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

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

Bastian Prasse, Massimo A. Achterberg, Long Ma, Piet Van Mieghem

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.

2020

epidemiology, coronavirus, covid-19, SIR model, network inference

10.1007/s41109-020-00274-2

Epidemiology and Health

Korean Society of Epidemiology

Applied mathematics. Quantitative methods