Network-inference-based prediction of the COVID-19 epidemic outbreak in the Chinese province Hubei

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作者
Bastian Prasse
Massimo A. Achterberg
Long Ma
Piet Van Mieghem
机构
[1] Faculty of Electrical Engineering,
[2] Mathematics and Computer Science,undefined
[3] Delft University of Technology,undefined
来源
Applied Network Science | / 5卷
关键词
Network inference; Epidemiology; COVID-19; Coronavirus; SIR model;
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摘要
At the moment of writing, the future evolution of the COVID-19 epidemic is unclear. Predictions of the further course of the epidemic are decisive to deploy targeted disease control measures. We consider a network-based model to describe the COVID-19 epidemic in the Hubei province. The network is composed of the cities in Hubei and their interactions (e.g., traffic flow). However, the precise interactions between cities is unknown and must be inferred from observing the epidemic. We propose the Network-Inference-Based Prediction Algorithm (NIPA) to forecast the future prevalence of the COVID-19 epidemic in every city. Our results indicate that NIPA is beneficial for an accurate forecast of the epidemic outbreak.
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