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

Journal Article (2020)
Author(s)

Bastian Prasse (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Massimo A. Achterberg (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Long Ma (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Piet Van Mieghem (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Network Architectures and Services
DOI related publication
https://doi.org/10.1007/s41109-020-00274-2 Final published version
More Info
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Publication Year
2020
Language
English
Research Group
Network Architectures and Services
Issue number
1
Volume number
5
Article number
35
Pages (from-to)
1-11
Downloads counter
274
Collections
Institutional Repository
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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.