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

Journal article (2020)

Authors

B. Prasse Network Architectures and Services - EEMCS
M.A. Achterberg Network Architectures and Services - EEMCS
L. Ma Network Architectures and Services - EEMCS
P.F.A. Van Mieghem Network Architectures and Services - EEMCS
Research Group
Network Architectures and Services (EEMCS) (TU Delft)
Copyright: © 2020 B. Prasse, M.A. Achterberg, L. Ma, P.F.A. Van Mieghem
DOI: https://doi.org/10.1007/s41109-020-00274-2
More Info
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Published Date

2020

Language

English

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Quantum & Computer Engineering

Research Group

Network Architectures and Services

Abstract

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.