Healthcare Resources in Illinois: Reproducing Kang et al. (2020)

For this reproduction of the Kang et al. (2020) study, I focused on implementing suggested modifications of improving speed limit calculations and creating a weighted overlay. These improvements resulted in a new speed limit data output and two accessibility map visualizations to compare to the original Kang et al. (2020) study. By improving speed limit data within the study, it better reflects the accessibility of areas by assigning speed limits by ‘highway types.’ More specifically, these changes showcased a shrunken area of the highest accessibility, indicating Kang et al. (2020) may be overestimating hospital accessibility within regions of Chicago. These modifications helped to improve the study’s construct validity with a more accurate method of identifying accessibility.

Also, this reproduction focused on Chicago (rather than all of Illinois) because of the resources needed to conduct such research. If one were to take this model of hospital accessibility to a greater geographical scale, they should note the computing resources needed to complete this model. This reproduction both improved my understanding of geographic concepts (such as how Kang uses catchment areas and hexagonal grids) while also helping me to develop a critical lens on research methods.

Check out the reproduced study here

Check out the Github repository for the replication here

I would like to specifically thank fellow students Grace Sokolow and Audrey Park for the collaboration on this replication.

References

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.