Understanding Intensive Care Unit (ICU) Data
This section outlines the process to evaluate current and projected ICU capacities in California counties and regions. It also summarizes the calculations and projections used to determine entrance and exit of the Regional Stay At Home Orders (RSAHO). Since ICU staff, resources, and space limit the scope of patient care in hospitals and healthcare systems, ICU-specific metrics are used to capture the overall burden on the CA healthcare system.
Furthermore, as the recent COVID-19 surge in CA has necessitated surge planning, reported ICU surge beds and patients are being followed and used to capture the contribution of surge resources to ICU capacity. Notably, % ICU availability is used to reflect % ICU capacity.
County ICU Availability
Regional ICU Availability
Regional Stay at Home Order (Historical Data)
ICU Projections
Regional Map: Projected 4-week ICU Capacity Data
Hospitals are required to submit information on the total number of available ICU beds daily. This includes both non-surge ICU beds and surge ICU beds. To calculate regional ICU availability, the total number of adult ICU beds is calculated by removing neonatal ICU beds (NICU) and pediatric ICU beds (PICU). From there, the percentage of remaining available adult ICU beds is calculated.
% ICU Availability =
100
ā (# occupied surge and non-surge ICU beds, excluding NICU and PICU
/ # occupied surge ICU beds and total # non-surge ICU beds (excl. NICU and PICU)
X 100
āPercent of ICU beds (excl. NICU and PICU) currently available at hospitals with an ED.
| āDaily calculation. Calculation excludes hospitals without an ED. 100 minus the following: # occupied surge and non-surge ICU beds (excl. NICU and PICU) / # occupied surge ICU beds and total non-surge ICU beds (excl. NICU and PICU) x 100. Occupied surge and non-surge ICU beds (excl. NICU and PICU) is the sum of surge bed ICU patients + occupied non-surge ICU beds (excl. NICU and PICU). Occupied surge ICU beds and total non-surge ICU beds (excl. NICU and PICU) is the sum of surge bed ICU patients + non-surge ICU beds (excl. NICU and PICU). Surge bed ICU patients is defined as: the daily total number of patients occupying ICU surge beds at the hospital. Occupied non-surge ICU beds (excl. NICU and PICU) is defined as: the number of adult ICU beds occupied by a patient, excluding surge beds. Non-surge ICU beds (excl. NICU and PICU) is defined as: the number of physical, staffed adult intensive care beds in the facility. If the intensive care bed is not currently staffed and equipped but is usable and has the potential to be staffed and equipped using routine available hospital resources and staffing it is counted. The same applies to a blocked intensive care bed. If the intensive care bed is currently blocked, but is a usable bed, it is counted.
|
Hospitals are required to submit information on the total number of available ICU beds daily. This includes both non-surge ICU beds and surge ICU beds. To calculate regional ICU availability, the total number of adult ICU beds is calculated by removing neonatal ICU beds (NICU) and pediatric ICU beds (PICU). From there, the percentage of remaining available adult ICU beds is calculated.
Current Calculations
% ICU Availability =
100 ā (# occupied surge and non-surge ICU beds, excluding NICU and PICU / # occupied surge ICU beds and total # non-surge ICU beds (excl. NICU and PICU) X 100
āPercent of ICU beds (excl. NICU and PICU) currently available at hospitals with an Emergency Department (ED)
| āDaily calculation. Calculation excludes hospitals without an ED. 100 minus the following: # occupied surge and non-surge ICU beds (excl. NICU and PICU) / # occupied surge ICU beds and total non-surge ICU beds (excl. NICU and PICU) x 100. Occupied surge and non-surge ICU beds (excl. NICU and PICU) is the sum of surge bed ICU patients + occupied non-surge ICU beds (excl. NICU and PICU). Occupied surge ICU beds and total non-surge ICU beds (excl. NICU and PICU) is the sum of surge bed ICU patients + non-surge ICU beds (excl. NICU and PICU). Surge bed ICU patients is defined as: the daily total number of patients occupying ICU surge beds at the hospital. Occupied non-surge ICU beds (excl. NICU and PICU) is defined as: the number of adult ICU beds occupied by a patient, excluding surge beds. Non-surge ICU beds (excl. NICU and PICU) is defined as: the number of physical, staffed adult intensive care beds in the facility. If the intensive care bed is not currently staffed and equipped but is usable and has the potential to be staffed and equipped using routine available hospital resources and staffing it is counted. The same applies to a blocked intensive care bed. If the intensive care bed is currently blocked, but is a usable bed, it is counted.
