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  1. Joshua Gilman
  2. Bryant Grady
  3. Megan Seeley
  4. Xin Wang

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Description: Vijayan et al. (2021) examined whether spatial patterns existed in SARS-CoV-2 age-adjusted testing rates, age-adjusted diagnosis rates, and crude positivity rates in Los Angeles County (LAC), and used a spatial regression model to explore associations between COVID-19 crude positivity rates and a series of predictor variables. The original analyses are retrospective and use observational data collected from federal and private sources. Although not publicly available, we were able to obtain the original study data after contacting the authors. However, the analysis code was not made available, nor was information about the computational environment used. At the outset of a larger project on reproducibility and replicability in the human-environment and geographic sciences, we chose this study to reproduce on account of its application of spatial statistical methods common in spatial epidemiology and its compatibility with graduate student training in spatial statistics (e.g., spatial regression and pattern analysis) as well as its data and code availability. As a reproduction study, we aimed to independently generate identical results from the original publication.

License: CC-By Attribution 4.0 International


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