PropertyValue
?:abstract
  • Researchers from various scientific disciplines have attempted to forecast the spread of the Coronavirus Disease 2019 (COVID-19). The proposed epidemic prediction methods range from basic curve fitting methods and traffic interaction models to machine-learning approaches. If we combine all these approaches, we obtain the Network Inference-based Prediction Algorithm (NIPA). In this paper, we analyse a diverse set of COVID-19 forecast algorithms, including several modifications of NIPA. Among the diverse set of algorithms that we evaluated, original NIPA performs best on forecasting the spread of COVID-19 in Hubei, China and in the Netherlands. In particular, we show that network-based forecasting is superior to any other forecasting algorithm.
is ?:annotates of
?:creator
?:journal
  • International_journal_of_forecasting
?:license
  • unk
?:publication_isRelatedTo_Disease
?:source
  • WHO
?:title
  • Comparing the accuracy of several network-based COVID-19 prediction algorithms
?:type
?:who_covidence_id
  • #842754
?:year
  • 2020

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