COVID-19

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While every neighborhood is at risk for COVID-19 infection, some neighborhoods may have more residents who are at higher risk of death (mortality) should they contract COVID-19. From the beginning of the pandemic, the Neighborhood Health Partnership program has been working with the Wisconsin Collaborative for Healthcare Quality (WCHQ) and the UW Health Innovation Program (HIP) to provide electronic health record data to help community decision makers mitigate risk in their planning, outreach and resource allocation. The Centers for Disease Control and others have learned more about the risk factors for COVID-19 since we first shared ZIP code level estimates for the risk of severe illness in April 2020. Based on this new information, we are now pleased to share estimates of the relative risk of COVID-19 mortality (death) for many Wisconsin ZIP codes and a tool outlining the potential barriers to successfully vaccinating the residents in those ZIP codes for COVID-19.

As you review these tools, keep in mind that health is complex and multicausal. These tools depict the state of health in a ZIP code, but do not address root causes of health or illness. More information on how to make sense of these tools is provided in the frequently asked questions section below.

Regardless of how your neighborhood is reflected in the data, we encourage everyone to do their part by staying informed about local guidelines and following the 3 W’s:

  • WEAR a face covering when in public.
  • WATCH your distance – stay at least 6 feet apart to avoid close contact.
  • WASH your hands often with soap and water for at least 20 seconds or rub hands with hand sanitizer with at least 60% alcohol until they feel dry.

Visit https://www.dhs.wisconsin.gov/covid-19/index.htm to learn more about how you can protect yourself and your community.

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COVID-19 Relative Mortality Risk Interactive Maps

COVID-19 relative mortality risk estimates were developed based on the general United States population risk calculator for COVID-19 mortality that was published in Nature Medicine by researchers from the Johns Hopkins Bloomberg School of Public Health. The calculator uses sociodemographic factors and information on pre-existing conditions to predict death from COVID-19. We adapted these estimates to reflect relative risk of death in a ZIP code compared to the average risk of death for the state of Wisconsin. These estimates reflect relative risk only if a patient contracts COVID-19 – they do not reflect the overall risk of both contracting and dying from COVID-19. (The risk of contracting COVID-19 varies by ZIP code and over time depending on community spread and is not represented in these maps.)

The maps below provide a visualization of the COVID-19 relative mortality risk for ZIP codes in counties where sufficient data is available. We suggest using a desktop for optimal performance of this tool.

Interactive Maps

To navigate the map, select the county you are interested in from the drop-down and hover over a ZIP code to view more information. Additional navigation tips:

  • Hold shift, click, and drag to pan the map.
  • Hover over the map to view map controls in the top left.
    • Use the Search Map button to zoom to a city or ZIP code of interest in the county.
    • Use the Zoom In and Zoom Out buttons to zoom in and out of an area of interest.
    • Use the Zoom Home button to pan out to view all ZIP codes selected in the county.
    • Use the Zoom Area, Pan, Rectangle, Radial, and Lasso buttons to zoom and pan the map.
  • Use the Undo button on the bottom right to undo a selection.
  • Use the Reset button on the bottom right to clear ZIP code selections and pan out to view all ZIP codes in the county.

Last Updated 01/26/2021

COVID-19 Relative Mortality Risk and Barriers to Vaccination Tool

Now that COVID-19 vaccines are available the next challenge becomes ensuring that enough people are vaccinated to put us on the path to population immunity and long-term protection from the disease. As decision makers plan and implement vaccination campaigns, understanding the COVID-19 relative mortality risks and historic rates of uptake of the seasonal flu vaccine will be valuable in building effective communication and outreach plans in each community. A recent Kaiser Family Foundation article highlights the many potential barriers to seasonal flu vaccinations including rates of insurance coverage, access to health care, and concern or misconceptions about vaccine safety, side effects and efficacy. While there are important distinctions between COVID-19 and seasonal flu and the public’s openness to a COVID-19 vaccine may differ from the flu vaccine, flu vaccination rates can help us understand some of the challenges ahead in achieving equity in distribution and sufficient levels of immunity with a COVID-19 vaccine.

