Attributed network embedding model for exposing COVID-19 spread trajectory archetypes
Author:
Funder
National Science Foundation RAPID project
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41060-024-00627-5.pdf
Reference66 articles.
1. Castro, M.C., et al.: Spatiotemporal pattern of COVID-19 spread in Brazil. Science 372(6544), 821–826 (2021)
2. Li, Q., et al.: unraveling the dynamic importance of county-level features in trajectory of COVID-19. Sci. Rep. 11(1), 1–11 (2021)
3. Dowd, J.B., et al.: Demographic science aids in understanding the spread and fatality rates of COVID-19. Proc. Natl. Acad. Sci. 117(18), 9696–9698 (2020)
4. Benzell, S.G., Collis, A., Nicolaides, C.: Rationing social contact during the COVID-19 pandemic: transmission risk and social benefits of US locations. Proc. Natl. Acad. Sci. 117(26), 14642–14644 (2020)
5. Jia, J.S., et al.: Population flow drives spatio-temporal distribution of COVID-19 in China. Nature 582(7812), 389–394 (2020)
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