|
Historical Calculations
Actual % ICU Capacity (for entrance into RSAHO)
The preliminary ICU capacity calculations on December 3, 2020, included PICU beds and did not account for the percentage of ICU patients that were COVID-19 positive. However, between December 4, 2020 and January 25, 2021 when the RSAHO was lifted entirely, ICU capacity was standardized to reflect effective capacity in ICUs by accounting for the percentage of adult ICU patients that were COVID-19 positive patients. If a region was utilizing more than 30% of its ICU beds for COVID-19 positive patients, then its available ICU capacity was adjusted downward by 0.5% for each 1% over the 30% threshold. This was done to preserve the capacity of the ICU to accommodate patients with non-COVID-19 conditions.
ICU Occupancy =
[(non-surge occupied ICU beds, excluding NICU and PICU + surge occupied ICU beds)
/ (non-surge total ICU beds, excluding NICU and PICU + surge total ICU patients)]
X 100
Percent of adult ICU patients that are COVID-positive =
[ICU COVID-positive confirmed patients
/ (staffed ICU non-surge occupied beds, excluding NICU and PICU
+ ICU surge bed occupied bed)]
X 100
ICU Capacity =
100
ā (ICU Occupancy)
Reduction in ICU capacity due to % of adult ICU patients with COVID-19 =
(Percent of adult ICU patients that are COVID-positive - 30%) X 0.5
ICU Capacity (with correction for COVID-positive ICU patients) =
ICU Capacity ā Reduction in ICU capacity due to % of adult ICU patients with COVID-19
Projected % ICU Capacity (for exit out of RSAHO)
The 4-week projections of ICU capacity were used to determine when a county or LHO region would leave RSAHO. The projection was made for each county in a region and then summed to give a regional projection. These projections were based on a simple growth forecast of cases.
The calculation depends on four factors which are taken on the day the projection was made:
- The regional case rate (7-day average with a 7-day lag)
- The measure of COVID-19 community transmission (R-effective)
- The daily COVID-19 admission rate
- The current ICU capacity (7-day average)
The number of ICU patients at the end of 4 weeks is divided by the regional ICU bed capacity to estimate of the projected ICU bed availability in 4 weeks.
The following assumptions and values are used in the projections, and have been adjusted from time to time based on updated information from health systems:
- The projection assumes an exponential growth in new cases according to the rate given by the recent ensemble R-effective from CalCAT.
- The non-COVID hospital census is assumed to stay the same throughout the projection period.
- In order to make applicable projections, specific values were assigned to various metrics based on historical averages:
- The time interval for exponential growth used was 7 days, based on the duration an infected person is infectious
- 9% of new COVID-19 cases were hospitalized
- 12% of these new COVID-19 hospitalized cases required ICU level care
- Length of stay for hospitalized (medical/surge level of care) was 8.5 days
- Length of stay for ICU patients was 12 days.
Simple Growth Projections
Projected COVID Cases =
Current COVID Cases, 7-day lag, 7-day average X Daily COVID Case Growth, using R effective
Projected New COVID Admissions =
Projected COVID Cases, 1 weeks prior X % COVID Hospitalization Rate, based on historical #'s
Projected New ICU Admissions =
Projected New COVID Admissions X % of COVID Hospitalizations Needing ICU
Projected COVID ICU Discharges =
Projected ICU Admissions 12 Days Prior, based on length of stay
Projected Total Occupied ICU Beds =
ICU Occupied Beds, including Surge + Projected New ICU Admissions - Projected COVID ICU Discharges
Projected % ICU Available Beds =
[1 - (Projected Total Occupied ICU Beds / ICU Bed Capacity, 7-day average)] X 100
āCase Rate
| āCalculated as the average (mean) daily number of COVID-19+ cases over 7 days (based on episode date), divided by the number of people living in the county/region/state. This number is then multiplied by 100,000. Due to reporting delays, there is a 7-day lag built into this calculation. For example, for data updated through 1/22/21, the case rate will be dated as 1/15/21 and will include the average case rate from 1/9/21 - 1/15/21.
|
āR-effective
| āAlso called the effective reproduction number, represents the average number of new infections stemming from any given infection. When R-effective > 1, then the disease burden is increasing, and when R-effective < 1 then the disease burden is decreasing. CalCAT catalogues R-effective as estimated by a number of modeling groups and generates an ensemble average. To account for lagged data, the ensemble average R-effective estimate for 4 days ago is used. R-effective is used to project case growth in each county, and the county projections are aggregated for each region.
