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Infectious Disease Epidemiology, Prevention and Control Division
651-201-5414
IDEPC Comment Form

Contact Info

Infectious Disease Epidemiology, Prevention and Control Division
651-201-5414
IDEPC Comment Form

Hospitalization Data
COVID-19 Situation Update

Updated 11/14/2024
Updated weekly on Thursdays at 11 a.m. with data as of 4 a.m. on the Tuesday prior, unless noted otherwise.

Situation Update Home:   Cases & Variants | Hospitalizations | Mortality (Deaths)

  • Hospitalization data show how many cases were hospitalized or admitted to an intensive care unit (ICU) within 14-days of testing positive for SARS-CoV-2, the virus that causes COVID-19.
    • Hospitalizations meeting the confirmed or probable case criteria are included in Minnesota data unless otherwise specified.
    • Admissions include all Minnesota resident cases regardless of location of hospitalization.
    • Cases in residents of other states hospitalized in Minnesota are not included in the Minnesota case counts.
  • All data are preliminary and may change as more information is received.
    The shaded bar at the end of graphs indicates a lag period where data may be incomplete.

  • Population estimates are obtained from the 2010 Census Bureau Population Estimates Program (PEP) and the 2019 American Community Survey (ACS) 5-year estimates for the state of Minnesota available at United States Census Bureau: Explore Census Data
  • Hospitalizations include people who are hospitalized in the ICU.
  • Case hospitalization data by date is reported by admission date (when the case was first admitted to the hospital or ICU) unless otherwise specified. In most cases, the original admission was for COVID-19.
    • Some cases are hospitalized before they are diagnosed with COVID-19. This is the reason for admission dates before the first case was identified in Minnesota.
  • All data are preliminary, and reports require verification before counting as a hospitalization. Therefore, the data may change and reports for the most recent weeks may more dramatically undercount the total number of hospitalizations occurring in that week. We continuously receive hospitalization reports and work to confirm, process, and report them as quickly as possible.
  • For some hospitalizations, sex, race/ethnicity, or age data may not be available and therefore are excluded from an analysis. This means that the total number of cases for each of the charts below may vary slightly.
  • Most of the graphs on this page show COVID-19 hospitalization rates rather than hospitalization counts. It is important to use hospitalization rates when making comparisons between groups that have different population sizes. For example, the White population is much larger than the Native American/Alaska Native population in Minnesota so we would expect to see much higher hospitalization counts among White Minnesotans. In order to compare whether one of these two groups is being disproportionately impacted by COVID-19, we must calculate the rate, which is the number of hospitalizations divided by the population size. Count data is still available and can be found in the CSV files that accompany each graph.
  • Age adjustment for age-adjusted rates is performed when you want to make comparisons between groups with different age distributions. It is important to note, that age-adjusted rates are not the actual rate of disease occurring in the state. The crude rate is the actual rate among a population in the state of Minnesota and is a result of many factors, including age, race/ethnicity, gender, and other factors we are unable to measure.
    • For example, in Minnesota women are on average older than men. Because age is associated with a higher rate of severe infection and death due to COVID-19, the rate of hospitalization and death in women in Minnesota might be higher because women are older. If we want to understand whether a woman is at higher risk of hospitalization or death compared to a man of the same age, we use age adjustment to remove the effect of age in the population to make a more direct comparison by sex. The same process can be used to compare different groups by race/ethnicity or other factors.
  • Data for the most recent MMWR week will only contain information for Sunday through Tuesday based on when the data are compiled to create these graphs.

On this page:
Hospitalization Trends
Demographics
 

Hospitalization Trends

Hospitalizations Over Time (7-day Moving Average)

We are currently experiencing technical difficulties with interactive graphs. 
Up to date data can be accessed from the CSV file below.

  • Download: 7-day Moving Average of Hospitalizations (CSV)
  • Hospitalizations over time are shown using a 7-day moving average of the daily count of all hospitalizations and the statewide daily hospitalization rate.
    • To get the 7-day moving average for hospitalizations, we add all the hospitalizations from the previous 7-days (including the current date) and then divide by 7.
    • To get the 7-day moving average for rates, we add all the rates (number of hospitalizations divided by the total Minnesota population, multiplied by 100,000) from the previous 7 days (including the current date) and divide by 7.
  • A 7-day moving average provides a more useful representation of the data by smoothing out any short-term spikes or dips that occur across a week because of external factors not related to disease transmission, such as a facility not being open on certain days or delays in data reporting.
Total cases hospitalized (cumulative)101,192
Total cases hospitalized in ICU (cumulative)16,477

Hospitalization Rate by County of Residence

We are currently experiencing technical difficulties with interactive graphs. 
Up to date data can be accessed from the CSV file below.

