Corpus ID: 237571648

Non-stationary spatio-temporal point process modeling for high-resolution COVID-19 data

@inproceedings{Dong2021NonstationarySP,
  title={Non-stationary spatio-temporal point process modeling for high-resolution COVID-19 data},
  author={Zheng Dong and Shixiang Zhu and Yao Xie and Jorge Mateu and Francisco J. Rodr'iguez-Cort'es},
  year={2021}
}
Most COVID-19 studies commonly report figures of the overall infection at a stateor county-level, reporting the aggregated number of cases in a particular region at one time. This aggregation tends to miss out on fine details of the propagation patterns of the virus. This paper is motivated by analyzing a high-resolution COVID-19 dataset in Cali, Colombia, that provides every confirmed case’s exact location and time information, offering vital insights for the spatio-temporal interaction… Expand

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