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Why all graphs are cummulative instead of new cases for that day? It's harder to notice how it is growing that way (i.e. more or less new cases than the previou

Why all graphs are cummulative instead of new cases for that day? It's harder to notice how it is growing that way (i.e. more or less new cases than the previous days) and harder to see if it is going exponential, lineal or whatever. And, of course, forces to use log scales because the accumulated number is already high. At least for networking graphs is more meaningful to see difference from the actual from the previous commulative total, than watching the total for a network interface. Another, at least for me, misleading use of graphs is to show the cummulative total people that ever got sick, instead of the current amount of sick people (taking out the recovered, and maybe the dead ones). I know that how the measurements are done in most places is rigged, as not everyone is checked, and there are a lot of people that are asymptomatic, but that happens with both the new cases and the cummulative ones. Showing the cummulative numbers don't take out that rigging.

arcticbull 7y ago
Yeah I came by to say the same thing. I understand that "cumulative" and "dead" are super sensationalist, but what really matters isn't how many people have had it, but how many people have it right now and how that number's changing day by day. It's impossible to figure out and it makes this chart very misleading. For instance, China's hovering around 10e5 cases on the chart, but they have 2e3. That's three orders of magnitude misleading, especially when 95-100% of people recover completely and are quite unlikely to get it again. tl;dr: China features prominently on those graphs but their outbreak is contained and finished, they've re-opened internally and pollution (hence factory output) is returning to normal. The graph doesn't reflect that in a meaningful way. [1] [1] https://www.forbes.com/sites/jeffmcmahon/2020/03/22/video-watch-from-space-as-air-pollution-vanishes-over-china-during-coronavirus-lockdown-then-returns/#3db933f135f0 https://www.forbes.com/sites/jeffmcmahon/2020/03/22/video-wa...
theSage 7y ago
I'm not sure if the equation is right but I've done a daily case plot for Indian cases. https://gist.github.com/theSage21/29608c666a378dcb276a9dd9e4ad9fed https://gist.github.com/theSage21/29608c666a378dcb276a9dd9e4...
em500 7y ago
One reason is that daily increases are very volatile/noisy. The standard way to handle this is to use n-day moving averages, but they have a time lag and are harder to interpret. Financial Times has the best graphical trackers I've seen. They used to show cumulative counts, but switched to 7-day moving averages of daily increases" recently. https://www.ft.com/coronavirus-latest https://www.ft.com/coronavirus-latest I agree that displaying increases/growth rates are more informative overall, but it does take more time to understand the metrics. (Just compare the descriptions: "Total Deaths" vs "7-day moving average of daily increase in Total Deaths")
- computerphysics 7y ago
  Not really. Data for Spain can be perfectly used and fit without averages on daily increases => https://media-exp1.licdn.com/dms/image/C5622AQH1JmaVMs3mqQ/feedshare-shrink_2048_1536/0?e=1588809600&v=beta&t=oMud1mnDc9G9xn9wIa_nMQ83ZZzvVhS5y7ZMB9WMZWA https://media-exp1.licdn.com/dms/image/C5622AQH1JmaVMs3mqQ/f...
  - em500 7y ago
    It's unclear what that graph is supposed to show. It can't be cumulative cases (because there are days with decreases), but the scales are completely off if they're supposed to show daily increases/diffs (Spain certainly did not see daily increases anywhere near 100k in the past few days).
- jacobush 7y ago
  On the other hand I don't understand how bad it is from looking at the graph with the easy to understand metric.
grey-area 7y ago
Daily numbers have problems too, they can get quite noisy. Both have their uses, particularly seen together. I also think linear scales have their place alongside log (which can be hard for laypeople to grasp). Here are daily numbers for France for example: https://coronavirus.projectpage.app/france?period=28 https://coronavirus.projectpage.app/france?period=28 The jump recently is due to a change in reporting to include deaths outside hospital (something most countries have yet to do), and these are reported deaths not actual, and subject to all kinds of caveats. Reported cases is even worse. Recovered cases is worst of all and not being properly tracked in most areas. A moving average of daily cases might be best. I think the ft (who have nice graphs of this along with commentary) are moving toward this. https://www.ft.com/coronavirus-latest https://www.ft.com/coronavirus-latest There's a nice commentary on what they're doing here: https://mobile.twitter.com/jburnmurdoch/status/1246184639540146178 https://mobile.twitter.com/jburnmurdoch/status/1246184639540...
mrb 7y ago
I agree! Cumulative charts are less useful. For my charts, I represent new cases or new deaths per day. It shows such a clear picture of the trend of the growth: https://mobile.twitter.com/zorinaq/status/1245787017436221445 https://mobile.twitter.com/zorinaq/status/124578701743622144...
- jansan 7y ago
  Do you have these charts for the main countries? From your chart it looks like Italy and Spain have reached the peak, US is still growing, Germany may be just about to peak. But it is hard to read.
  - em500 7y ago
    The FT graphs show the increases/growths/1st-derivative. Italy and Spain are likely over peak-growth, Germany and France nearly, UK and US not yet. These are 7-day rolling averages, so there's roughly 3.5 days delay in the estimated signal. https://www.ft.com/coronavirus-latest https://www.ft.com/coronavirus-latest
op03 7y ago
Apparently the right way to do it is to show Daily Total deaths (ALL deaths not just covid) per local region Vs daily historic total deaths of that region - so some kind of Excess Death indicator. And that shows pandemic effect rising and falling, because many cases either don't reach a hospital, get misclassified etc But getting a daily ticker of total deaths (all deaths not just covid) in most parts of the world gets shutdown quick by politicians of all stripes.
analog31 7y ago
For a while there, it made no difference. When cases are growing exponentially, the two graphs are proportional to one another. The cumulative graph made it easy to spot when a particular region or locality had gone exponential, which I took to indicate the onset of community spread.
Youden 7y ago
Just in case you haven't seen it, I'm a big fan of this [0] chart, which plots new weekly cases against cumulative total, both axes on a log scale. It has a whole video explanation [1] if you're interested in the logic behind it. [0]: https://aatishb.com/covidtrends/ https://aatishb.com/covidtrends/ [1]: https://www.youtube.com/watch?v=54XLXg4fYsc https://www.youtube.com/watch?v=54XLXg4fYsc
- contravariant 7y ago
  I'm not too fond of that chart because all you can really see clearly on it is when the increase stops being exponential. It is pretty hard to see the base of the exponential (in most countries the increase in confirmed infections has been slowing down, relatively speaking, but that is incredibly hard to spot from that graph, which makes the situations seem worse than it already is).
FabHK 7y ago
The FT switched from cumulative to new. While taking that first derivative has some advantages, I for one was clamouring for the original plots, and am grateful that the author has brought them back. Thanks!
rmst 7y ago
Log cumulative graphs make it hard to see whether the daily rates are increasing or decreasing. Here are non-log, non-cumulative, new daily deaths per 1M people to compare different countries: https://colab.research.google.com/drive/1dNAVpgRGjEViK-9ULhEI2ad7xBb39YMi https://colab.research.google.com/drive/1dNAVpgRGjEViK-9ULhE...
seektable 7y ago
New cases may be calculated as a difference between cummulative prev and next day. This is how daily cases are shown here by JHU dataset: http://covid-19.seektable.com/report/fe66549d73c64773bd6712e45af9bbc2 http://covid-19.seektable.com/report/fe66549d73c64773bd6712e...

