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County Data Monitoring

Step 1: Active Data Monitoring

County Data Chart

Understanding the Data Being Monitored

When reviewing the data, a few assumptions should be noted, such as: 1) COVID positive case rates amongst state and federal prison inmates are not included in the case rate; 2) increasing hospitalization and limited hospital capacity data may represent the county accepting patients from neighboring jurisdictions or increase in testing; and, 3) testing data may help explain or provide context for interpreting the elevated disease transmission data. All of these key assumptions and the extent to which a county's data is above the threshold level would factor into CDPH's targeted engagement with local health departments. Data in the county table and link is presented by county, which encompasses the city Pasadena, Long Beach, and Berkeley, who have their own city health departments.

As described above, the data and metrics monitored here should be viewed as supplemental to the triggers for modifications outlined by the county and not a replacement for metrics used in their local containment plans. For disease transmission and increasing hospitalization metrics, the data is provided over a different range of time than what was requested by the state for the variance attestations.

Elevated Disease Transmission (Source: CalRedie):

The 14-day case rate (without prison cases) and 7-day testing positivity rate are used to assess the level of COVID-19 burden in a county.  For each measure, the higher the number, the more a county is impacted by COVID-19.  However, it is important to look at this data in the context of average number of tests per day, as well as who is being tested.  In general, higher number of tests per day indicates more widespread testing for COVID-19 beyond individuals who have symptoms.  This means that more individuals who either do not have COVID-19 or have COVID-19 but are asymptomatic will be tested.  As a result, as the number of tests per day increases, the case rate may increase (due to the identification of asymptomatic cases) and the testing positivity rate may decrease (due to more testing among individuals who do not have COVID-19).

A county is flagged for elevated disease transmission criteria if:

1)   Case rate (per 100,000) >100

OR

2)   Case rate (per 100,000) >25 AND testing positivity >8.0% 

14-day case rate (without prison cases): The total number of cases diagnosed and reported over a 14-day period divided by the number of people living in the county.  This number is then multiplied by 100,000.   Due to reporting delay, there is a 3-day lag.  For example, a case rate calculated on April 1st would correspond to cases occurring from March 15th - March 28th.  Although case rates are often calculated using the date they were reported to the health department, this measure uses the episode date.  The episode date is the earliest of several dates and corresponds to the earliest date that the case can be known to have had the infection. 

7-day testing positivity: The total number of positive polymerase chain reaction (PCR) tests divided by the total number of PCR tests conducted.  This number is then multiplied by 100 to get a percentage.   Due to reporting delay (which may be different between positive and negative tests), there is a 7-day lag.  For example, a case rate calculated on April 1st would correspond to specimens collected between March 18th - March 24th.

Increasing Hospitalizations (Source: California Hospital Association Survey):

Monitoring changes to the number of individuals who are hospitalized for COVID-19 is another way to assess the burden of COVID-19 in a county.  If more people are being hospitalized for COVID-19, it is likely that disease transmission is increasing, although increases in hospitalization rates are likely to lag by approximately two weeks.  Unlike the case rate or testing positivity rate, the number of people hospitalized for COVID-19 is less likely to be influenced by how much testing is occurring. However, the number of patients currently hospitalized for COVID-19 may be influenced by a number of factors including: how long someone is hospitalized for COVID-19, whether hospitals in a county have accepted patient transfers from other counties, and who is being infected by COVID-19 (people who are older or have certain underlying medical conditions are more likely to require hospitalization). 

A county is considered to meet the increasing hospitalization criteria if:

1)   >10% increase in the average number of confirmed COVID-19 patients hospitalized

Percent change in confirmed COVID-19 patients hospitalized: Calculated by comparing the average number of laboratory confirmed COVID-19 patients hospitalized over the past 3 days to the 3 days prior.  For example, a number calculated on April 1st would compare the average number of patients hospitalized on March 29th, 30th, 31st to the average number of confirmed patients hospitalized on March 26th, 27th, and 28th. Counties with an average of <20 laboratory confirmed COVID-19 patients hospitalized over the past 3 days are not considered to meet the increasing hospitalization criteria.

Limited Hospital Capacity (Data Source: California Hospital Association Survey):

If a county is experiencing increased transmission rates and increases in hospitalization, it is important to monitor whether there is sufficient remaining capacity in the health care system to care for patients in the county.  In addition to overall hospital capacity, other key indicators of hospital capacity include availability of intensive care unit (ICU) beds and ventilators.

A county is considered to meet the limited hospital capacity if:

1)   <20% of staffed ICU beds are available

OR

2)   <25% of ventilators are available

ICU Bed Availability: The total number of available ICU beds divided by the total number of staffed ICU beds. This number is then multiplied by 100 to get a percentage. NICU beds are excluded from this calculation.

Ventilator Availability: The total number of available ventilators divided by the total number of ventilators.  This number is then multiplied by 100 to get a percentage.

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