This map displays several neighborhood-level measures of populations with greater risk associated with COVID-19. To develop the indices, we used demographic and health characteristics thought to increase a person's risk for severe symptoms or death, as identified by national and world health organizations.
Centers for Disease Control and Prevention says that "some people are at higher risk of getting very sick from this illness, [including] older adults [and] people who have serious chronic medical conditions like heart disease, diabetes, [and] lung disease." The National Cancer Institute says that people with certain types of cancer or treatments can have weaker immune systems, making them more susceptible to COVID-19. The National Institute on Drug Abuse says those who smoke may also be more susceptible to the disease. The World Health Organization suggests that people with asthma may be more vulnerable to a serious respiratory infection from Coronavirus.
Using demographic data from the U.S. Census Bureau and estimates of neighborhood health data from the CDC's 500 Cities Project, we can estimate areas with high-risk populations.
Because it's hard to understand eight different maps, each with a different risk factor, we used statistics (specifically principle component analysis) to simplify and synthesize the information. We found that there are two distinct groups of indicators that relate to risk populations. These roughly split our eight indicators into two groups of four, with one group related to socioeconomic status and one group related to age.
The socioeconomic risk group contains behaviors and outcomes that tend to relate to income and economic opportunity. These are the uninsured population, asthma, smoking rates, and diabetes.
The age risk group contains demographics (age itself) and health outcomes that are linked to older age populations. This includes cancer and heart disease.
The values shown in this tool are calculated from all the census tracts in Indiana where 500 Cities health data is available. This includes most major cities in Indiana. Therefore, the ranges shown on the map are in comparison to the other cities across Indiana, not just to neighborhoods within Bloomington. This is because using only the relatively small number of census tracts in Bloomington would not provide enough data points for a strong analysis.
On the whole, census tracts in Bloomington do not score highly in either socioeconomic-related risk factors or age-related risk factors. Most tracts score below average on the socioeconomic-related risk index compared to other major cities in the state. Some of the lowest-risk neighborhoods, according to this index, are located just south of the Indiana University campus near Bryant Park and Maxwell Lane, in the suburban areas near Griffy Lake, and in the suburban developments on the far south side (along Sare Road).
Neighborhoods just west of Rogers have the highest socioeconomic risk index scores in Bloomington. The census tracts containing neighborhoods like Pigeon Hill, Crestmont, and the Near West Side tend to have rates of uninsured residents, asthma, and smoking that are at or near the state average. In most Bloomington neighborhoods, these rates are well below the state average.
Some Bloomington neighborhoods score slightly higher than the state average in the age-related risk index. These are mostly suburban areas on the far north and far south sides of the city (near Griffy Lake and Lake Monroe). This is driven by high older populations and an estimated cancer rate that is above the state average. Heart disease rates are still low in these neighborhoods, compared to the state average.
To use this map, click on a neighborhood area (census tract) and explore its risk factors in the legend to the left. Expand each index to see the individual variables that have the strongest impact on that measure. To change the data displayed on the map, click “map this” located next to the index name or variable name in the legend. If you zoom in, additional neighborhood names will appear on the map.
This was built by SAVI, a program of the Polis Center at IUPUI. If you have any questions, please contact firstname.lastname@example.org.
Geographies shown are census tracts. Demographic data (age groups) are from the 2017 American Community Survey 5-Year Averages (via SAVI). Health data are from the CDC's 500 Cities Project (via SAVI). Bloomington neighborhood labels are from the City of Bloomington's Neighborhood Association Data.
We have limited information about the risk factors related to COVID-19, how they relate, and their relative importance. This information changes quickly, but we will work to update this map as new information becomes available.
The combined risk index was created by standardizing each indicator by calculating z-scores for each tract (in other words, how far above or below average is each tract for each indicators). Principal component analysis was used to develop a measure highlighting tracts with many overlapping risk factors. This revealed two components that have the strongest explanatory power. Component one, what we call socioeconomic-related risk factors, explains 50% of the variation in these eight indicators. Component two, what we call age-related risk factors, explains 33% of variation.