There is no "actual data" in your comment above. There is a claim that you make that you have graphed some data, but no graphs and no data.
Also, it doesn't take an epidemiologist to know that a non-epidemiologist should not play at epidemiology. The other poster doesn't have any responsibility to tell you "how to model the data better".
There is in http://nrg.cs.ucl.ac.uk/mjh/covid19/#w which I said matches what I've found rather well.
> The other poster doesn't have any responsibility to tell you "how to model the data better".
Yes he does,
But I'll try to help. You're looking at a graph of confirmed cases, in other words, positive test results.
That may be due to an increase in the number of infected people; or because the number of tests being performed is increasing, and therefore the percentage of infected people reported as confirmed cases is increasing; or because some positive test results (even with confirmation) are false positives. And there may be other causes that I don't know, because I'm not an epidemiologist either, just a statistics grad student.
Figuring out the the contribution of each cause is a job for the professionals.
There may be data there, but if I understand you correctly you did not have it when you made your first post.
It is therefore inadmissible evidence as to whether your first post was a reasonable thing to write.
> Yes he does,
If you have decided you want to be an epidemiologist, or at least to learn their skillset, whose responsibility is it to fulfill that desire?
I don't think there is a reasonable answer to that other than "mine."
With this in mind I think we should stop nitpicking on non-specialists who try to raise awareness of this pandemic.
Yes there might be some differences from what a specialist would have done.
Due to the speed at which the situation evolves and the inability to test everyone daily there are lots of unknowns so even a specialist may not be able to give a more much precise figure, everything is going to be a rough estimate.
This is a very serious situation and it's better to err on the caution side, people's lives depend on everyone doing their part.
Non-constructive criticism of people who raise awareness will erode people's buy-in and people will die because of this.
May I ask, what area do you work in, numerical, discrete, logic, other?
I made it clear the limits of my knowledge - which may still not excuse me, however I have to ask if you are an epidemiologist and if so, please tell me how to model the data better. And I don't mean randomly google up some papers to dump here and pretend you are an expert (unless you are).
How far can I extrapolate e^x before it becomes useless? What are the confidence limits I can use in the extrapolation? How much can I approximate the logistic function with an exponential, when as now, the cases are currently a small fraction of the population? Why is this site http://nrg.cs.ucl.ac.uk/mjh/covid19/ done by experts using log axis any different from mine using curve fitting with exponentials? Why does http://nrg.cs.ucl.ac.uk/mjh/covid19/#w say the USA is 11.5 days behind Italy whereas my amateur attemp suggest ~9 days? (and yes, I wish I'd seen these graphs before I posted) What else have I missed? Criticise freely, with reason, don't just accuse me of misinformation because I posted my fears, which others have done too, only I did the maths.
Now please excuse me while I look at the logistics curve and compare its early stages with exponentiation.