作者
Massimo A Achterberg, Bastian Prasse, Long Ma, Stojan Trajanovski, Maksim Kitsak, Piet Van Mieghem
发表日期
2022/4/1
期刊
International journal of forecasting
卷号
38
期号
2
页码范围
489-504
出版商
Elsevier
简介
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.
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MA Achterberg, B Prasse, L Ma, S Trajanovski… - International journal of forecasting, 2022