Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset supports the Philadelphia Council District Health Dashboard, an interactive web application that visualizes health disparities and social determinants of health across Philadelphia's 10 City Council Districts. The dashboard provides district-level insights to guide equitable policy and investment decisions by City Council members and the public.
Philadelphia residents experience drastically different health outcomes across the city – differences shaped by federal, state, and local policies rather than individual choices alone. This project maps key health indicators across all 10 Philadelphia City Council Districts to show how politics and geography intersect to shape Philadelphian health.
Data aggregated from original geographic units to City Council District boundaries using population-weighted methods.
data_v1.csv
- Main dataset containing health indicators by Philadelphia City Council Districtcodebook_v1.csv
- Complete metadata and variable documentationSupports policy analysis, community advocacy, academic research, and public health planning at the district level.
Amber Bolli, Tamara Rushovich, Ran Li, Stephanie Hernandez, Alina Schnake-Mahl
Transform Academia for Equity grant from Robert Wood Johnson Foundation
Philadelphia, City Council, Health Disparities, Social Determinants, Urban Health, Public Policy, Geospatial Analysis
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset supports the Philadelphia Council District Health Dashboard, an interactive web application that visualizes health disparities and social determinants of health across Philadelphia's 10 City Council Districts. The dashboard provides district-level insights to guide equitable policy and investment decisions by City Council members and the public.
Philadelphia residents experience drastically different health outcomes across the city – differences shaped by federal, state, and local policies rather than individual choices alone. This project maps key health indicators across all 10 Philadelphia City Council Districts to show how politics and geography intersect to shape Philadelphian health.
Data aggregated from original geographic units to City Council District boundaries using population-weighted methods.
data_v1_1.csv
- Main dataset containing health indicators by Philadelphia City Council Districtcodebook_v1_1.csv
- Complete metadata and variable documentationSupports policy analysis, community advocacy, academic research, and public health planning at the district level.
Amber Bolli, Tamara Rushovich, Ran Li, Stephanie Hernandez, Alina Schnake-Mahl
Transform Academia for Equity grant from Robert Wood Johnson Foundation
Philadelphia, City Council, Health Disparities, Social Determinants, Urban Health, Public Policy, Geospatial Analysis
Population metrics are provided at the census tract, planning district, and citywide levels of geography. You can find related vital statistics tables that contain aggregate metrics on natality (births) and mortality (deaths) of Philadelphia residents as well as social determinants of health metrics at the city and planning district levels of geography. Please refer to the metadata links below for variable definitions and the technical notes document to access detailed technical notes and variable definitions.
This dataset combines lead risk and socioeconomic factors to explore patterns in West and North Philadelphia. Lead risk data includes: lead-in-soil, land recycled sites, demolitions, housing code violations, age of housing, smelters, and elevated blood lead levels of children. Census data includes: homeownership status, house vintage, racial demographics, and percentage of population with a disability. Our visual analysis explored elevated blood lead levels in children and soil contamination as compared to spatial demographic distributions. General inequities regarding which populations are most impacted by environmental health hazards are significant in order to inform public health and urban planning policy.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Demographics and self-reported health in relation to rates (in %) of Hospital Anxiety and Depression Scale scores above ≥11 (case) plus mean and standard deviations (SD) of the scores among 1,293 participants in survey of adult residents of Philadelphia, PA, during the first wave of COVID-19 epidemic.
https://www.usa.gov/government-workshttps://www.usa.gov/government-works
Weekly updates have finished with the June 28th update.
This dataset contains aggregate data of COVID vaccines administered to citizens based on zip code of residence. Data includes counts of individuals who received a vaccine dose that provides partial coverage against the disease and counts of individuals that received a vaccine dose that provides full coverage against the disease. Suppression applies for quantities less than 5.
Data only includes information reported to PA-SIIS, the Pennsylvania Statewide Immunization Information System.
Effective 7/9/2021, the COVID-19 Vaccine Dashboard is updated to more accurately reflect the number of people who are partially and fully vaccinated in each county outside of Philadelphia, along with the demographics of those receiving vaccine. For state-to-state comparisons refer to the CDC vaccine data tracker located here: https://covid.cdc.gov/covid-data-tracker/#county-view
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Sociodemographic characteristics of HIV testing agency staff who completed online survey, Philadelphia County, 2020 (N = 42).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Summary of the main themes from individual interviews with HIV testers and agency leaders regarding HIV self-test (HIVST) integration into existing HIV testing programs.
