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

被引：39

作者：

Prasse, Bastian ^{[1
]}

Achterberg, Massimo A. ^{[1
]}

Ma, Long ^{[1
]}

Van Mieghem, Piet ^{[1
]}

机构：

[1] Delft Univ Technol, Fac Elect Engn Math & Comp Sci, POB 5031, NL-2600 GA Delft, Netherlands

来源：

APPLIED NETWORK SCIENCE | 2020年 / 5卷 / 01期

关键词：

Network inference; Epidemiology; COVID-19; Coronavirus; SIR model; CORONAVIRUS; TRANSMISSION; COMPLEX; WUHAN;

D O I：

10.1007/s41109-020-00274-2

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

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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页数：11

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