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

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

14 Citations (Scopus)
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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.

Original languageEnglish
Article number35
Pages (from-to)1-11
Number of pages11
JournalApplied Network Science
Issue number1
Publication statusPublished - 2020


  • Coronavirus
  • COVID-19
  • Epidemiology
  • Network inference
  • SIR model


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