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.

Details

Title
Network-inference-based prediction of the COVID-19 epidemic outbreak in the Chinese province Hubei
Author
Prasse Bastian 1   VIAFID ORCID Logo  ; Achterberg, Massimo A 1 ; Long, Ma 1 ; Piet, Van Mieghem 1 

1  Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands (GRID:grid.5292.c) (ISNI:0000 0001 2097 4740) 
Publication year
2020
Publication date
Dec 2020
Publisher
Springer Nature B.V.
e-ISSN
23648228
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1007/s41109-020-00274-2
ProQuest document ID
2421245467
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.