Why are covid-19 cases shown also on a logarithmic scale? on worldometer for example.
From my understanding, the ln(x) is the inverse function of the e(x) and so we could better see, if the curve flattens, when plotting the cases on a logarithmic scale? is this true?
Interesting question! Please see the following thread: What's a logarithmic graph and how does it help explain the spread of COVID-19? https://www.weforum.org/agenda/2020/04/covid-19-spread-logarithmic-graph/
In fact the logarithmic scale has an "optimistic" effect it does NOT show the evolution it gives the false feeling of flattening although the growing rate is still important.
in the natural sciences more often logarithmic scales are used, but unfortunately also too often , as Nick also wrote in essence, hiding details what really happens, it flattens out a lot. Looking at what happens is even better when taking daily increments, these should go down.
thanks Nick, indeed clearly visible.
Still, I think increments show better what is to be expected, see my paper on researchgate (uploaded the other day)
infectious diseases don’t spread in an even, linear fashion. On a linear scale graph, the rate of growth keeps going up and up – the line can become almost vertical and appear to go on forever. That can create the impression measures like social distancing aren’t working.
On a logarithmic scale, numbers on the Y-axis don’t move up in equal increments but instead each interval increases by a set factor – it’s often 10 but could be a factor of 3 or 350 or 3,500, anything at all. It all depends on what is deemed to be the most effective way of interpreting the data in question. The Richter scale is logarithmic – an earthquake that measures 6 is 10- times more destructive than one that measures 5.
The logarithmic scale is ideal for measuring rates of change, particularly rates of growth, explains mathematician, teacher, and author of The Life-Changing Magic of Numbers, Bobby Seagull.
It “flattens out the rate of growth so it becomes easier to see,", he says. "On a logarithmic graph of COVID-19 infections, even though the overall numbers are still increasing, you can see the point at which the rate of growth starts to level off when that exponential growth has stopped."
At that point, the logarithmic scale makes it possible to see when public health measures are starting to have the desired effect.
This is what the COVID-19 situation in China looks like when plotted on a linear graph
I do not think your statement is correct. It starts exponential, but the exponent depends on the number of contacts, among other factors, and one sees clearly a slowing down when contacts are diminished. This is so in all countries for COV-19, the numbers reveal this
If you plot say death rate vs. cumulative deaths on a log-log plot you will see why it is done. You can see when exponential growth begins to go linear and then rolls over. Great way to see this inflection even before the peak of the death rate is reached. See
syage-covid19-assessment.com
This is because the increase is an exponential exponential increase, as one person can affect 16 people as an average, and therefore each person will affect 16 others. When crossing the value of 700, the increase will be in the form of mutations
The curve of infection depends on reaction of infected person and his society so the positive continuing numbers depend on person reaction with his society thats why covid-19 logarithmic
there is a very informative presentation on this on Internet
https://www.good.is/mathematician-explains-why-the-coronaviruss-exponential-growth-is-not-as-terrifying-as-it-sounds
Robert J Meier
The increments are a measure of the derivative and of course give a very good information about trends.
I think that both should be used since as well trends as absolute values are important for the analysis. For the curves I used as example here is the increment graphic which I used as well to see when the "peak" could be reached for "constant" conditions.