The tool below plots the COVID-19 relative mortality risks and the potential barriers to vaccination for each ZIP code. Potential barriers to vaccination were calculated for each ZIP code by dividing the estimated flu vaccination rate for the 2019 –2020 season by the average vaccination rate for the state. 1.0 is equal to the state average for both mortality risks and vaccination rates. We suggest using a desktop for optimal performance of this tool.

The resulting Communication Groups can be used to inform the outreach, communications, and messaging plans for each community:

  • Higher Priority: ZIP codes that fall in the upper right quadrant represent the communities that have both the highest risk of COVID-19 relative mortality and barriers to vaccination. These are the communities that would benefit from quick vaccination of its residents, but there may be substantial barriers to overcome to make that possible. They should be targeted with the highest volume communications from multiple channels/sources to make the processes and timelines to get vaccinated clear and to overcome potential barriers to vaccination including perceptions of cost, access, and hesitancy.
  • Medium Priority on Barriers to get Vaccinated: ZIP codes that fall in the upper left quadrant represent communities that have lower than average COVID-19 relative mortality risks, but higher than average barriers to vaccination. While speed of vaccination may not be as critical, these communities do need to be vaccinated to ensure population immunity. Early and frequent communications that overcome potential barriers to vaccination could be beneficial.
  • Medium Priority on Process to get Vaccinated: ZIP codes that fall into the bottom right quadrant represent communities that have higher than average COVID-19 relative mortality risks, but lower than average barriers to vaccinations. These communities should be vaccinated as quickly as possible, and require communications that make vaccination processes and timelines clear.
  • Lower Priority: These communities have both lower-than-average COVID-19 relative mortality risks and barriers to vaccination. These communities need base level communications on processes and timelines, but do not require any added effort to ensure vaccination.

Click here to view NHP Director, Jessica Bonham-Werling provide an overview of this tool and how it can be used during a WCHQ Webinar focused on COVID-19 Vaccine Communication’s and Outreach.

Interactive Tool

To navigate the tool, select the counties, ZIP codes, Rural Urban and/or Communication Groups you are interested in from the drop-down and hover over the dots for more information. Additional navigation tips:

  • Use the legend to further subset the tool to a Rural Urban Group of interest.
    • Select one or more legend values to highlight corresponding ZIP codes in the tool. Hold ctrl to select multiple legend values.
    • Notice, only legend values for your selections will appear.
  • Use the Undo button on the bottom right to undo a selection.
  • Use the Reset button on the bottom right to clear ZIP code selections and pan out to view all ZIP codes.

Last Updated 01/26/2021

Frequently Asked Questions

The COVID-19 Relative Mortality Risk was created using the general population risk calculator for COVID-19 mortality developed by researchers at the Bloomberg School of Public Health and Johns Hopkins University and published in Nature Medicine. This calculator uses various sociodemographic factors and pre-existing conditions for the U.S. population, combining information from the UK-based OpenSAFELY study with mortality rates by age and ethnicity across US states.

To find the COVID-19 Relative Mortality Risk for a given ZIP code we calculated the risk (hazard ratio) for each WCHQ health system patient in Wisconsin, aged 18-85. The hazard ratio for each patient was then averaged across all WCHQ health systems statewide. To calculate the relative risk, each patient’s hazard ratio was divided by the average hazard ratio for WCHQ health systems statewide. We then calculated the average relative risk for the patients in each ZIP code.

Patient COVID-19 Relative Mortality Risk was calculated based on a weighted combination of:

  • Sociodemographic factors including age, race/ethnicity, sex and the deprivation of their home ZIP code (based upon the assigned “Rural Urban Group” from the WCHQ 2020 Disparities Report),
  • Behavioral factors including body mass index and smoking status,
  • Predisposing health conditions including blood pressure, respiratory disease excluding asthma, asthma, chronic heart disease, diabetes, cancer, stroke, kidney disease and rheumatoid arthritis.

