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EpiGNN: Exploring Spatial Transmission with Graph Neural Network for Regional Epidemic Forecasting. (arXiv:2208.11517v1 [q-bio.QM])
cs.LG updates on arXiv.org arxiv.org
Epidemic forecasting is the key to effective control of epidemic transmission
and helps the world mitigate the crisis that threatens public health. To better
understand the transmission and evolution of epidemics, we propose EpiGNN, a
graph neural network-based model for epidemic forecasting. Specifically, we
design a transmission risk encoding module to characterize local and global
spatial effects of regions in epidemic processes and incorporate them into the
model. Meanwhile, we develop a Region-Aware Graph Learner (RAGL) that takes
transmission risk, …
arxiv bio epidemic forecasting graph graph neural network network neural network