Population over 60 (S0101), Women Who Had a Birth in the Past 12 Months (B13002), Below Poverty Level (B17015), No Health Insurance (B27001), Household Receiving SNAP Assistance (S2201), No Internet Access (B28002), Total Population (B01003) and Language at Home (C16001)

Cross-tabulation of the 2019 release of the Centers for Disease Control & Prevention's Local Data For Better Health from the 500 Cities Project: https://covid19response.buffalony.gov/Health/Local-Data-For-Better-Health-2019-Release-500-Citi/wpzi-9qpb.

Definitive Healthcare designed the COVID-19 Capacity Predictor, an interactive, visual Tableau map to help predict where, and when, important resources should be allocated as case volume continues to grow.

In order to build this dashboard, Definitive Healthcare’s data science team combined proprietary Definitive Healthcare ICU and ventilator data with public information about population distribution, COVID-19 cases, and COVID-19 testing – and fit an exponential function to the data to model the growth. The data behind this dashboard is presented here and updated daily.

Source link: https://github.com/CSSEGISandData/COVID-19

This data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE).

Social vulnerability refers to the socioeconomic and demographic factors that affect the resilience of communities. Studies have shown that in disaster events the socially vulnerable are more likely to be adversely affected, i.e. they are less likely to recover and more likely to die. Effectively addressing social vulnerability decreases both human suffering and the economic loss related to providing social services and public assistance after a disaster. The development of a social vulnerability index (SVI) from 15 census variables at the census tract level was built by the CDC for use in emergency management.