The weights assigned to each factor were defined by the relative magnitude of the contribution of these factors to the risk of death due to COVID-19 in the adult population.

Note: Some values from the Nature Medicine article were not available in the WCHQ data and were excluded. This includes “ex-smoker” status and cancer (both hematological and non-hematological) diagnoses that occurred more than two years prior to June 2018. Other values were missing for only a subset of health system patients and mean imputation was performed to populate. This includes smoking status, blood pressure and diabetes control. Additionally, we only used three social deprivation groupings while the original model used five.

For the interactive map, each ZIP code has been assigned a quartile based on the relative risk of COVID-19 mortality for its residents.

  • Lowest Relative Risk: These are the ZIP codes with much lower than average risks of COVID-19 mortality. They have lower risks than three quarters of the other ZIPs in the state.
  • Lowest Middle Relative Risk: These are the ZIP codes with lower than average risks of COVID-19 mortality. They have lower risks than half of the other ZIPs in the state.
  • Highest Middle Relative Risk: These are the ZIP codes with higher than average risks of COVID-19 mortality. They have higher risks than half of the other ZIPs in the state.
  • Highest Relative Risk: These are the ZIP codes with much higher than average risks of COVID-19 mortality. They have higher risks than three quarters of the other ZIPs in the state.

The groupings are intended to be a helpful tool in planning COVID-19 vaccine communications in the various communities in Wisconsin.

  • Higher Priority: ZIP codes that fall in the upper right quadrant represent the communities that have both the highest risk of COVID-19 relative mortality and barriers to vaccination. These are the communities that would benefit from quick vaccination of its residents, but there may be substantial barriers to overcome to make that possible. They should be targeted with the highest volume communications from multiple channels/sources to make the processes and timelines to get vaccinated clear and to overcome potential barriers to vaccination including perceptions of cost, access, and hesitancy.
  • Medium Priority on Barriers to get Vaccinated: ZIP codes that fall in the upper left quadrant represent communities that have lower than average COVID-19 relative mortality risks, but higher than average barriers to vaccination. While speed of vaccination may not be as critical, these communities do need to be vaccinated to ensure population immunity. Early and frequent communications that overcome potential barriers to vaccination could be beneficial.
  • Medium Priority on Process to get Vaccinated: ZIP codes that fall into the bottom right quadrant represent communities that have higher than average COVID-19 relative mortality risks, but lower than average barriers to vaccinations. These communities should be vaccinated as quickly as possible, and require communications that make vaccination processes and timelines clear.
  • Lower Priority: These communities have both lower-than-average COVID-19 relative mortality risks and barriers to vaccination. These communities need base level communications on processes and timelines, but do not require any added effort to ensure vaccination.

The Rural Urban Groups refer to the six groups defined in the 2020 Wisconsin Health Disparities Report: Rural and Urban Populations. In this report, researchers at the UW-Madison used an established model to distinguish the unique health-related resources of rural and urban ZIP codes across Wisconsin to find key factors (i.e., health care providers, insurance status, poverty) that contribute to health. This resulted in six groups of rural and urban ZIP codes: rural underserved, rural, rural advantaged, urban underserved, urban, and urban advantaged.

Estimated coverage on the map tooltip refers to the number of patients, ages 18-85, who receive primary care from a WCHQ member health system compared to the number of patients estimated to live in the selected ZIP code based on the 2014-2018 American Community Survey (ACS).

Note: While the ACS is the best source for detailed population information, it is still just an estimate for one point in time. Portions of the population may be missed and/or the population may fluctuate over time as people move in and out of a particular community.

These tools provide data about people who have sought care from 2016 – 2018 at health systems that report data to WCHQ. People who do not receive primary care from a WCHQ member health system that publicly reports their data are not included. This includes people who get their health care elsewhere, those who do not have adequate health care, and those who simply have not gone in for a primary care visit during this period. While this data covers much of the state’s healthcare systems, our federally qualified health centers are underrepresented and therefore may not accurately reflect the health of some of Wisconsin’s vulnerable communities. Additionally, some ZIP codes do not have a large enough number of patients in the data to ensure confidentiality.

