Reproduction of Mollalo et al 2020 GIS-based spatial modeling of COVID-19 incidence rate in the continental United States
This is a reproduction study of:
Mollalo, A., Vahedi, B. and Rivera, K.M., 2020. GIS-based spatial modeling of COVID-19 incidence rate in the continental United States. Science of the total environment, 728, p.138884. DOI: 10.1016/j.scitotenv.2020.138884
This reproduction study is part of a publication:
Kedron, P., Bardin, S., Holler, J., Gilman, J., Grady, B., Seeley, M., Wang, X. and Yang, W. (2023), A Framework for Moving Beyond Computational Reproducibility: Lessons from Three Reproductions of Geographical Analyses of COVID-19. Geogr Anal. https://doi.org/10.1111/gean.12370
Mollalo et al. (2020) investigated county-level variations of COVID-19 incidence across the continental United States using spatial lag and spatial error models to investigate spatial dependence as well as geographically weighted regression (GWR) and multiscale GWR (MGWR) models to locally examine spatial non-stationarity. The original analyses are retrospective and use observational data collected from federal and other public sources. Although not publicly available, we were able to obtain the original data based on the authors's description. However, the analysis code was not made available.
- Peter Kedron
- Joseph Holler
- Sarah Bardin
- Joshua Gilman
- Bryant Grady
- Megan Seeley
- Xin Wang
- Wenxin Yang
Link your reports, manuscripts, presentations, publication DOIs, preregistrations, etc. here. Delete this instruction and unused list items from your final repository. Adjust the file names and paths and add additional items as necessary.
- Pre-analysis plan and study report: docs/report/RP-Mollalo-Report.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.