# Analysis of Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data

@article{Hickok2021AnalysisOS, title={Analysis of Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data}, author={Abigail Hickok and Deanna Needell and Mason A. Porter}, journal={ArXiv}, year={2021}, volume={abs/2107.09188} }

We develop a method for analyzing spatiotemporal anomalies in geospatial data using topological data analysis (TDA). To do this, we use persistent homology (PH), a tool from TDA that allows one to algorithmically detect geometric voids in a data set and quantify the persistence of these voids. We construct an efficient filtered simplicial complex (FSC) such that the voids in our FSC are in one-to-one correspondence with the anomalies. Our approach goes beyond simply identifying anomalies; it… Expand

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