I think the model uses a much shorter time for active infections than 2.5 weeks. Not sure what it is, but I think it’s closer to 5 days or something like that, which seems to actually fit the behavior of the disease best, on a broad scale.
Agree that it looks weird. I’ve asked the authors of the project to add a cumulative graph, which makes these assumptions a lot clearer.
Wait, so your graph shows the number of people having their 2-day “infectious period” at any given time, which could be much lower than the number of people infected at a given time? That doesn’t seem to be explained on the page.
Anyway, I think the really important number is how many people are having their “required hospitalization period” at any given time (which is longer than 2 days). Maybe you could show that too, since you’re already showing the “care capacity” line?
I think the model uses a much shorter time for active infections than 2.5 weeks. Not sure what it is, but I think it’s closer to 5 days or something like that, which seems to actually fit the behavior of the disease best, on a broad scale.
Agree that it looks weird. I’ve asked the authors of the project to add a cumulative graph, which makes these assumptions a lot clearer.
We used parameters based on a paper modelling Wuhan, that found that ~2 day infectious period predicted spread the best.
Adding cumulative statistics is in the pipeline; I or one of the devs might get around to it today.
Wait, so your graph shows the number of people having their 2-day “infectious period” at any given time, which could be much lower than the number of people infected at a given time? That doesn’t seem to be explained on the page.
Anyway, I think the really important number is how many people are having their “required hospitalization period” at any given time (which is longer than 2 days). Maybe you could show that too, since you’re already showing the “care capacity” line?