Sanchez-Caballero Samuel, Selles Miguel A, Peydro Miguel A, Perez-Bernabeu Elena
Institute of Manufacturing and Design, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.
Technological Institute of Materials, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.
J Clin Med. 2020 May 20;9(5):1547. doi: 10.3390/jcm9051547.
The present work develops an accurate prediction model of the COVID-19 pandemic, capable not only of fitting data with a high regression coefficient but also to predict the overall infections and the infection peak day as well. The model is based on the Verhulst equation, which has been used to fit the data of the COVID-19 spread in China, Italy, and Spain. This model has been used to predict both the infection peak day, and the total infected people in Italy and Spain. With this prediction model, the overall infections, the infection peak, and date can accurately be predicted one week before they occur. According to the study, the infection peak took place on 23 March in Italy, and on 29 March in Spain. Moreover, the influence of the total and partial lockdowns has been studied, without finding any meaningful difference in the disease spread. However, the infected population, and the rate of new infections at the start of the lockdown, seem to play an important role in the infection spread. The developed model is not only an important tool to predict the disease spread, but also gives some significant clues about the main factors that affect to the COVID-19 spread, and quantifies the effects of partial and total lockdowns as well.
本研究建立了一个准确的新冠疫情预测模型，该模型不仅能够以高回归系数拟合数据，还能预测总体感染情况以及感染高峰日。该模型基于Verhulst方程，已被用于拟合中国、意大利和西班牙的新冠疫情传播数据。此模型已用于预测意大利和西班牙的感染高峰日以及总感染人数。借助这个预测模型，可以在感染高峰和总感染人数出现前一周准确预测其情况。根据研究，意大利的感染高峰出现在3月23日，西班牙的感染高峰出现在3月29日。此外，还研究了全面和部分封锁措施的影响，未发现疾病传播有任何显著差异。然而，封锁开始时的感染人群和新增感染率似乎在感染传播中起着重要作用。所建立的模型不仅是预测疾病传播的重要工具，还为影响新冠疫情传播的主要因素提供了一些重要线索，并对部分和全面封锁措施的效果进行了量化。
