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Adequacy of Logistic models for describing the dynamics of COVID-19 pandemic

机译:用于描述Covid-19流行性动态的物流模型的充分性

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摘要

Logistic models have been widely used for modelling the ongoing COVID-19 pandemic. This study used the data for Kuwait to assess the adequacy of the two most commonly used logistic models (Verhulst and Richards models) for describing the dynamics COVID-19. Specifically, the study assessed the predictive performance of these two models and the practical identifiability of their parameters. Two model calibration approaches were adopted. In the first approach, all the data was used to fit the models as per the heuristic model fitting method. In the second approach, only the first half of the data was used for calibrating the models, while the other half was left for validating the models. Analysis of the obtained calibration and validation results have indicated that parameters of the two models cannot be identified with high certainty from COVID-19 data. Further, the models shown to have structural problems as they could not predict reasonably the validation data. Therefore, they should not be used for long-term predictions of COVID-19. Suggestion have been made for improving the performances of the models.
机译:物流模型已被广泛用于建模正在进行的Covid-19大流行。本研究使用了科威特的数据来评估用于描述动态Covid-19的两个最常用的物流模型(Verhulst和Richards模型)的充分性。具体而言,该研究评估了这两种模型的预测性能和其参数的实际可识别性。采用了两种模型校准方法。在第一种方法中,所有数据都用于根据启发式模型拟合方法拟合模型。在第二种方法中,仅使用上半部的数据用于校准模型,而另一半留需用于验证模型。对获得的校准和验证结果的分析表明,无法从Covid-19数据高确定两个模型的参数。此外,显示的模型具有结构问题,因为它们无法接受可合理地预测验证数据。因此,它们不应用于Covid-19的长期预测。建议改善模型的表现。

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