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A Review of Graph Neural Networks in Epidemic Modeling
April 1, 2024, 4:41 a.m. | Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
cs.LG updates on arXiv.org arxiv.org
Abstract: Since the onset of the COVID-19 pandemic, there has been a growing interest in studying epidemiological models. Traditional mechanistic models mathematically describe the transmission mechanisms of infectious diseases. However, they often fall short when confronted with the growing challenges of today. Consequently, Graph Neural Networks (GNNs) have emerged as a progressively popular tool in epidemic research. In this paper, we endeavor to furnish a comprehensive review of GNNs in epidemic tasks and highlight potential future …
abstract arxiv challenges covid covid-19 covid-19 pandemic cs.lg cs.si diseases epidemic gnns graph graph neural networks however infectious diseases modeling networks neural networks pandemic physics.soc-ph q-bio.pe review studying type
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