California unfortunately has a huge backlog of pending test results. The cause seems to be the private labs (Quest in particular) accepted test samples and build up a huge backlog of the earlier manually processed test samples. Other labs would push back if their queue got too long. The newer samples are run on the Roche high speed machines.
Who gets tested is a moving target. Stanford a short time ago did a free-for-all testing binge in order to collect data, but finished that and is now restricting tests to people requiring specific risk factors to give a test.
The first time I tried to get a test from another provider I just wasn't able, they didn't know of anywhere that would test me outside of hospitalization-type symptoms.
So testing is uneven and not very available, any stats need to include some metric for the criteria to get tests in the first place.
In other words, there is likely an enormous population with no symptoms or mild symptoms who couldn't get tested if they tried.
After two video appointments with separate providers I was able to get tested yesterday and the result came back negative about 22 hours later. It took me about 8 hours of effort and time to get that done, a luxury many people do not have.
The one I pay attention to is daily growth rate of confirmed cases. It can't cover people who aren't tested. But, it approximates the velocity of the problem's magnitude. And, over time it shows the acceleration --which reflects on how we are improving the situation, or not...
The good news is that the US has gone from a 30+% daily growth rate 10 days ago down to a 15% growth rate and falling. We need to keep falling into the negative rates to solve this problem.
Honestly, the most important metric is deaths, and from what I can see, the SF Bay Area has done relatively well in that metric. No overcrowded hospitals, for example.
The conspicuous lack of realistic infection data from India, coupled with the extreme challenges to containment and control there (just due to the sheer crowding) is frightening, regardless of whether the poor data is intentional or just because India is hard place to coordinate.
That the published infection and mortality rates are so low strains credulity in the extreme, especially when much smaller-population countries at similar proximity to the equator but greater distance from China have higher case rates (i.e Brazil, Ecuador, the UAE).
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.
(note: I think we need to update the cumulative counter, we'll be fixing that shortly)
@andfrob happy to get you free/unlimited access to MintData if you're interested in making similar visualizations, please DM me if this would be helpful.
Skimming the health department web sites of various counties, it doesn't look like it. Most of them just provide the basic cases and deaths numbers. Whoever compiled this at the Stanford Open Data site (https://opendata.stanforddaily.com/#/datasets/covid19_bayare...) might be doing so manually.
That would be so useful to identify hotspots within counties. Also information about new cases such as if they are working from home or are considered "essential workers". How are transmissions occurring despite all the stay at home efforts? That would help us all tighten up our collective defenses. Hopefully the governments are doing at least some rudimentary "contact tracing" efforts and we're just not getting to see the data.
Very cool. By the way did you intend for the Y-axis on the "Days since 100 cases" chart to be "Days since 100 cases"? It seems like the Y-axis is "cases" and the X-axis is "Days since 100 cases".
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.
[+] [-] pkaye|6 years ago|reply
[+] [-] grandmczeb|6 years ago|reply
[+] [-] Jommi|6 years ago|reply
[+] [-] colechristensen|6 years ago|reply
Who gets tested is a moving target. Stanford a short time ago did a free-for-all testing binge in order to collect data, but finished that and is now restricting tests to people requiring specific risk factors to give a test.
The first time I tried to get a test from another provider I just wasn't able, they didn't know of anywhere that would test me outside of hospitalization-type symptoms.
So testing is uneven and not very available, any stats need to include some metric for the criteria to get tests in the first place.
In other words, there is likely an enormous population with no symptoms or mild symptoms who couldn't get tested if they tried.
After two video appointments with separate providers I was able to get tested yesterday and the result came back negative about 22 hours later. It took me about 8 hours of effort and time to get that done, a luxury many people do not have.
[+] [-] corysama|6 years ago|reply
https://paroj.github.io/arewedeadyet/#rate
The good news is that the US has gone from a 30+% daily growth rate 10 days ago down to a 15% growth rate and falling. We need to keep falling into the negative rates to solve this problem.
[+] [-] samcheng|6 years ago|reply
[+] [-] andfrob|6 years ago|reply
There are some limited stats to the very far right side of the "SF Bay Area Actuals" sheet.
Anecdotally, Bay Area is seeing <10% positivity rates
[+] [-] danans|6 years ago|reply
That the published infection and mortality rates are so low strains credulity in the extreme, especially when much smaller-population countries at similar proximity to the equator but greater distance from China have higher case rates (i.e Brazil, Ecuador, the UAE).
[+] [-] andfrob|6 years ago|reply
I am updating it regularly.
[+] [-] pkaye|6 years ago|reply
I wish you had the new cases per day graphed for all the bay area counties because that is what I monitor.
[+] [-] denster|6 years ago|reply
We made one here from the NYT dataset on MintData [1]:
https://nyt-map.covid42.com/
(note: I think we need to update the cumulative counter, we'll be fixing that shortly)
@andfrob happy to get you free/unlimited access to MintData if you're interested in making similar visualizations, please DM me if this would be helpful.
[1] https://mintdata.com
[+] [-] testfoobar|6 years ago|reply
For example, San Diego has zipcode breakdown here: https://www.sandiegocounty.gov/content/sdc/hhsa/programs/phs...
[+] [-] et-al|6 years ago|reply
SF County - https://www.sfdph.org/dph/alerts/coronavirus.asp
San Mateo County - https://www.smchealth.org/coronavirus
Alameda County excluding Berkeley - http://www.acphd.org/2019-ncov.aspx
Berkeley - https://www.cityofberkeley.info/coronavirus/
Santa Clara County - https://www.sccgov.org/sites/phd/DiseaseInformation/novel-co...
Marin County has an (ominously named) dashboard - https://coronavirus.marinhhs.org/surveillance
[+] [-] bosswipe|6 years ago|reply
[+] [-] jhammons|6 years ago|reply
[+] [-] andfrob|6 years ago|reply
[+] [-] norifukuoka|6 years ago|reply
[+] [-] andfrob|6 years ago|reply
[+] [-] the_crocodile|6 years ago|reply
Have you been able to find data on # of tests carried out?
[+] [-] andfrob|6 years ago|reply
California does report them on aggregate, but the purpose of this sheet was to focus on the Bay Area.
[+] [-] Cactus2018|6 years ago|reply
[+] [-] savagedata|6 years ago|reply
[+] [-] starpilot|6 years ago|reply
[+] [-] kilbuz|6 years ago|reply