arcticbull 7y ago

Yeah I came by to say the same thing. I understand that "cumulative" and "dead" are super sensationalist, but what really matters isn't how many people have had it, but how many people have it right now and how that number's changing day by day. It's impossible to figure out and it makes this chart very misleading. For instance, China's hovering around 10e5 cases on the chart, but they have 2e3. That's three orders of magnitude misleading, especially when 95-100% of people recover completely and are quite unlikely to get it again. tl;dr: China features prominently on those graphs but their outbreak is contained and finished, they've re-opened internally and pollution (hence factory output) is returning to normal. The graph doesn't reflect that in a meaningful way. [1] [1] https://www.forbes.com/sites/jeffmcmahon/2020/03/22/video-watch-from-space-as-air-pollution-vanishes-over-china-during-coronavirus-lockdown-then-returns/#3db933f135f0 https://www.forbes.com/sites/jeffmcmahon/2020/03/22/video-wa...

theSage 7y ago

I'm not sure if the equation is right but I've done a daily case plot for Indian cases. https://gist.github.com/theSage21/29608c666a378dcb276a9dd9e4ad9fed https://gist.github.com/theSage21/29608c666a378dcb276a9dd9e4...

em500 7y ago

One reason is that daily increases are very volatile/noisy. The standard way to handle this is to use n-day moving averages, but they have a time lag and are harder to interpret. Financial Times has the best graphical trackers I've seen. They used to show cumulative counts, but switched to 7-day moving averages of daily increases" recently. https://www.ft.com/coronavirus-latest https://www.ft.com/coronavirus-latest I agree that displaying increases/growth rates are more informative overall, but it does take more time to understand the metrics. (Just compare the descriptions: "Total Deaths" vs "7-day moving average of daily increase in Total Deaths")

computerphysics 7y ago
Not really. Data for Spain can be perfectly used and fit without averages on daily increases => https://media-exp1.licdn.com/dms/image/C5622AQH1JmaVMs3mqQ/feedshare-shrink_2048_1536/0?e=1588809600&v=beta&t=oMud1mnDc9G9xn9wIa_nMQ83ZZzvVhS5y7ZMB9WMZWA https://media-exp1.licdn.com/dms/image/C5622AQH1JmaVMs3mqQ/f...
- em500 7y ago
  It's unclear what that graph is supposed to show. It can't be cumulative cases (because there are days with decreases), but the scales are completely off if they're supposed to show daily increases/diffs (Spain certainly did not see daily increases anywhere near 100k in the past few days).
jacobush 7y ago
On the other hand I don't understand how bad it is from looking at the graph with the easy to understand metric.