2024 UpdatesDVRPC performed an analysis to create the CHSTP Priority Score, a layer that helps users visualize where there is a potentially high need to improve transit service for vulnerable populations to reach essential services in the Greater Philadelphia region. As a metropolitan planning organization, Delaware Valley Regional Planning Commission (DVRPC) is responsible for updating the region's Coordinated Human Services Transportation Plan (CHSTP). The CHSTP update engaged a variety of stakeholders to identify unmet needs and service gaps, recommend innovative transportation access solutions, and empower communities to climb "ladders of opportunity" toward greater social and economic mobility.As part of the CHSTP update, DVRPC created the CHSTP Priority Score Map Toolkit. This interactive web-based tool demonstrates disparities in access to essential services like hospitals, health clinics, recreational spaces, senior centers, and more in the Greater Philadelphia region. Users can view layers representing different datasets including the locations of essential services; bus routes, transit stops, and rail lines; transit walksheds; distributions of vulnerable populations like seniors, households in poverty, and people with disabilities; and areas where transit access is low.https://github.com/dvrpc/gis-chstp includes all code for the analysis.Below are several of the analyses included in this dataset.Vulnerable Populations answers the question, “Who lives here?” and highlights populations in need.Essential Services answers the question, “Where do people need to go?” and highlights areas with more services in the region.Population-Services Mismatch answers the question, “Where is there a gap between areas of need and essential services?” This layer highlights areas where there are higher numbers of vulnerable populations but fewer essential services and vice versa.Transit Accessibility answers the question, “How is transit service distributed?” and highlights areas in the region with lower transit accessibility.Priority Score answers the question, “Where can transit service be improved to help vulnerable populations access essential services?” This layer, the result of our analysis, highlights areas with higher numbers of vulnerable populations or essential services, but lower transit accessibility and vice versa.NameFieldSourceAdditional InfoNotesVULNERABLE POPULATIONSTotal Number of HouseholdshhACSB11001_001EAmerican Community Survey 5-Year Data (2018-2022)Total Number of PeoplepopACSB01003_001EAmerican Community Survey 5-Year Data (2018-2022)Households with 1 or More People with Disabilityhh1_disACSB22010, Estimate; Household received Food Stamps/SNAP in the past 12 monthsAmerican Community Survey 5-Year Data (2018-2022)Number of Households Below Poverty Linehh_povACSB17017 Estimate; Income in the past 12 months below poverty level:American Community Survey 5-Year Data (2018-2022)People 65 or Older_65olderACSB01001, summarized by sex and age groupsAmerican Community Survey 5-Year Data (2018-2022)Vulnerable Population Rankvul_pop_rankDVRPCcalculatedESSENTIAL SERVICESActivity Centers for Seniors or Disabledss_cntOverture MapOverture Map (2024)Food Storesfood_cntOverture MapOverture Map (2024)Health Care Facilitieshc_cntOverture MapOverture Map (2024)Number of Educational Institutionsschool_cntNCEShttps://nces.ed.gov/collegenavigator/ ; https://nces.ed.gov/surveys/pss/privateschoolsearch/ ; https://nces.ed.gov/ccd/schoolsearch/Parks/Open Space Presentos_checkDVRPCDVRPC Parks/Open Space (2016)Trailstrail_cntDVRPCDVRPC Circuit Trails (2020)Essential Services Totales_sumDVRPCcalculatedJobssum_jobsCensus LODESCensus LODESEssential Services Rankes_rankDVRPCcalculatedAccess Gapaccess_gap_rankDVRPCcalculate the difference of vulnerable population rank and essential service rank for access gapTRANSIT ACCESSIBILITYTransit Accessibilty Zonest_45min_zone_cnt ; t_zone_quantileDVRPCDVRPC Travel Models (2023), How many areas a person could access in a 45 minute transit tripEssential Services in 45 minute TAZ zones t_es_cnt; t_job_cnt; t_45min_es_job_avgOverture Maps, DVRPC travel modeljobs in block group and other essential services grouped into separate bins then averagedDaily Departures (by TAZ)total_departures, depart_quantileGTFS - SEPTA, NJTRANSIT, PATCOFrequency of serviceWalkability Rankwalkshed_quantileDVRPC pedestrian network, GTFS - SEPTA, NJTRANSIT, PATCOWalkability of the block group to transit stations/stopsTransit Accessibilty Ranktransit_access_rankDVRPCPriority Scorechstp_scoreDVRPCcalculated
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset supports the Philadelphia Council District Health Dashboard, an interactive web application that visualizes health disparities and social determinants of health across Philadelphia's 10 City Council Districts. The dashboard provides district-level insights to guide equitable policy and investment decisions by City Council members and the public.
Philadelphia residents experience drastically different health outcomes across the city – differences shaped by federal, state, and local policies rather than individual choices alone. This project maps key health indicators across all 10 Philadelphia City Council Districts to show how politics and geography intersect to shape Philadelphian health.
Data aggregated from original geographic units to City Council District boundaries using population-weighted methods.
data_v1.csv
- Main dataset containing health indicators by Philadelphia City Council Districtcodebook_v1.csv
- Complete metadata and variable documentationSupports policy analysis, community advocacy, academic research, and public health planning at the district level.
Amber Bolli, Tamara Rushovich, Ran Li, Stephanie Hernandez, Alina Schnake-Mahl
Transform Academia for Equity grant from Robert Wood Johnson Foundation
Philadelphia, City Council, Health Disparities, Social Determinants, Urban Health, Public Policy, Geospatial Analysis