Can we predict the occurrence of COVID-19 cases? Considerations using a simple model of growth
Can we predict the occurrence of COVID-19 cases? Considerations using a simple model of growth
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DOI：
10.1016/j.scitotenv.2020.138834
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发表时间：
2020-08-01
影响因子：
9.8
通讯作者：
Pires, Luiz F.
中科院分区：
文献类型：
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作者：
Cassaro, Fabio A. M.;Pires, Luiz F.
本研究旨在提供一个简单的模型，以跟踪COVID-19（CV-19）大流行在不同国家的演变。累积分布函数（CDF）及其一阶导数用于这项任务。模拟显示，根据最初的CV-19病例（第1、2或3周）预测大流行将如何演变几乎是不可能的。然而，这里提出的结果表明，这种方法可以作为一种替代指数增长模型，传统上用作预测模型，并作为一个有价值的工具，调查如何保护措施正在改变大流行的演变。
This study aimed to present a simple model to follow the evolution of the COVID-19 (CV-19) pandemic in different countries. The cumulative distribution function (CDF) and its first derivative were employed for this task. The simulations showed that it is almost impossible to predict based on the initial CV-19 cases (1st 2nd or 3rd weeks) how the pandemic will evolve. However, the results presented here revealed that this approach can be used as an alternative for the exponential growth model, traditionally employed as a prediction model, and serve as a valuable tool for investigating how protective measures are changing the evolution of the pandemic.