Reproduction and Reanalysis of Kang et al 2020 Spatial Accessibility of COVID-19 Health Care Resources
This study is a replication of:
Kang, J. Y., A. Michels, F. Lyu, Shaohua Wang, N. Agbodo, V. L. Freeman, and Shaowen Wang. 2020. Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA. International Journal of Health Geographics 19 (1):1–17. DOI:10.1186/s12942-020-00229-x.
The original paper is an implementation of the enhanced two-step floating catchment area (E2FCA) method of spatial accessibility measurement in health geography, applied to accessibility of intensive care unit beds and ventilators in the state of Illinois for vulnerable people aged 50 or over or diagnosed with COVID-19. The study is significant in its use of parallel processing and cyberinfrastructure, implemented on the CyberGISX system, and the study provides reproducibility and transparency for the COVID-19 spatial health services accessibility dashboard, Where COVID-19.
- Joseph Holler
- Kufre Udoh
- Derrick Burt
- Peter Kedron
- Benjamin Cordola
- GEOG 323 Classes of Spring 2021 and Fall 2021
- Preregistration: https://osf.io/my_study
- Publication: https://doi.org/my_study
- Pre-analysis plan: docs/report/preanalysis.pdf
- Study report: docs/report/report.pdf
- Manuscript: docs/manuscript/manuscript.pdf
The contents of this repository are outlined in three tables:
- Data: data/data_metadata.csv
- Procedures: procedure/procedure_metadata.csv
- Results: results/results_metadata.csv
The template_readme.md file contains more information on structure and rationale of this research template repository, as well as important references and licenses.
The content below is from the root
readme.md
document for the original Where COVID-19 Accessibility repository as of April 21, 2021.
Authors: Jeon-Young Kang, Alexander Michels, Fangzheng Lyu, Shaohua Wang, Nelson Agbodo, Vincent L. Freeman & Shaowen Wang
Paper: https://doi.org/10.1186/s12942-020-00229-x
Abstract: This aims to measure spatial access for people to hospitals in Illinois. The spatial accessibiilty 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.
To view accessibility measures updated daily, check out: https://wherecovid19.cigi.illinois.edu/
A quick explanation of the components:
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 IllinoisHospitalData/
has shapefiles for the hospitals in Chicago and IllinoisIL_zip_covid19/COVIDZip.json
has JSON file which contains COVID cases by zip code from IDPHPopData/
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 measuresSVI/
contains data about the Social Vulnerability Index (SVI)