Charts included with this update
- VS2 – Vital Stats – Southern California
- VS3 – Southern California Snapshot
- CH1 – LA County Hospitalizations
- CH2 – San Diego County Hospitalizations
- CH3 – Orange County Hospitalizations
- CH4 – Riverside County Hospitalizations
- CH5 – Ventura County Hospitalizations
- CH6 – Kern County Hospitalizations
- FAQ’s 1, 2, 3, & 4
I’ve added to the FAQ’s. FAQ #2 now has an explanation of the Prevalence Index. FAQ #3 has an explanation of the hospital utilization charts, which you’ll see today for the first time. It also has an explanation of the colors and range limits used on the snapshot table for Southern California [VS3]. Snapshot #4 has sources and notes, including sources for hospitalization data. Common definitions are now on FAQ #4. I’ll post these FAQ’s with every update. If you have any questions about the charts or calculations, please look at the FAQ’s first; your answer might be there.
Also, I wanted to clear up something about the links to the raw data and the charts. These links are to url’s created by Google for published spreadsheets. They are not user friendly. There’s no navigation, no row numbers, and they load very slowly. They are there strictly for those who would like to see the raw data and what is there. Please don’t draw any conclusions from those links about how I do my updates, though. They are just crude windows into the raw data, nothing more.
About the Hospitalization Charts – CH1 – CH6
You may have guessed the theme of this update: hospital data. Since the charts here are new, I’m going to explain them as best I can.
I get 4 pieces of data form the CA DHHS: patients confirmed, patients suspected, ICU confirmed, and ICU suspected. The numbers are for that day only; they are not cumulative, and I have no way to get those numbers. The ICU numbers are included in the “patient” numbers.
I combine the confirmed and suspected into a single number for “hospitalized” and the confirmed and suspected ICU into “ICU”. Then I do a 7 day moving average to smooth out the noise from day to day.
Why do we care about hospitalization numbers? Because we all saw what happened in NY, when hospitals got overwhelmed. Once that happens, the entire health care system is effectively shut down, and that is a disaster, resulting in more lives lost, not just from CV19, but from other medical emergencies that can no longer be handled.
So bed utilization rates are critical. Sadly, there are no easily accessible statistics on this. We all know that the number of licensed hospital beds and ICU beds can vary from week to week, but there’s no way to keep track of that. So I had to use static numbers from the CA Hospital Assn. and KPBS. From these sources, I got licensed hospital beds for each county, as well as licensed ICU beds.
The next question is what percentage of these beds are utilized. To get that, I consulted various sources, and the consensus is that around 60% to 65% of licensed beds are utilized during normal times. The utilization for ICU beds runs a bit higher — around 68%.
That means that if CV19 patients take up 20% of available beds, we are near a crisis point. Why? For a couple of reasons. First, hospitals don’t hire staff for 100% utilization; they hire for the utilization rate that’s typical for them. So if there’s a surge of new patients, that means more overtime, longer shifts, no vacations, etc., and eventually hiring. Second, CV19 patients put an incredible amount of stress on a hospital — PPE, isolation of patients, long stays, etc. Look at one of the YouTube videos from Bergamo and you’ll see what I mean.
From everything I’ve been able to read about it, a untilization rate of under 10% for regular CV19 patients and 15% for ICU patients is manageable. Anything above that results in stress on the system, and utilization rates at 25% and above are danger indicators.
Let me make one thing clear: I am not a hospital administrator, virologist, epidemiologist, scientist, etc. I am not an expert. I’m putting together data and giving you my interpretation of it. If any of you out there are experts, and see something I’ve got wrong, please correct me; I’m anxious to learn and get it right.
Back to the charts. There are five pieces of information.
- Daily case counts based on a 7 day moving average
- Daily patient counts, based on 7 day avg.
- Daily icu counts based on 7 day avg.
- Daily hospital utilization rate, based on dividing daily patient counts into licensed beds for that county.
- Daily ICU utilization rates, based on dividing daily icu counts into licensed icu beds for that county.
Each chart has two vertical axes. The left axis represents the daily counts; the right axis the rates.
What do these charts tell us?
- If case counts are increasing, they can help answer whether they are rising because of increased testing. If that’s the case, then you will probably see stable or falling hospitalization and icu rates. If those rates are rising, you know more people are getting sick, because getting a test doesn’t cause you to be hospitalized.
- They give us a good indication of how safe it is to open up and relax restrictions. Keeping in mind that the one of the main purposes of these restrictions in the first place was to preserve the hospital system, opening up the economy depends on utilization rates that are in the “safe zone.”
I’m offering this commentary as a theory, in a way. It makes sense to me, but I hope that those of you out there with direct experience will set me straight.
LA County [CH1]
Cases show an upward trend, but hospitalizations as well as icu’s are going down. This may indicate that what the county has been saying, i.e. that the increased case count is a result of more testing, is true. Not only that, but hospital utilization rate (HUR) and icu utilization rates (IUR) are declining slightly. The HUR went from 8% 2 weeks ago to 7% today, and the IUR declined from a very high 22% to 18% today.
San Diego County [CH2]
The trend line for cases is slightly upward, but mostly flat. Hospitalizations and ICU’s have declined slightly. The HUR has been steady at 5%, and the IUR has declined from a high of 19% a couple of weeks ago to 17% today.
Orange County [CH3]
Mostly, this is the same situation as that in San Diego – almost flat case trend lines, slightly higher hospitalizations. The troubling thing here is the IUR, which has gone from 16% two weeks ago to 20% today.
Riverside County [CH4]
Here again we have sharply rising cases, but not mirrored in hospitalizations — yet. Since the incubation period is up to 3 weeks, this may still happen. Indeed there is a slight increase in hospitalizations, but the increase is only about 20 per day over a two week period. The HUR and IUR remain relatively flat.
Ventura County [CH5]
Very much like Riverside, but here the increase in hospitalizations is slightly more pronounced, from 277 three weeks ago to 322 today. The HUR and IUR are flat.
Kern County [CH6]
This is the chart that could indicate some real trouble ahead. The absolute numbers are not huge, but the trend lines are moving upward more or less in unison. Over the past three weeks, cases have doubled, hospitalizations have doubled, and ICU’s have gone up by around 40%. The HUR is very high, at 25%. If their pre-pandemic HUR was 65%, and we add another 25% to that, it would give us an overall HUR of 90%. That doesn’t leave any wiggle room.
I’ve included the Vital Statistics tables just to keep you updated; discussion on that tomorrow.
Stay healthy and safe, everyone.
Donations: quite a few of you have offered various types of donations to show your appreciation for these updates. I have everything I need, so I’d rather you contribute to a great cause instead. The link below is to donate to the Black Visions Collective in Minneapolis. Sorry, no bank accounts, just credit cards.