论文标题
用于描述和预测Covid-19的大流行危机的数学模型
Mathematical Models for Describing and Predicting the COVID-19 Pandemic Crisis
论文作者
论文摘要
本文研究了两个确定性模型的扩展,用于描述新型冠状病毒大流行危机,SIR模型和SEIR模型。研究了模型并将其与实际数据进行比较,以支持每个描述的有效性并提取有关大流行的重要信息,例如基本的生殖数R0,这可能会提供有关每个模型预测的大流行率的有用信息。接下来,我们继续进行预测,并将SEIR模型与SIRD模型得出的更复杂的模型进行比较,以找到最适合描述和预测大流行危机的模型。旨在回答这个问题,与更复杂的模型相比,简单的SIRD模型是否能够做出可靠的预测并提供合适的信息。
The present article studies the extension of two deterministic models for describing the novel coronavirus pandemic crisis, the SIR model and the SEIR model. The models were studied and compared to real data in order to support the validity of each description and extract important information regarding the pandemic, such as the basic reproductive number R0, which might provide useful information concerning the rate of increase of the pandemic predicted by each model. We next proceed to making predictions and comparing more complex models derived from the SEIR model with the SIRD model, in order to find the most suitable one for describing and predicting the pandemic crisis. Aiming to answer the question if the simple SIRD model is able to make reliable predictions and deliver suitable information compared to more complex models.