ArticleApplied network science2020
Network-inference-based prediction of the COVID-19 epidemic outbreak in the Chinese province Hubei.
Article in Applied network science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Assessing COVID-19 transmission through school and family networks using population-level registry data from the Netherlands.Scientific reports · 2024Article
- A Networked Meta-Population Epidemic Model with Population Flow and Its Application to the Prediction of the COVID-19 Pandemic.Entropy (Basel, Switzerland) · 2024Article
- Duality between predictability and reconstructability in complex systems.Nature communications · 2024Article
- Modeling COVID-19 spread using multi-agent simulation with small-world network approach.BMC public health · 2024Article
- Quality assessment and community detection methods for anonymized mobility data in the Italian Covid context.Scientific reports · 2024Article
- Highway traffic flow prediction model with multi-component spatial-temporal graph convolution networks.Scientific reports · 2022Article
- Prediction of COVID-19 Infected Population for Indian States through a State Interaction Network-based SEIR Epidemic Model.IFAC-PapersOnLine · 2022Article
- Predicting COVID-19 community infection relative risk with a Dynamic Bayesian Network.Frontiers in public health · 2022Article
- Understanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models.Transactions in GIS : TG · 2021Article
- Epidemic size, trend and spatiotemporal mapping of SARS-CoV-2 using geographical information system in Alborz Province, Iran.BMC infectious diseases · 2021Article
- Effect of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) on reproductive system.Stem cell research · 2021Review
- Count regression models for COVID-19.Physica A · 2021Article
- The prediction of the lifetime of the new coronavirus in the USA using mathematical models.Soft computing · 2021Article
- Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography.Scientific reports · 2020Article
- COVID-19 and SARS-CoV-2. Modeling the present, looking at the future.Physics reports · 2020Review
- Effective containment explains subexponential growth in recent confirmed COVID-19 cases in China.Science (New York, N.Y.) · 2020Article
- Piecewise quadratic growth during the 2019 novel coronavirus epidemic.Infectious Disease Modelling · 2020Article
- SEIR modeling of the COVID-19 and its dynamics.Nonlinear dynamics · 2020Article
- A fractional-order SEIHDR model for COVID-19 with inter-city networked coupling effects.Nonlinear dynamics · 2020Review
- Memory-based meso-scale modeling of Covid-19: County-resolved timelines in Germany.Computational mechanics · 2020Article
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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