Department of Telecommunications Engineering, University of Malaga, Malaga, Spain.
PLoS One. 2021 Jun 24;16(6):e0253004. doi: 10.1371/journal.pone.0253004. eCollection 2021.
Since the first case reported of SARS-CoV-2 the end of December 2019 in China, the number of cases quickly climbed following an exponential growth trend, demonstrating that a global pandemic is possible. As of December 3, 2020, the total number of cases reported are around 65,527,000 contagions worldwide, and 1,524,000 deaths affecting 218 countries and territories. In this scenario, Spain is one of the countries that has suffered in a hard way, the ongoing epidemic caused by the novel coronavirus SARS-CoV-2, namely COVID-19 disease. In this paper, we present the utilization of phenomenological epidemic models to characterize the two first outbreak waves of COVID-19 in Spain. The study is driven using a two-step phenomenological epidemic approach. First, we use a simple generalized growth model to fit the main parameters at the early epidemic phase; later, we apply our previous finding over a logistic growth model to that characterize both waves completely. The results show that even in the absence of accurate data series, it is possible to characterize the curves of case incidence, and construct a short-term forecast of 60 days in the near time horizon, in relation to the expected total duration of the pandemic.
自 2019 年 12 月底中国首次报告 SARS-CoV-2 病例以来,病例数量呈指数级增长趋势迅速攀升,表明全球大流行是有可能发生的。截至 2020 年 12 月 3 日,全球报告的病例总数约为 6552.7 万例,受影响的国家和地区有 218 个,死亡人数达 152.4 万。在这种情况下,西班牙是受新型冠状病毒 SARS-CoV-2 (即 COVID-19 疾病)影响严重的国家之一。本文介绍了利用现象学流行模型来描述西班牙 COVID-19 的前两波暴发。该研究使用两步现象学流行方法进行驱动。首先,我们使用一个简单的广义增长模型来拟合早期流行阶段的主要参数;之后,我们应用之前在 logistic 增长模型上的发现来完整地描述这两波流行。结果表明,即使在没有准确数据序列的情况下,也有可能描述病例发病率曲线,并在短时间内对未来 60 天进行短期预测,这与大流行的预期总持续时间有关。