|
āICU Capacity (7-day average)
| āThe 7-day average of the number of ICU beds including surge ICU patients in a region as reported in the daily CHA survey. PICU and NICU beds are excluded, as are beds from specialty hospitals which do not have an ED.
|
Understanding how variables may affect ICU Projections:
Projected new COVID19 cases: The current reproductive number (Re) is used to project new cases over the 4-week projection period. Factors which affect the Re, can affect actual new cases which in turn affect new ICU COVID19 admissions and ICU availability. Examples of factors which can alter the Re include but are not limited to: change in compliance with masking, social distancing, gathering size, or other public health orders; changes is transmissibility of COVID19 (as with the COVID19 variants circulating in the population); changes in the virulence of COVID19 (how sick people get and how many need hospitalization).
Variation in hospital COVID care: The percentage of hospitalized patients needing ICU care, and the average length of stay used for projections are based on recent historical data from California hospitals. Any factors which may change those numbers can also change the actual number of patients with COVID-19 in 4 weeks. Examples of factors which can affect hospital care include new and more effective therapeutics or treatments which can decrease length of stay or need for ICU care.
Variations in non-COVID ICU census: The ICU projections assume non-COVID ICU census will remain the same over the duration of the 4 weeks projection. Changes in non-COVID ICU census will result in actual ICU availability that differs from projections. This can occur for various reasons, including if hospitals begin doing more elective procedures which need critical care.
Variations in ICU beds: The ICU projections assume that the number of ICU beds currently reported will be available throughout the 4 week projection period. Changes in staffed ICU beds will result in actual ICU availability that differs from projections. This can happen if current opened surge beds are closed as COVID cases and ICU demand decrease, or conversely if more surge ICU beds are opened to respond to increasing COVID cases and ICU demand.
Vaccination efforts: CDPH is evaluating available data to determine how vaccinations will affect COVID19 cases and hospitalizations.
Regional Stay at Home Order (Historical Data)
Beginning in late November 2020, California experienced the most intense surge in COVID-19 cases and hospitalizations to date. Our hospitals and front-line medical workers were stretched to their limits, which required us to take immediate action to keep our hospital capacity intact. The
Regional Stay At Home Order took effect on December 5.
Order Lifted on January 25
Californians heard the urgent message to stay home when possible and our surge after the December holidays was significant, and the order helped lessen the strain on hospitals. By late January, the curve was flattening, with case rates, case positivity, the rate of transmission, hospital admissions all on the decline and ICU admissions inching downward. At the same time, our medical surge efforts bolstered our hospital system with additional staff, space and supplies.
With regional four-week ICU projections above 15 percent availability and consistent,
CDPH ended the Regional Stay at Home Order statewide, effectively lifting the order in Southern California, the San Joaquin Valley and Bay Area. The
Limited Stay at Home Order (curfew) also ended with the exit of all regions from the Regional Stay at Home Order. This action allowed all counties statewide to return to the rules and framework of the Blueprint for a Safer Economy and color-coded tiers that indicate which activities and businesses are open based on local case rates and test positivity.
Understanding the Data
Entering and Exiting the Order
Regions entered the order when their current ICU capacity dropped below 15%. To exit the Regional Stay at Home Order, a region must have a four-week projected ICU capacity of equal to or more than 15%.
Background on ICU Capacity Calculations
Hospitals are required to submit information on the total number of available staffed ICU beds daily. This includes both existing staffed ICU beds and staffed ICU surge beds. To calculate regional ICU capacity, the total number of adult ICU beds is calculated by removing neonatal ICU beds (NICU) and pediatric ICU beds (PICU). From there the percentage of remaining available adult ICU beds is calculated.
This ICU capacity measure is standardized to reflect effective capacity in ICUs by looking at the percentage of COVID-19 positive patients in the ICU. If a region is utilizing more than 30% of its ICU beds for COVID-19 positive patients, then its available ICU capacity is adjusted downward by 0.5% for each 1% over the 30% threshold. This is done to preserve the capacity of the ICU to also treat non-COVID-19 conditions. The ICU is an important tool to save lives for those with COVID-19 and other critical medical conditions such as cancer, heart attacks and strokes. If a disproportionate number of ICU beds are being utilized to treat COVID-19 patients, then patients with non-COVID medical issues may not be receiving or be able to receive the level of care they need.
