COVID-19 vaccines have been proven to be safe and effective. However, no vaccines are 100% effective at preventing illness in vaccinated people. There will be a small percentage of fully vaccinated and boosted people who still get sick, are hospitalized, or die from COVID-19. These are called “breakthrough cases.” Fortunately, there is evidence that vaccination may make breakthrough cases less severe and people who are fully vaccinated may be less likely to spread the disease to others.
Fully Vaccinated Breakthrough Case: A person who tests positive for COVID-19 14 days or more after they have completed the full series of an approved or authorized COVID-19 vaccine and who has not had a bivalent booster dose yet. People who were fully vaccinated 14 days before testing positive for COVID-19 and received a bivalent booster within 14 days before testing positive for COVID-19 are counted as Fully Vaccinated. People who completed their primary series and received a monovalent booster, but not a bivalent booster, are considered Fully Vaccinated.
Bivalent Booster Breakthrough Case: A person who tests positive for COVID-19 14 days or more after receiving an approved or authorized bivalent booster COVID-19 vaccine after completing the full series on or after September 15th, 2022. Booster data and rates are analyzed starting September 15th, 2022, two weeks after the date boosters became available to those 18 years and older (September 1st, 2022).
Unvaccinated Case: A person who tests positive for COVID-19 and who is not fully vaccinated or boosted yet. This includes people who have not had any doses of a COVID-19 vaccine, those who have only had one dose of the Moderna or Pfizer vaccine, or those for whom 14 days have not passed between their positive COVID-19 test and their last dose in a primary vaccine series.
The Utah Department of Health and Human Services determines vaccine status for cases using two methods: by automatically linking known cases to vaccination records reported into the Utah Statewide Immunization Information System (USIIIS), and through self-report by asking interviewed cases if they have been fully vaccinated. Breakthrough cases may be under-represented if there is incomplete or incorrect data to link a person to their USIIS record, or if case investigators are unable to conduct an interview.
Data Reliability: Recent availability and use of at-home has caused only a small portion of tests to be reported to DHHS. The tests that are reported are from people tested by healthcare providers or at testing sites. People who are tested at these sites are likely not similar to the general population, with more older adults and people with complex medical conditions testing at these locations. These populations are also more likely to be vaccinated. This bias in test reporting affects our ability to accurately calculate vaccine efficacy. DHHS now shows data collected since the bivalent booster became available (09/15/2022) as top level vaccine efficacy measures. 28-day rates are still available in the tables below. While case rate ratios are significantly affected by the unequal capture of testing results, hospitalization and death rate ratios are more accurate and reliable.
To protect patient privacy, these analyses exclude the last seven days. Death counts and rates will be updated separately once per week and age groups with fewer than 20 deaths are suppressed.
Person-day population estimates: To calculate the eligible Utah population 12 years and older who are fully vaccinated, DHHS takes the cumulative total of people 14 days after becoming fully vaccinated or boosted reported into USIIS each day and sums all the days. To calculate the eligible but unvaccinated population, DHHS takes the cumulative total of people 14 days post-full vaccination or boosted minus the 2019 census population estimate for people 12 years and older each day and sums all the days.
¹Age adjustment for total rates: As of 10/5/2021, DHHS age-adjusts total rates to better show the risk of people who are fully vaccinated, boosted, and unvaccinated getting COVID-19, being hospitalized, or dying. Age adjusting is a way to control for the effects of age in multiple populations, in this case in vaccinated, boosted, and unvaccinated Utahns. We age-adjust using the direct age standardization method with the Utah 2019 census population from IBIS as the standard population. To calculate age-adjusted rates, DHHS calculates each age groups’ individual case rate for vaccinated and unvaccinated people and then multiplies that rate by the proportion of that age group in the 2019 Utah population. DHHS then sums each weighted rate to get the total age-adjusted rate for the state.
*Rates are a cumulative incidence rate per 100,000 person-days and are calculated as the “sum of people observed with COVID-19 outcome each day” divided by the “sum of people vaccinated, boosted, or unvaccinated each day” times 100,000.
