10.5281/zenodo.5542643
https://zenodo.org/records/5542643
oai:zenodo.org:5542643
Vahedi, Behzad
Behzad
Vahedi
0000-0001-5782-3831
University of Colorado Boulder, Boulder, USA
Karimzadeh, Morteza
Morteza
Karimzadeh
0000-0002-6498-1763
University of Colorado Boulder, Boulder, USA
Zoraghein, Hamidreza
Hamidreza
Zoraghein
0000-0001-5918-368X
Population Council, New York, USA
Spatiotemporal Prediction of COVID-19 Cases using Inter- and Intra-County Proxies of Human Interactions (dataset)
Zenodo
2021
COVID-19
spatiotemporal machine learning
GeoAI
Nature Communications
2021-10-01
10.5281/zenodo.5542642
v1.0
Creative Commons Attribution 4.0 International
This repository contains data (features) necessary to run STXGB model and accompanies the paper titled "Spatiotemporal Prediction of COVID-19 Cases using Inter- and Intra-County Proxies of Human Interactions".
STXGB is a spatiotemporal autoregressive model that predicts county-level new cases of COVID-19 in the coterminous US in 1- to 4-week prediction horizons using spatiotemporal lags of infection rates, human interactions, human mobility, and socioeconomic composition of counties as predictive features.