ArticleInternational journal of forecasting
Comparing the accuracy of several network-based COVID-19 prediction algorithms.
Article in International journal of forecasting. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- A simplicial epidemic model for COVID-19 spread analysis.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Transfer-recursive-ensemble learning for multi-day COVID-19 prediction in India using recurrent neural networks.Scientific reports · 2023Article
- Comparison of Three Prediction Models for Predicting Chronic Obstructive Pulmonary Disease in China.International journal of chronic obstructive pulmonary disease · 2023Article
- Autoregressive count data modeling on mobility patterns to predict cases of COVID-19 infection.Stochastic environmental research and risk assessment : research journal · 2022Article
- Predicting COVID-19 community infection relative risk with a Dynamic Bayesian Network.Frontiers in public health · 2022Article
- Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA.Quality & quantity · 2022Article
- Weighted butterfly optimization algorithm with intuitionistic fuzzy Gaussian function based adaptive-neuro fuzzy inference system for covid-19 prediction.Materials today. Proceedings · 2022Article
- On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19.European journal of operational research · 2021Article
- Establishment of epidemic early warning index system and optimization of infectious disease model: Analysis on monitoring data of public health emergencies.International journal of disaster risk reduction : IJDRR · 2021Article
- COVID-19 prediction models: a systematic literature review.Osong public health and research perspectives · 2021Article
- Article
- Multitask learning and nonlinear optimal control of the COVID-19 outbreak: A geometric programming approach.Annual reviews in control · 2021Article
- Article
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6 authors.
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Abstract
Researchers from various scientific disciplines have attempted to forecast the spread of 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 algorithms that we evaluated, the original NIPA performed best at 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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