The preliminary ICU capacity calculations on December 3, 2020, included PICU beds and did not account for percentage of COVID-19 positive patients. As of December 4, 2020, the ICU capacity metric is being calculated as presented here.
Background on Four-Week ICU Capacity Projections
Projected ICU capacity is based on four factors: current estimated regional ICU capacity available, measure of current community transmission (R-effective), current regional case rates (7-day average with a 7-day lag) and the proportion of cases being admitted to the ICU. (See figure below.)
The projected number of ICU patients is used to calculate projected ICU capacity by using a static (not a projected number) denominator of staffed ICU beds to arrive at an estimate of % ICU available in 4 weeks.
ICU projections were first generated on December 28 when the first two regions (San Joaquin Valley and Southern California) placed under the order met the minimum three weeks before being eligible to exit.
Total staffed ICU beds was not initially fully captured in the California Hospital Association's survey and has fluctuated throughout January as the survey was adjusted on Jan 8 to include that variable. Projections of ICU bed availability are dependent on hospital reported data including ICU patients and ICU beds. Under-reporting of available ICU beds would lead to under-reporting of ICU bed availability, and conversely, over-reporting of available ICU beds (beds that are not staffed) would lead to over-reporting of ICU bed availability. When first introduced to the hospital survey on Jan 8, irregular reporting of "surge ICU beds" resulted in inconsistent and wide variability across hospitals, initially, and concerns while inconsistent that they would lead to unreliable projections of ICU bed availability using that variable.
The calculations of % ICU available 4 weeks out was adjusted to include revised input from hospitals regarding total staffed beds on and after January 11.
Other parameters that changed over time in the projections include:
- On January 4, we noted that testing volume and case numbers had fluctuated dramatically over the Christmas and New Year's holidays leading to very low case rates which we were likely not reflective of actual levels of cases and disease and potentially an artificiality of the low testing patterns seen two weeks in a row. (We subsequently noted cases did increase again and that this concern was warranted).
- On January 21, we were still evaluating surge bed data and also had recently noted a precipitous drop in daily new case rates. We wanted to follow this for a few more days to ensure it was not an anomaly and a true decrease in cases versus an artificially low number of cases due to low testing, for example, before relying on projections based on those dates.
Projection Start to End Date:
12/28/2020 ā 1/25/2021
Date Projection was Run:
12/28/2020
Bay Area
| 14.8
| 47.3 | 1.1 | 3.7 |
| Greater Sacramento | 18.4
| 54.5 | 1.0 | 8.7 |
| Northern California | 27.1 | 42.7 | 1.0 | 12.1 |
| San Joaquin Valley | (0.2) | 82.6 | 1.1
