A collection of public data sources at sub-state geographic layers with informative information on public health outcomes.
For many public health research studies, data needs to be collected from a variety of public sources and the process can consume much of the research project. The Healthy Neighbrohoods Repository is an assembly of open access data from public sources that provide social, economic and environmental data below the state level The library consists of collected tables that connect the different data sources by the geographic identifier for a given year range. These tables are able to be analyzed using basic machine learning variable reduction techniques to develop models for informing further research, to inform evidence based screening methods, and to create risk assessment instruments.
The 2020 data release contains data from the following sources:
US Census - American Community Survey
Flordia Department Health - Florida Vital Statistics Top Causes of Mortality
Centers for Medicare and Medicaid Services - Service Area File for Medicare Fee for Service
Health Resource Services Administration - Area Health Resource File
Centers for Medicare and Medicaid Services - Quality Payment Program
The 2020 release can be accessed by downloading the 'hnb_2020.zip' file listed under 'Releases'
release_2020 All files included in the 2020 Release
_archive Old files from previous years
_raw Collected raw data, documentation, and code for staging
allocativ_2.1.yml Conda environment for use with repositories in the allocativ project
The repository uses the following file organization.
_data staged data files related to the project
_fig graphs, images, and maps related to the project
_archive old files no longer used
_raw raw data files, documentation, and code used for staging data
project Files related to specifc project
README Description, directory, notes
topic_prefix_suffix.ext
Topics are assigned based on content and listed in the directory README
alpha_ First draft of script, continuting with greek alphabet
omega_ Final draft of script
`
_code Development code script for working in an IDE
_book Jupyter notebook
_stage Data files that have been modified from raw source
_2020-01-01 Text scripts with results output with date it was run
_map 2D geographic display
_graph 2D chart or graph representing numeric data
Code scripts use the following style:
Whenever possible code scripts follow PEP-8 standards.
Python and R code scripts use the following elective options:
= for variable defintions (no <-)
'' for all character strings or arguments (no "")
A single space is provided between each element ex. columns = 'COlA'
Python and R code scripts use the following variable naming conventions:
data frames: df_xx
list: l_xx
arrays: a_xx
feature tables: df_X
target tables: df_Y
While the author (Andrew Cistola) is a Florida DOH employee and a University of Florida PhD student, these are NOT official publications by the Florida DOH, the University of Florida, or any other agency. No information is included in this repository that is not available to any member of the public. All information in this repository is available for public review and dissemination but is not to be used for making medical decisions. All code and data inside this repository is available for open source use per the terms of the included license.
This repository is part of the larger allocativ project dedicated to prodiving analytical tools that are 'open source for public health.' Learn more at https://allocativ.com.