**The rate ratio is the “incidence rate of unvaccinated people” divided by “incidence rate of fully vaccinated or boosted people.” The rate ratio is interpreted as how many times more the risk is for unvaccinated people than fully vaccinated or boosted people. If the lower bound of the 95% confidence interval (CI) is greater than 1, then the vaccines have a statistically significant effect on risk. Groups that don’t have overlapping 95% confidence intervals have statistically significant differences in risk, while groups whose confidence intervals do overlap are not statistically different.
² Seven-day age-adjusted rates are calculated using the number of fully vaccinated, boosted, and unvaccinated cases per age group and dividing by the median vaccinated and unvaccinated population during that week. The total weekly rates are age-adjusted to the Utah 2019 census population estimates available on IBIS. Seven-day rates exclude the current calendar week as cases reported in this time may not yet be investigated. Hospitalizations and deaths will backfill as these events are reported to DHHS.
³There may be large daily changes in recent case rates and age-specific hospitalizations and deaths because of small case counts. These changes do not indicate differences in vaccine efficacy but instead reflect DHHS identifying additional hospitalizations and deaths in this time window, which often lag case reports.
This analysis relies on surveillance data and does not control for individual differences in risk, location, or testing practices so these data should be considered in conjunction with clinical trials and other vaccine efficacy studies that show the vaccine is very effective at preventing symptomatic illness and severe disease. Breakthrough cases may be under-represented if there is insufficient data to link a case to a USIIS record or reach a person for interview, or over-represented if vaccinated communities are more likely to have access to and receive testing.
Data on pre-existing conditions are gathered from a variety of sources, including case interviews and medical records (when available). Case interviews are conducted by public health investigators across state and local health departments to determine what potential medical risk factors cases may have had prior to developing COVID-19. Data gathered through interviews is self-reported by cases and is dependent on their willingness to share this information with health departments. This is not a complete list of conditions and rates may change as we collect more data and performs additional analysis.
Data collection forms used by the Utah Department of Health and Human Services and Utah’s Local Health Departments have been updated to collect information on additional pre-existing conditions: autoimmune conditions, disabilities, hypertension, severe/morbid obesity, psychological/psychiatric conditions, and substance abuse. The previous neurologic pre-existing condition has been moved into the broader disability condition, which includes neurological, neurodevelopmental, intellectual, and physical disabilities. Additionally, investigators are now able to distinguish between type 1 and type 2 diabetes. All analyses of these new conditions are based on the subset of cases that use the new forms. These forms no longer collect information on specific conditions from cases without that condition or where the status is unknown; this information remains available for the overall ‘Any Pre-Existing Condition’ question.
Examples of persons with compromised immune systems include those with cancer and transplant patients who are taking certain immunosuppressive drugs, persons living with HIV/AIDS, and those with inherited diseases that affect the immune system. Chronic pulmonary conditions include uncontrolled asthma, emphysema, and COPD. Examples of persons with a disability include those with dementia, seizure disorders, cognitive impairment, and Alzheimer’s disease. Psychological/psychiatric conditions include schizophrenia, major depressive disorder, and bipolar disorder.
In the data below, counts below 5 are suppressed to protect privacy. Suppressed values in the chart are represented by the percent equivalent to a count of 5 in that category.
These data reflect any individual who reports being an employee in the healthcare setting in any capacity such as cooks, environmental services, administrative roles, support staff, physicians, nurses, respiratory therapists, pharmacists, home health and personal care aids, etc. Healthcare workers also include those who commonly have patient interactions such as dentists, physical therapists, EMTS, firefighters, phlebotomists, and other technical occupations. These data are not intended to represent the amount of transmission occurring within the healthcare setting. Rather, the data can help us have a better understand the burdenour healthcare systems due to employees testing positive for COVID-19.
Data for this report were accessed on November 02, 2023 12:04 PM.