Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions
Measurements of human interaction through proxies such as social connectedness or movement patterns have proved useful for predictive modeling of COVID-19. In this study, the authors develop a spatiotemporal machine learning model to predict county level new cases in the US using a variety of predic...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-26742-6 |
| Summary: | Measurements of human interaction through proxies such as social connectedness or movement patterns have proved useful for predictive modeling of COVID-19. In this study, the authors develop a spatiotemporal machine learning model to predict county level new cases in the US using a variety of predictive features. |
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| ISSN: | 2041-1723 |