grey-area 7y ago

Daily numbers have problems too, they can get quite noisy. Both have their uses, particularly seen together. I also think linear scales have their place alongside log (which can be hard for laypeople to grasp). Here are daily numbers for France for example: https://coronavirus.projectpage.app/france?period=28 https://coronavirus.projectpage.app/france?period=28 The jump recently is due to a change in reporting to include deaths outside hospital (something most countries have yet to do), and these are reported deaths not actual, and subject to all kinds of caveats. Reported cases is even worse. Recovered cases is worst of all and not being properly tracked in most areas. A moving average of daily cases might be best. I think the ft (who have nice graphs of this along with commentary) are moving toward this. https://www.ft.com/coronavirus-latest https://www.ft.com/coronavirus-latest There's a nice commentary on what they're doing here: https://mobile.twitter.com/jburnmurdoch/status/1246184639540146178 https://mobile.twitter.com/jburnmurdoch/status/1246184639540...

mrb 7y ago

I agree! Cumulative charts are less useful. For my charts, I represent new cases or new deaths per day. It shows such a clear picture of the trend of the growth: https://mobile.twitter.com/zorinaq/status/1245787017436221445 https://mobile.twitter.com/zorinaq/status/124578701743622144...

jansan 7y ago
Do you have these charts for the main countries? From your chart it looks like Italy and Spain have reached the peak, US is still growing, Germany may be just about to peak. But it is hard to read.
- em500 7y ago
  The FT graphs show the increases/growths/1st-derivative. Italy and Spain are likely over peak-growth, Germany and France nearly, UK and US not yet. These are 7-day rolling averages, so there's roughly 3.5 days delay in the estimated signal. https://www.ft.com/coronavirus-latest https://www.ft.com/coronavirus-latest

op03 7y ago

Apparently the right way to do it is to show Daily Total deaths (ALL deaths not just covid) per local region Vs daily historic total deaths of that region - so some kind of Excess Death indicator. And that shows pandemic effect rising and falling, because many cases either don't reach a hospital, get misclassified etc But getting a daily ticker of total deaths (all deaths not just covid) in most parts of the world gets shutdown quick by politicians of all stripes.

analog31 7y ago

For a while there, it made no difference. When cases are growing exponentially, the two graphs are proportional to one another. The cumulative graph made it easy to spot when a particular region or locality had gone exponential, which I took to indicate the onset of community spread.

Youden 7y ago

Just in case you haven't seen it, I'm a big fan of this [0] chart, which plots new weekly cases against cumulative total, both axes on a log scale. It has a whole video explanation [1] if you're interested in the logic behind it. [0]: https://aatishb.com/covidtrends/ https://aatishb.com/covidtrends/ [1]: https://www.youtube.com/watch?v=54XLXg4fYsc https://www.youtube.com/watch?v=54XLXg4fYsc

contravariant 7y ago
I'm not too fond of that chart because all you can really see clearly on it is when the increase stops being exponential. It is pretty hard to see the base of the exponential (in most countries the increase in confirmed infections has been slowing down, relatively speaking, but that is incredibly hard to spot from that graph, which makes the situations seem worse than it already is).

FabHK 7y ago

The FT switched from cumulative to new. While taking that first derivative has some advantages, I for one was clamouring for the original plots, and am grateful that the author has brought them back. Thanks!

rmst 7y ago

Log cumulative graphs make it hard to see whether the daily rates are increasing or decreasing. Here are non-log, non-cumulative, new daily deaths per 1M people to compare different countries: https://colab.research.google.com/drive/1dNAVpgRGjEViK-9ULhEI2ad7xBb39YMi https://colab.research.google.com/drive/1dNAVpgRGjEViK-9ULhE...

seektable 7y ago

New cases may be calculated as a difference between cummulative prev and next day. This is how daily cases are shown here by JHU dataset: http://covid-19.seektable.com/report/fe66549d73c64773bd6712e45af9bbc2 http://covid-19.seektable.com/report/fe66549d73c64773bd6712e...