| (43.1) |
| Southern California | (1.3) | 117.7 | 1.1 | (40.9) |
Projection Start to End Date:
12/30/2020 ā 1/27/2021
Date Projection was Run:
12/30/2020
| Bay Area | 13.9 | 52.1 | 1.1 | 2.6 |
| Greater Sacramento | 18.3 | 55.6 | 1.0 | 8.6 |
| Northern California | 30.1 | 42.1 | 1.0 | 15.9 |
| San Joaquin Valley | (5.3) | 88.2 | 1.1 | (35.7) |
| Southern California | (3.3) | 129.7 | 1.1 | (36.7) |
Projection Start to End Date:
1/4/2021 ā 2/1/2021
Date Projection was Run:
1/4/2021
| Bay Area | 16.6 | 44.7 | 1.0 | 17.3 |
| Greater Sacramento | 19.7 | 44.0 | 1.0 | 25.9 |
| Northern California | 30.4 | 36.2 | 1.0 | 24.6 |
| San Joaquin Valley | (3.7) | 63.9 | 1.0 | 6.4 |
| Southern California | (5.3) | 101.6 | 1.0 | (4.6) |
Projection Start to End Date:
1/7/2021 ā 2/4/2021
Date Projection was Run:
1/7/2021
| Bay Area | 10.1 | 52.4 | 1.0 | 7.0 |
| Greater Sacramento | 13.6 | 51.4 | 1.0 | 13.8 |
| Northern California | 24.8 | 41.3 | 1.0 | 15.4 |
| San Joaquin Valley | (8.3) | 72.8 | 1.0 | (3.8) |
| Southern California | (7.4) | 115.6 | 1.0 | (12.1) |
Projection Start to End Date:
1/11/2021 ā 2/8/2021
Date Projection was Run:
1/11/2021
| Bay Area | 11.5 | 53.3 | 1.0 | 7.2 |
| Greater Sacramento | 19.9 | 53.2 | 1.0 | 19.2 |
| Northern California | 36.1 | 40.6 | 1.0 | 24.3 |
| San Joaquin Valley | 5.6 | 78.7 | 1.0 | 7.4 |
| Southern California | 2.4 | 121.6 | 1.0 | (3.0) |
Projection Start to End Date:
1/14/2021 ā 2/8/2021
Date Projection was Run:
1/14/2021
| Bay Area | 16.5 | 57.7 | 1.1 | 7.9 |
| Greater Sacramento | 16.9 | 54.8 | 1.0 | 13.3 |
| Northern California | 18.4 | 42.1 | 1.0 | 4.4 |
| San Joaquin Valley | 3.9 | 84.2 | 1.0 | (6.4) |
| Southern California | 6.0 | 124.7 | 1.0 | (0.7) |
Projection Start to End Date:
1/18/2021 ā 2/15/2021
Date Projection was Run:
1/18/2021
| Bay Area | 14.0 | 59.0 | 1.0 | 4.9 |
| Greater Sacramento | 18.2 | 49.4 | 1.0 | 18.8 |
| Northern California | 23.7 | 39.8 | 1.0 | 13.7 |
| San Joaquin Valley | 7.2 | 86.4 | 1.0 | (3.3) |
| Southern California | 6.3 | 121.3 | 1.0 | 3.1 |
Projection Start to End Date:
1/21/2021 ā 2/18/2021
Date Projection was Run:
1/21/2021
| Bay Area | 13.8 | 48.3 | 1.0 | 13.9 |
| Greater Sacramento | 15.9 | 40.8 | 1.0 | 24.0 |
| Northern California | 27.0 | 36.4 | 1.0 | 20.6 |
| San Joaquin Valley | 9.3 | 70.1 | 1.0 | 10.0 |
| Southern California | 7.6 | 90.9 | 0.9 | 22.2 |
Projection Start to End Date:
1/24/2021 ā 2/21/2021
Date Projection was Run:
1/24/2021 (Order lifted on 1/25/2021)
| Bay Area | 15.2 | 38.2 | 0.9 | 25.0 |
| Greater Sacramento | 14.7 | 34.1 | 0.9 | 27.3 |
| Northern California | 25.2 | 30.7 | 0.9 | 18.9 |
| San Joaquin Valley | 8.5 | 56.6 | 0.9 | 22.3 |
| Southern California | 9.9
| 73.0 | 0.9 | 33.3
|
Projection Start to End Date:
2/2/2021 ā 3/2/2021
Date Projection was Run:
2/2/2021
| Bay Area | 18.1 | 24.1 | 0.82 | 33.3 |
| Greater Sacramento | 18.4 | 22.6 | 0.84 | 31.4 |
| Northern California | 24.4 | 10.4 | 0.87 | 29.2 |
| San Joaquin Valley | 10.7 | 34.3
| 0.80 | 35.1 |
| Southern California | 9.1 | 42.3 | 0.77 | 43.7
|
Projection Start to End Date:
