This data set contains Wisconsin COVID-19 data by county boundary. Data is updated at 2:00PM CDT daily.Detailed data descriptions can be found within the COVID-19 Public Use Data Definitions document.All data are laboratory-confirmed cases of COVID-19 that we freeze once a day to verify and ensure that we are reporting accurate information. These numbers are the official state numbers, though counties may report their own totals independent of DHS. Combining the DHS and local totals may result in inaccurate totals.Data included in these tables are subject to change. As individual cases are investigated by public health, there may be corrections to the status and details of cases that result in changes to this information.Deaths must be reported by health care providers, medical examiners/coroners, and recorded by local health departments in order to be counted.Starting on March 30, 2020, the number of people with negative test results was changed to include only Wisconsin residents. The number of people with negative test results includes only Wisconsin residents who had their results reported electronically to DHS. As a result, this number underestimates the total number of Wisconsin residents with negative test results."-999" values represent fewer than 5 cases, including 0 cases.For more information on the COVID-19 outbreak please visit https://www.dhs.wisconsin.gov/outbreaks/index.htm.

The dataset represents the number of COVID-19 cases statewide in Wisconsin.

This data set contains Wisconsin COVID-19 case, death, hospitalization, test data and population information by county boundary. All data are laboratory-confirmed cases of COVID-19 that are frozen once a day to verify and ensure that we are reporting accurate information. These numbers are the official state numbers, though counties may report their own totals independent of Department of Health Services (combining the DHS and local totals may result in inaccurate totals). Deaths are reported by health care providers, medical examiners/coroners, and recorded by local health departments in order to be counted by the state DHS. Detailed data descriptions can be found within the COVID-19 Public Use Data Definitions document: https://www.dhs.wisconsin.gov/publications/p02677.pdf.

This data set contains Wisconsin COVID-19 cases, deaths, hospitalizations and tests data with demographic information by state boundary from earliest reporting date. Deaths must be reported by health care providers, medical examiners/coroners, and recorded by local health departments in order to be counted. These numbers are the official state numbers, though counties may report their own totals independent of the state's department of health. The data are updated daily.

The dataset contains Wisconsin COVID-19 cases, deaths, hospitalization and test data by census tract boundary. Deaths are reported by health care providers, medical examiners/coroners, and recorded by local health departments in order to be counted by the state DHS. All data are laboratory-confirmed cases of COVID-19 that are frozen once a day to verify and ensure that we are reporting accurate information.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Context

.COVID-19: Illness After Vaccination

"The COVID-19 vaccines are extremely effective at preventing serious illness, hospitalization, and death. Fully vaccinated people who test positive for COVID-19 more than 2 weeks after their completed vaccine dose series are called "breakthrough infections." No vaccine is 100 percent effective, and as such we expect to see some fully vaccinated people test positive for COVID-19. Breakthrough cases typically report mild illness or no symptoms."

https://www.dhs.wisconsin.gov/covid-19/vaccine-status.htm#summary

Content

"Your likelihood of being infected with the virus that causes COVID-19 is determined by many factors, which include vaccinations, but also include the level of transmission and vaccine coverage in your community, whether you or others wear masks as recommended, the number of people you have close contact with, and more. On average, fully vaccinated individuals are less likely to be infected, hospitalized, and die from COVID-19 compared to unvaccinated individuals."

https://www.dhs.wisconsin.gov/covid-19/vaccine-status.htm#summary

Acknowledgements

https://www.dhs.wisconsin.gov/covid-19/vaccine-status.htm#summary

Photo by Joshua Hoehne on Unsplash

Inspiration

COVID-19: Illness After Vaccination

Over the past thirty years, disaster scholars have highlighted that communities with stronger social infrastructure - including social ties that enable trust, mutual aid, and collective action - tend to respond to and recover better from crisis. However, comprehensive measurements of social capital across communities have been rare. This study adapts Kyne and Aldrich’s (2019) county-level social capital index to the census-tract level, generating social capital indices from 2011 to 2018 at the census-tract, zipcode, and county subdivision levels. To demonstrate their usefulness to disaster planners, public health experts, and local officials, we paired these with the CDC’s Social Vulnerability Index to predict the incidence of COVID-19 in case studies in Massachusetts, Wisconsin, Illinois, and New York City. We found that social capital and social vulnerability predicted as much as 95% of the variation in COVID outbreaks, highlighting their power as diagnostic and predictive tools for combating the spread of COVID.

This dataset/code archive included all the data and R codes that were used to explore the universal and robust wastewater biomarkers for population normalization in the SARS-CoV-2 wastewater-based epidemiology. There are nine R code files to produce figures and tables. The data included:

Raw data of weekly biomarkers (caffeine, paraxanthine, and PMMoV) wastewater concentrations, weekly new COVID-19 case numbers, SARS-CoV-2 N1/N2 copies in wastewater, wastewater flow rate

A total of 2,624 wastewater samples (41 weeks) were collected weekly from May 2021- April 2022 from 64 wastewater treatment plants across Missouri, US;

pMMoV data was only available from Sep 13 2021-April 2022 for Missouri data;

Validation dataset from 10 wastewater treatment plants across Wisconsin, US, to test the relationship between wastewater biomarkers and population.

Downloaded Apple mobility data during the pandemic

Validation dataset for wastewater flowrate estimation using paraxanthine concentrations.