Spatial accessibility of COVID-19 healthcare resources in Illinois, USA

This dataset contains all the code, notebooks, datasets used in the study conducted to measure the spatial accessibility of COVID-19 healthcare resources with a particular focus on Illinois, USA. Specifically, the dataset measures spatial access for people to hospitals and ICU beds in Illinois. The spatial accessibility is measured by the use of an enhanced two-step floating catchment area (E2FCA) method (Luo & Qi, 2009), which is an outcome of interactions between demands (i.e, # of potential patients; people) and supply (i.e., # of beds or physicians). The result is a map of spatial accessibility to hospital beds. It identifies which regions need more healthcare resources, such as the number of ICU beds and ventilators. This notebook serves as a guideline of which areas need more beds in the fight against COVID-19.

## What's Inside

A quick explanation of the components of the zip file

* `COVID-19Acc.ipynb` is a notebook for calculating spatial accessibility and `COVID-19Acc.html` is an export of the notebook as HTML.
* `Data` contains all of the data necessary for calculations:
      * `Chicago_Network.graphml`/`Illinois_Network.graphml` are GraphML files of the OSMNX street networks for Chicago and Illinois respectively.
      * `GridFile/` has hexagonal gridfiles for Chicago and Illinois
      * `HospitalData/` has shapefiles for the hospitals in Chicago and Illinois
      * `IL_zip_covid19/COVIDZip.json` has JSON file which contains COVID cases by zip code from IDPH
      * `PopData/` contains population data for Chicago and Illinois by census tract and zip code.
      * `Result/` is where we write out the results of the spatial accessibility measures
      * `SVI/`contains data about the Social Vulnerability Index (SVI)
* `img/` contains some images and HTML maps of the hospitals (the notebook generates the maps)
* `README.md` is the document you're currently reading!
* `requirements.txt` is a list of Python packages necessary to use the notebook (besides Jupyter/IPython). You can install the packages with `python3 -m pip install -r requirements.txt`