to COVID" weren't counted. This is a combination of plain uncertainty, not having testing available for everything, all the way up to people fudging numbers (perhaps by choosing not to test categories of deaths). B) It's unclear (as in people will argue, on both sides) if "deaths with COVID" vs "deaths due to COVID (with some definition of 'due')" is the right measure. The failures is just shit talking (shit talk can be both deserved and undeserved) the government responses. The basis of the shit talking is that the red and green lines should be far closer to the previous baselines.

tantalor 5y ago

Nightingale rose diagram https://en.wikipedia.org/wiki/Pie_chart#Polar_area_diagram https://en.wikipedia.org/wiki/Pie_chart#Polar_area_diagram

sn9 5y ago
Someone mentioned how the area under the curve could be misleading, and this link addresses how to correct for that: "The radius of each sector would be proportional to the square root of the death count for the month, so the area of a sector represents the number of deaths in a month."
- mcculley 5y ago
  Author here. Yes, I didn't think of that. I will change the code to do that. Thanks.
erk__ 5y ago
Numberphile made a video about them 5 months ago for the same use as presented here https://youtu.be/VTdVPNvwULM https://youtu.be/VTdVPNvwULM

antattack 5y ago

I think looking at individual state charts bring more meaning and accuracy. What caught my eye was that while many states almost returned to pre-pandemic death rate, Florida and Texas have been running above average while their governor's are fighting masking mandates.

deleted 5y ago
[deleted]

syntaxfree 5y ago

In Microsoft Excel: “radar chart”.

aaron695 5y ago

The reason you are not apes in tress is because you can turn data into lower dimensions. Which this shows. A bar graph or line graph would be better. Trying to use the data in this 2.5D it looks like is skews North North East. But that seems to be an optical illusion due to the darker colors. Not sure, need less dimensions like a number. These are good for news articles, the more ape like you make people the more they tend to click. Some higher dimensions work like maps. But you can see how AR will always fail and VR has a long road because their added dimensions are too much in most circumstances.

n8ta 5y ago

"Using this kind of graph one can more easily see" False, I cannot tell what is happening in this graph. It's hard to go back and forth between the graph and the legend to tell what year it is. One way to improve the readability is to have the color shift uniformly between one PAST color and one PRESENT color so I can follow the line from the past to the present. While animation rarely improves graphs, it really can if time is the 3rd dimension your 2d visualization (image) needs. Something like this http://www.climate-lab-book.ac.uk/spirals/ http://www.climate-lab-book.ac.uk/spirals/ (first gif)

vletal 5y ago
It would be enough if the legend was closer to the point when the color changes.
- mcculley 5y ago
  Author here. I had not thought of doing that. I will try that. Thanks.

willsoon 5y ago

Uhu. April is the cruelest month.

vletal 5y ago

What caused the excess death in early 2018?

icegreentea2 5y ago
Maybe flu? 2017-2018 flu season was relatively rough.
whoopdedo 5y ago
Cyclonic blizzard over the East coast.

stardenburden 5y ago

In Germany less people died through the pandemic than died in normal years. At least in 2020. What happened was that people were overly careful - in all parts of life, e.g. meeting people, wearing masks (less of a flu season = less deaths) and going to a doctor when sick - hospital s greatly increased their capacity and afaik Germany never had the dramatic situations where people couldn't get oxygen or staff was at the edge of quitting.

beervirus 5y ago
This does not seem to be true, at least based on a quick googling.
- jeffbee 5y ago
  Even just eyeballing the Euromomo.eu graphs, I can see no time at which deaths in Germany were below the long-term average rate during 2020, and many times where they are far above it.
- s9w 5y ago
  It's still true. At least when taking population changes into account.

d--b 5y ago

The only benefit of this compared to overlapping yearly line charts is to connect December with January, which does not justify losing the ability to quickly compare values on a straight linear axis.

Elzear 5y ago

There are a lot of very nice articles showing the mortality in France during Covid-19 compared to other years and events (epidemics, heat waves), good reads. https://www.insee.fr/en/statistiques/5359584 https://www.insee.fr/en/statistiques/5359584

jamessb 5y ago

See also this similar plot for the UK: https://www.cebm.net/covid-19/covid-19-florence-nightingales-daigrams-for-deaths/ https://www.cebm.net/covid-19/covid-19-florence-nightingales...

argvargc 5y ago

Is this just number of deaths without population context? If so, it's falsely accumulating. Probably not a huge deal given the period and growth rate, but still, not hard to adjust. USA population growth is about 0.6%/year. Adjust total population on a per month basis and show the deaths per population instead of the total deaths. Would love to see a bunch of age-stratified versions.

MatteoFrigo 5y ago
https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm has the age-stratified data for the US you are looking for. I think they adjust for population growth, but I am not sure. https://euromomo.eu/graphs-and-maps/ https://euromomo.eu/graphs-and-maps/ has similar data for most of Europe and Israel, and they adjust for population growth and a seasonal component (looks like a sine wave of period 1 year).

zigradett 5y ago

From this it looks like "April May June July 2021" are almost back to the "normal" number of deaths, and not too much excess. Wonder what that means. Maybe that everyone who was gonna die from COVID-19 exposure already did. Maybe something else. We can be sure that "December January February 2022" will show some excess.