  • Download: Hospitalization Rate by County of Residence (CSV)
  • County rates are calculated using hospitalized probable and confirmed cases by reported county of residence by week of first admission divided by the total county population. The rate is then multiplied by 100,000.
  • Weeks are defined as Sunday through Saturday. Therefore "Last Week" corresponds with the Sunday through Saturday of the week prior to when the data are posted.

Demographics

Hospitalization Rate by Age Group

We are currently experiencing technical difficulties with interactive graphs. 
Up to date data can be accessed from the CSV file below.

  • Download: Hospitalization Rate by Age Group (CSV)
  • Rates are calculated using hospitalized probable and confirmed cases by reported age at date of specimen collection divided by the age-specific Minnesota population. The rate is then multiplied by 100,000.
  • The “total” rate line is the total of all hospitalizations in this graph (for whom age is available) divided by the Minnesota population, obtained by adding together the total population for each age group. The rate is then multiplied by 100,000.
  • Data in this graph have been smoothed using a 4-week moving average. Moving averages combine the raw counts for the data from preceding days or weeks and then average them (e.g., a 4-week moving average combines data from the current week and the previous 3 weeks and averages them). They are useful for observing trends in data which have larger fluctuations over short periods of time because of small population sizes or rare outcomes. Raw data of the count and rate per week are still available in the downloadable CSV file.

Hospitalization Rate by Sex

We are currently experiencing technical difficulties with interactive graphs. 
Up to date data can be accessed from the CSV file below.

  • Download: Hospitalization Rate by Sex (CSV)
  • Rates are calculated using hospitalized probable and confirmed cases by reported sex at date of specimen collection divided by the total sex-specific Minnesota population. The rate is then multiplied by 100,000.
  • The “total” rate line is the total of all hospitalizations in this graph (for whom sex data is available) divided by the Minnesota population. The rate is then multiplied by 100,000.
  • The age-adjusted rates per 100,000 are obtained by taking the incidence rate per 100,000 (as described above) for all hospitalizations for whom sex data is available and standardizing to the U.S. 2000 Standard Population which can be obtained from the National Cancer Institute: Standard Populations (Millions) for Age-Adjustment.
  • Data in this graph have been smoothed using a 4-week moving average. Moving averages combine the raw counts for the data from preceding days or weeks and then average them (e.g., a 4-week moving average combines data from the current week and the previous 3 weeks and averages them). They are useful for observing trends in data which have larger fluctuations over short periods of time because of small population sizes or rare outcomes. Raw data of the count and rate per week are still available in the downloadable CSV file.

Hospitalization Rate by Race/Ethnicity

We are currently experiencing technical difficulties with interactive graphs. 
Up to date data can be accessed from the CSV file below.

  • Download: Hospitalization Rate by Race and Ethnicity (CSV)
  • Rates are calculated using hospitalized probable and confirmed cases by reported race/ethnicity at date of specimen collection divided by the total Minnesota population for each race/ethnicity. The rate is then multiplied by 100,000.
  • The “total” rate line is the total of all hospitalizations in this graph (for whom race and ethnicity data is available) divided by the Minnesota population. The rate is then multiplied by 100,000.
  • The age-adjusted rates per 100,000 are obtained by taking the incidence rate per 100,000 (as described above) for all hospitalizations for whom race and ethnicity data is available and standardizing to the U.S. 2000 Standard Population which can be obtained from the National Cancer Institute: Standard Populations (Millions) for Age-Adjustment.
  • Data in this graph have been smoothed using a 4-week moving average. Moving averages combine the raw counts for the data from preceding days or weeks and then average them (e.g., a 4-week moving average combines data from the current week and the previous 3 weeks and averages them). They are useful for observing trends in data which have larger fluctuations over short periods of time because of small population sizes or rare outcomes. Raw data of the count and rate per week are still available in the downloadable CSV file.
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Last Updated: 11/14/2024