Check the setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- An internet connection
Census-tract and county social-vulnerability rankings for building emergency planning, outreach, and hazard-equity tools.
From source to product signal
SVI ranks communities on socioeconomic, household, minority-status, and housing themes derived from ACS. Start with 2022 county ranks for the United States file. Percentiles are relative within one vintage, so do not compare 2020 and 2022 ranks as a time series.
Install the packages, then run the notebook cell.
python -m pip install pandas requests
import pandas as pd
import requests
response = requests.get(
"https://onemap.cdc.gov/onemapservices/rest/services/SVI/"
"CDC_ATSDR_Social_Vulnerability_Index_2022_USA/FeatureServer/1/query",
params={
"where": "1=1",
"outFields": "ST,STATE,STCNTY,COUNTY,RPL_THEMES,E_TOTPOP",
"returnGeometry": "false",
"resultRecordCount": 50,
"f": "json",
},
timeout=30,
)
response.raise_for_status()
counties = pd.DataFrame(
[feature["attributes"] for feature in response.json()["features"]]
)
print(counties.head())Test a useful signal
Test whether SVI percentiles can flag counties for emergency-planning outreach.
Agency for Toxic Substances and Disease Registry is a government source. Last verified 2026-08-18. Temporal coverage: 2000-2022 SVI releases.