2/8/2021 ā 3/8/2021
Date Projection was Run:
2/8/2021
| Bay Area | 21.6 | 16.0
| 0.77 | 39.6 |
| Greater Sacramento | 19.5
| 14.8
| 0.76 | 35.1 |
| Northern California | 36.0
| 14.3
| 0.81 | 37.6 |
| San Joaquin Valley | 10.5 | 24.5
| 0.79 | 38.8 |
| Southern California | 10.6 | 26.5
| 0.73 | 46.3
|
Projection Start to End Date: 2/15/2021 ā 3/15/2021
Date Projection was Run: 2/15/2021
| Bay Area | 24 | 16.8 | 0.76 | 36.5 |
| Greater Sacramento | 22.4 | 16.4 | 0.8 | 29 |
| Northern California | 33.3 | 16.6 | 0.76 | 32.9 |
| San Joaquin Valley | 13 | 26.1 | 0.77 | 38.5 |
| Southern California | 14.8 | 26.6 | 0.67 | 44.8
|
Projection Start to End Date: 2/22/2021 ā 3/22/2021
Date Projection was Run: 2/22/2021
| Bay Area | 25.4 | 7.8 | 0.72 | 35.5 |
| Greater Sacramento | 24.0 | 9.1 | 0.77 | 31.5 |
| Northern California | 33.6 | 7.6 | 0.74 | 34.9 |
| San Joaquin Valley | 16.8
| 11.9 | 0.75 | 41.6 |
| Southern California | 19.5 | 8.5 | 0.63 | 45.2 |
Projection Start to End Date: 3/1/2021 ā 3/29/2021
Date Projection was Run: 3/1/2021
| Bay Area | 27.8 | 6.9
| 0.75 | 38 |
| Greater Sacramento | 23.5 | 7.8
| 0.77 | 29.5 |
| Northern California | 36.4
| 7.5
| 0.78 | 36.4 |
San Joaquin Valley
| 18.3
| 10.2
| 0.77 | 34.6 |
Southern California
| 25.3
| 6.3
| 0.68 | 40.1
|
Projection Start to End Date: 3/8/2021 ā 4/5/2021
Date Projection was Run: 3/8/2021
| Bay Area | 27.2 | 5.2 | 0.74 | 34.8 |
| Greater Sacramento | 23.1 | 5.8 | 0.75 | 32.5 |
| Northern California | 37.3 | 4.9 | 0.75 | 28.5 |
| San Joaquin Valley | 21.3 | 7.6 | 0.7 | 36.1 |
| Southern California | 27.6 | 4.5 | 0.68 | 40.3 |
Projection Start to End Date: 3/15/2021 ā 4/12/2021
Date Projection was Run: 3/15/2021
| Bay Area | 27.5 | 4.2 | 0.73 | 33.0 |
| Greater Sacramento | 28.2 | 5.2 | 0.74 | 33.4 |
| Northern California | 25.8 | 4.8 | 0.75 | 31.2 |
| San Joaquin Valley | 21.0 | 7.2 | 0.72 | 34.0 |
| Southern California | 30.5 | 4.1 | 0.62 | 41.3 |
Projection Start to End Date: 3/22/2021 ā 4/19/2021
Date Projection was Run: 3/22/2021
| Bay Area | 30.3 | 3.8 | 0.80 | 30.2 |
| Greater Sacramento | 27.1 | 5.5 | 0.84 | 28.1 |
| Northern California | 29.1 | 4.5 | 0.78 | 30.7 |
| San Joaquin Valley | 20.1 | 7.0 | 0.86 | 28.9 |
| Southern California | 31.8 | 3.1 | 0.71 | 37.8 |
Projection Start to End Date: 3/29/2021 ā 4/26/2021
Date Projection was Run: 3/29/2021
| Bay Area | 28.0 | 3.6 | 0.83 | 32.9 |
| Greater Sacramento | 25.8
| 8.2 | 0.90 | 26.8 |
| Northern California | 33.1 | 5.0 | 0.88 | 35.6 |
| San Joaquin Valley | 22.8 | 6.0 | 0.85 | 28.7 |
| Southern California | 32.7 | 3.7 | 0.75 | 38.4
|
Projection Start to End Date: 4/5/2021 ā 5/3/2021
Date Projection was Run: 4/5/2021
| Bay Area | 33.4 | 4.1 | 0.85 | 33.1 |
| Greater Sacramento | 27.8 | 7.6 | 0.96 | 25.1 |
| Northern California | 33.6 | 5.3 | 0.82 | 33.2 |
| San Joaquin Valley | 21.3 | 6.4 | 0.84 | 29.5 |
| Southern California | 32.1 | 3.4 | 0.84 | 37.2
|
Projection Start to End Date: 4/12/2021 ā 5/10/2021
Date Projection was Run: 4/12/2021
| Bay Area | 33.3 | 4.0 | 0.86 | 33.7 |
| Greater Sacramento | 28.9 | 7.1 | 0.95 | 28.1 |
