Network-Based Prediction of the 2019-nCoV Epidemic Outbreak in the Chinese Province Hubei

Abstract

At the moment of writing (12 February, 2020), the future evolution of the 2019-nCoV virus 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 2019-nCoV 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 a network-based method to predict the future prevalence of the 2019-nCoV virus in every city. Our results indicate that network-based modelling is beneficial for an accurate forecast of the epidemic outbreak.

arXiv commentOrdering of cities in Table 1 has been corrected; Prediction considers more recent observations

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Cited by in corpus (6)

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• A feedback SIR (fSIR) model highlights advantages and limitations of infection-dependent mitigation strategies
• Estimating impacts of covid19 on transport capacity in railway networks
• Unified modelling of epidemics by coupled dynamics via Monte-Carlo Markov Chain algorithms