Another important data point to assess testing is Case Fatality Rate (CFR). This is about 2.5% in the SF Bay Area.
In other places with higher testing, such as Australia, the CFR is 0.6% or less. This implies that the true number of cases is 4-5 times higher... probably a lot more.
It seems like this disease is so successful because of a significant symptom-free-but-contageous period followed by a small percentage of very serious symptoms.
That's what a pandemic needs. If it is very deadly very quickly it kills its transmission vectors before they can transmit. If it is entirely symptom free, it is very evolutionarily successful, but no one cares because there aren't any negative effects.
There is an "optimum" of disease characteristics for maximum damage and we seem to be experiencing one.
The bottom line is that it seems to be very difficult to prevent a majority of the world population from getting this disease and the result is going to be a global fatality rate of somewhere in the neighborhood of 1%.
What put it into perspective for me is the CDC estimate of up to 25% cases being entirely asymptomatic [1], and data from Iceland shows 50% of those tested were asymptomatic at time of testing [2].
It will be hard to trace and isolate if this is the case.
That also doesn't account for the exponential growth in number of cases; the people dying now are out of a much smaller cohort of confirmed cases in the past.
Deaths / (Deaths + Recoveries) would be more like it, and that's a scary number.
Very, very limited data on the Bay Area. Under the "SF Bay Area Actuals" you can scroll all the way to the right you will see what I have been able to find.
California does report them on aggregate, but the purpose of this sheet was to focus on the Bay Area.
I developed this for myself but data junkies trying to get a feel for what is happening with the coronavirus spread across the San Francisco Bay Area will appreciate it.
Where are you getting the raw data? I'm extracting it from the New York Times dataset for my own graphing. They have the data for all counties in the US. I've been meaning to automate the graphing but for now doing it manually.
I wish you had the new cases per day graphed for all the bay area counties because that is what I monitor.
Raw data was originally from SF Chronicle, but they removed their timelapse view so I am now getting it direct from county websites. Stanford Open Data project also has a reasonable historical dataset that comes from the county websites.
To clear up some confusion around TinyMCE and Textbox.io. The products came to be under the same umbrella due to the merger of Ephox and Moxiecode. The combined company was renamed Tiny last year.
TinyMCE version 5, released earlier this year, incorporated much of the Textbox.io features and technology and is the main product moving forward. It is better than Textbox.io in almost every way now and is recommended for new projects.
Tiny did indeed raise $4M in venture capital last year. It has not been squandered by any means. In fact, we have only just started spending it as we were profitable and growing when we first raised the money.
Tiny has a good-sized development team with more than 30 people in engineering, QA, design and product management. Of the many options out there, TinyMCE is a good bet!