| Northern California | 34.9
| 4.7 | 0.83 | 33.2 |
| San Joaquin Valley | 21.5 | 5.0 | 0.83 | 31.4 |
| Southern California | 33.3 | 3.6 | 0.87 | 36.1
|
Projection Start to End Date: 4/19/2021 ā 5/17/2021
Date Projection was Run: 4/19/2021
| Bay Area | 30.7 | 4.6 | 0.89 | 27.7 |
| Greater Sacramento | 29.5 | 7.8 | 0.94 | 28.6 |
| Northern California | 34.6 | 5.5 | 0.92 | 34.4 |
| San Joaquin Valley | 22.5 | 4.8 | 0.83 | 27.1 |
| Southern California | 35.5 | 3.7 | 0.88 | 40.6
|
Projection Start to End Date: 4/26/2021 ā 5/24/2021
Date Projection was Run: 4/26/2021
| Bay Area | 31.9 | 4.2 | 0.89 | 32.5 |
| Greater Sacramento | 30.3 | 7.3 | 0.92 | 30.3 |
| Northern California | 27.3 | 7.0 | 0.95 | 29.3 |
| San Joaquin Valley | 21.7 | 4.9 | 0.84 | 28.2 |
| Southern California | 33.0 | 3.3 | 0.87 | 34.2
|
Projection Start to End Date: 5/03/2021 ā 5/31/2021
Date Projection was Run: 5/03/2021
| Bay Area | 33.9 | 3.5 | 0.84 | 33.4 |
| Greater Sacramento | 28.4 | 6.4 | 0.89 | 30.6 |
| Northern California | 34.9 | 6.6 | 0.92 | 25.9 |
| San Joaquin Valley | 23.2 | 5.2 | 0.85 | 30.4 |
| Southern California | 34.4 | 2.7 | 0.85 | 36.2
|
Projection Start to End Date: 5/10/2021 ā 6/07/2021
Date Projection was Run: 5/10/2021
Bay Area
| 34.9 | 3.1 | 0.84 | 38.1 |
| Greater Sacramento | 30.1 | 7.1 | 0.97 | 25.8 |
| Northern California | 29.5 | 8.3 | 0.93 | 24.3 |
| San Joaquin Valley | 19.9 | 4.8 | 0.85 | 27.9 |
| Southern California | 36.2 | 2.4 | 0.88 | 35.7
|
Projection Start to End Date: 5/17/2021 ā 6/14/2021
Date Projection was Run: 5/17/2021
| Bay Area | 34.8 | 2.4 | 0.80 | 36.5 |
| Greater Sacramento | 31.4 | 5.2 | 0.86 | 33.0 |
| Northern California | 34.9 | 7.2 | 0.90 | 33.1 |
| San Joaquin Valley | 22.8 | 3.6 | 0.85 | 29.5 |
| Southern California | 33.9 | 2.1 | 0.87 | 35.4
|
Projection Start to End Date: 5/24/2021 ā 6/21/2021
Date Projection was Run: 5/24/2021
| Bay Area | 34.6 | 1.8 | 0.77 | 35.6 |
| Greater Sacramento | 29.3 | 3.8 | 0.81 | 32.2 |
| Northern California | 44.2 | 7.4 | 0.92 | 37.4 |
| San Joaquin Valley | 23.5 | 3.1 | 0.81 | 27.4 |
| Southern California | 34.6 | 1.7 | 0.84 | 36.7
|
Projection Start to End Date: 5/31/2021 ā 6/28/2021
Date Projection was Run: 5/31/2021
| Bay Area | 33.1 | 1.5 | 0.75 | 32.6 |
| Greater Sacramento | 28.0 | 3.5 | 0.78 | 27.1 |
| Northern California | 26.6 | 5.5 | 0.83 | 38.1 |
| San Joaquin Valley | 29.7 | 2.5 | 0.77 | 34.7 |
| Southern California | 36.8 | 1.2 | 0.78 | 37.9
|
Projection Start to End Date: 6/7/2021 ā 7/5/2021
Date Projection was Run: 6/7/2021
| Bay Area | 30.3 | 1.5 | 0.80 | 35.4 |
| Greater Sacramento | 25.6 | 2.8 | 0.81 | 27.3 |
| Northern California | 37.0 | 2.6 | 0.77 | 48.1 |
| San Joaquin Valley | 27.4 | 1.9 | 0.79 | 29.0 |
| Southern California | 37.4 | 1.0 | 0.82 | 38.1
|
Projection Start to End Date: 6/14/2021 ā 7/12/2021
Date Projection was Run: 6/14/2021
| Bay Area | 32.6 | 1.8 | 0.85 | 32.6 |
| Greater Sacramento | 26.3 | 3.4 | 0.84 | 27.3 |
| Northern California | 37.5 | 4.7 | 0.84 | 45.7 |
| San Joaquin Valley | 28.8 | 2.2 | 0.82 | 33.3 |
| Southern California | 37.2 | 1.2 | 0.81 | 36.7 |