UM Geospatial Digital Special Collections

Citation: Center for Disease Control (2020). 2018 USA CDC Social Vulnerability Index (counties) [gis dataset]. CDC. https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html. last updated: 2024-10-09 (update frequency: Never). Abstract: Social vulnerability refers to the potential negative effects on communities caused by external stresses on human health. Such stresses include natural or human-caused disasters, or disease outbreaks. Reducing social vulnerability can decrease both human suffering and economic loss. The CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI) uses 16 U.S. census variables to help local officials identify communities that may need support before, during, or after disasters. Key words: United States, CDC, Vulnerability, Social Vulnerability Index, Counties, Public-Safety Open Geospatial Consortium Standards: dynamic vector tiles | | WMS (coming soon) | WFS (coming soon) Analytical Functions: gdsc_get_attributes(tablename=us_2018_svi_county,lat=25.718,lng=-80.279,identifier=location,attrs=[area_sqmi,county,e_age17,e_age65,e_crowd,e_daypop,e_disabl,e_groupq,e_hh,e_hu,e_limeng,e_minrty,e_mobile,e_munit,e_nohsdp,e_noveh,e_pci,e_pov,e_sngpnt,e_totpop,e_unemp,e_uninsur,ep_age17,ep_age65,ep_crowd,ep_disabl,ep_groupq,ep_limeng,ep_minrty,ep_mobile,ep_munit,ep_nohsdp,ep_noveh,ep_pci,ep_pov,ep_sngpnt,ep_unemp,ep_uninsur,epl_age17,epl_age65,epl_crowd,epl_disabl,epl_groupq,epl_limeng,epl_minrty,epl_mobile,epl_munit,epl_nohsdp,epl_noveh,epl_pci,epl_pov,epl_sngpnt,epl_unemp,f_age17,f_age65,f_crowd,f_disabl,f_groupq,f_limeng,f_minrty,f_mobile,f_munit,f_nohsdp,f_noveh,f_pci,f_pov,f_sngpnt,f_theme1,f_theme2,f_theme3,f_theme4,f_total,f_unemp,fips,location,m_age17,m_age65,m_crowd,m_disabl,m_groupq,m_hh,m_hu,m_limeng,m_minrty,m_mobile,m_munit,m_nohsdp,m_noveh,m_pci,m_pov,m_sngpnt,m_totpop,m_unemp,m_uninsur,mp_age17,mp_age65,mp_crowd,mp_disabl,mp_groupq,mp_limeng,mp_minrty,mp_mobile,mp_munit,mp_nohsdp,mp_noveh,mp_pci,mp_pov,mp_sngpnt,mp_unemp,mp_uninsur,rpl_theme1,rpl_theme2,rpl_theme3,rpl_theme4,rpl_themes,spl_theme1,spl_theme2,spl_theme3,spl_theme4,spl_themes,st,st_abbr,state,stcnty],normal='') ETL documentation

ETL for us_2018_svi_county

######### # GDSC ETL is performed in two steps: shell script to ETL data into postgres # and then additional transformations with SQL in postGIS (if needed). #### ######### # Step 1 - bash script (pseudo code) #### # create directory structure and move into it mkdir -p /data/us_2018_svi_county/{download,etl} && cd /data/us_2018_svi_county # set update flag based on last update and update frequency do_update=0 if date() < last_update + update_frequency else do_update = 1 # download if update flag is set: if do_update == 1 then wget -O download/us_2018_svi_county.zip 'https://svi.cdc.gov/Documents/Data/2018/db/states_counties/SVI_2018_US_county.zip' # unzip to download directory if update flag is set if do_update == 1 then unzip -d download download/us_2018_svi_county.zip && rm download/us_2018_svi_county.zip # load into postGIS with: ogr2ogr -lco GEOMETRY_NAME=geom -f PostgreSQL PG:"" download/SVI2018_US_county.gdb -nlt multipolygon -nln us_2018_svi_county ######### # Step 2 - SQL script (pseudo code): #### # remove duplicate points and make geometries valid: UPDATE us_2018_svi_county SET geom=ST_MakeValid(ST_RemoveRepeatedPoints(geom));" # add local geometry column and reproject existing geometries into local EPSG: SELECT AddGeometryColumn ( 'us_2018_svi_county', 'geom_local',6350,'multipolygon',2 ); UPDATE us_2018_svi_county SET geom_local=ST_MakeValid(ST_RemoveRepeatedPoints(ST_Transform(ST_Multi(geom),6350))); CREATE INDEX us_2018_svi_county_geom_local_idx ON us_2018_svi_county USING GIST (geom_local); NOTIFY pgrst, 'reload schema';"cd /data/us_2018_svi_county/ mkdir -p derived # Create pg_dump and downloadable zip of table in derivate directory pg_dump -d $POSTGRES_DB -U $POSTGRES_USER -p $POSTGRES_PORT -h postgis-gtqfomprafjglcnk -t us_2018_svi_county > derived/us_2018_svi_county.sql tar -czf derived/us_2018_svi_county.sql.tar.gz meta_dcat_us_2018_svi_county.json -C derived us_2018_svi_county.sql