Contact Info
Infectious Disease Epidemiology, Prevention and Control Division
651-201-5414
- 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.
- Case data by date is represented by the date of specimen collection unless otherwise specified.
- All data are preliminary, and reports require verification before counting as a case. Therefore, the data may change and reports for the most recent weeks may more dramatically undercount the total number of cases occurring in that week. We continuously receive case reports and work to confirm, process, and report them as quickly as possible.
- For some cases, 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 case rates rather than case counts. It is important to use case 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 case 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 cases 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.