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Prediction of asymptomatic COVID‐19 infections based on complex network
- Source :
- Optimal Control Applications & Methods
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- Novel coronavirus pneumonia (COVID‐19) epidemic outbreak at the end of 2019 and threaten global public health, social stability, and economic development, which is characterized by highly contagious and asymptomatic infections. At present, governments around the world are taking decisive action to limit the human and economic impact of COVID‐19, but very few interventions have been made to target the transmission of asymptomatic infected individuals. Thus, it is a quite crucial and complex problem to make accurate forecasts of epidemic trends, which many types of research dedicated to deal with it. In this article, we set up a novel COVID‐19 transmission model by introducing traditional SEIR (susceptible‐exposed‐infected‐removed) disease transmission models into complex network and propose an effective prediction algorithm based on the traditional machine learning algorithm TrustRank, which can predict asymptomatic infected individuals in a population contact network. Our simulation results show that our method largely outperforms the graph neural network algorithm for new coronary pneumonia prediction and our method is also robust and gives good results even if the network information is incomplete.
- Subjects :
- Special Issue Articles
Control and Optimization
Coronavirus disease 2019 (COVID-19)
Computer science
business.industry
Applied Mathematics
Special Issue Article
Complex network
Machine learning
computer.software_genre
Trustrank algorithm
Asymptomatic
machine learning
complex network
COVID‐19
Control and Systems Engineering
medicine
Artificial intelligence
medicine.symptom
business
computer
Software
Subjects
Details
- ISSN :
- 10991514 and 01432087
- Volume :
- 44
- Database :
- OpenAIRE
- Journal :
- Optimal Control Applications and Methods
- Accession number :
- edsair.doi.dedup.....c0ad99ae993383e2e9f412a661ba107c