Kang et al (2020) Study Reproduction

In my reproduction of Kang et al (2020), I refined the network analysis utilized to calculate hospital catchment areas. The study measures access to ICU beds and ventilators in Chicago during the COVID-19 pandemic. By improving the quality of the speed limit data input to the network analysis, a more accurate model of access to Chicago ICU beds and ventilator emerges. During the replication, I furthered my experience working with network analyzes and became more comfortable using Python as a GIS.

Aspects of Kang et al could be developed to further the research topic and learning opportunities. The temporal or spatial extent of the study could be changed to give insight into the impacts of COVID-19 at different times or locations. Changing the extent could teach students how to source and assess similar data to replicate a study. Students can discuss the study to improve their critical understanding of geographic threats to validity (Schmitt). Kang et al provides a snapshot of the spatially heterogeneous impacts on the health geographies of Chicago.

Please follow this link to the entire reproduction study.

Please follow this link to the reproduction study’s Github repository.

References

Kang, Jeon-Young, Alexander Michels, Fangzheng Lyu, Shaohua Wang, Nelson Agbodo, Vincent L. Freeman, and Shaowen Wang. “Rapidly Measuring Spatial Accessibility of COVID-19 Healthcare Resources: A Case Study of Illinois, USA.” International Journal of Health Geographics 19, no. 1 (September 14, 2020): 36. https://doi.org/10.1186/s12942-020-00229-x.

Schmitt, Rolf R. “Threats to Validity Involving Geographic Space.” Socio-Economic Planning Sciences 12, no. 4 (January 1, 1978): 191–95. https://doi.org/10.1016/0038-0121(78)90044-7.