Data is not provided for counties or ZIP codes with sample sizes of less than 50 people and/or where the estimated coverage is less than 10% of the ACS population.

COVID-19 Relative Mortality Risk: Data for this analysis are available through a partnership with the Wisconsin Collaborative for Healthcare Quality (WCHQ). The data used includes July 2016 – June 2018 electronic health record data from over 20 health system members of WCHQ, representing 65% of Wisconsin’s primary care providers. To learn more, visit the Making Sense of the Data action tool or visit https://www.wchq.org/.

We included any patient, aged 18-85 that was under regular care by a WCHQ member health system that has chosen to report their data. WCHQ Members who contributed data included in these reports include:

Access Community Health Centers, Agnesian Healthcare, Ascension North Region and Fox Valley, Ascension | Columbia St. Mary’s, Ascension | Wheaton Franciscan Healthcare, Aspirus Clinics, Inc., Associated Physicians, Divine Savior, Froedtert & The Medical College of Wisconsin, Gundersen Health System, Mayo Clinic Health System – Franciscan Healthcare, Mayo Clinic Health System in Eau Claire, Mercyhealth, Meriter Medical Group, Monroe Clinic, Prairie Clinic, Prevea Health, ProHealth Medical Group, Reedsburg Area Medical Center, Sauk Prairie Healthcare, SSM Health Dean Medical Group, UW Health Physicians, and Wildwood Family Clinic

Barriers to Vaccination: Data are based on 2019-2020 seasonal flu vaccination data provided by the Wisconsin Department of Health Services. Vaccination rates were estimated based on a comparison to population estimates from the 2014-2018 American Community Survey (ACS) data. While there are important distinctions between COVID-19 and seasonal flu and the public’s openness to a COVID-19 vaccine may differ from that of the flu vaccine, flu vaccination data can help us understand some of the challenges ahead in achieving equity in distribution and sufficient levels of immunity with a COVID-19 vaccine.

Don’t worry, you didn’t break the tools! The drop-downs and legend only display relevant values for your selections. Reset the tools using the “Reset” icon in the bottom right corner.

Making sense of these tools requires an appreciation of the data within a social, political, economic and cultural context. Health, like so many other things, is not equitably distributed across our neighborhoods.

Data showing differences between communities can only tell part of the story of how these differences came to be and continue to exist. This is because the root causes of health inequalities – preventable and unjust differences between who does and who does not have access to resources for living healthy and safely – are not reflected in the datasets of health outcomes. These root causes are often historically and structurally embedded and are less visible than health outcomes.

Without recognizing the role of the root causes of health inequities, we run the risk of drawing conclusions about communities that are untrue and harmful. Responsible data-users will be careful to not draw conclusions that might reinforce harmful and limiting stereotypes about communities and appreciate that a dataset can only ever tell us part of the story. They will connect these datasets with local knowledge about factors at the individual, neighborhood, organizational, community, and policy levels that affect health outcomes. More information is available on our Resources page to help you form a complete picture of the health of a neighborhood.

In addition to recognizing what is not represented in these tools, you should also understand that there are limitations to this data itself as not all people access the health care system and not all health care systems are able to share their data. Due to these factors, and others, the data in these maps may not accurately reflect the entire population of a ZIP code or county.

Our partners at the Population Health Institute have created and curated some must-read COVID-19 resources that focus on the social determinants of health and equity.

We strongly encourage you to use these tools, along with other available data, information and resources when planning COVID-19 responses or any other efforts to improve the overall health of your community.

County Health Rankings and Roadmaps and What Works for Health have a wealth of information that can help you form a more complete view of your community’s needs and all the factors that may influence health. They will also help you to assess your needs and available resources, focus on what is most important in your community, choose effective policies and programs and take action.

Learn More

If you have questions or would like to learn more about the Neighborhood Health Partnerships Program, please contact us at nhp@hip.wisc.edu.