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/tree/master/csse_covid_19_data/csse_covid_19_daily_reports

This dataset contains daily case reports compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE).

The Seeding Resilience initiative has aggregated food-related resources available in Buffalo, NY.

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.

This data is from the 2017 release of the United States Department of Agriculture Economic Research Service (USDA ERS)'s Food Access Research Atlas.

This dataset reports the self-response rate of planned census tracts in Erie County to the 2020 Census. The U.S Census Bureau is tracking self-response rates nationwide to help ensure a complete and accurate count.

Source link: https://2020census.gov/en/response-rates.html?#

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.

This dataset reports the self-response rate of Buffalo, NY to the 2020 Census. The U.S Census Bureau is tracking self-response rates nationwide to help ensure a complete and accurate count.

Source link: https://2020census.gov/en/response-rates.html?#

This is the filtered dataset from the 500 Cities project 2019 release. This dataset includes 2017, 2016 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2017, 2016), Census Bureau 2010 census population data, and American Community Survey (ACS) 2013-2017, 2012-2016 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures (all teeth lost, dental visits, mammograms, pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) from the 2016 BRFSS that are the same in the 2019 release as the previous 2018 release. More information about the methodology can be found at www.cdc.gov/500cities.

This data is sourced from The COVID Tracking Project, a site includes web scraping data from individual state health department agencies displaying information related to positive, negative, and pending tests across the United States.