Applied NanoFemto Technologies, LLC, Lowell, MA, USA.
Department of Pathology, Southern California Permanente Medical Group, Riverside, CA, USA.
Emerg Microbes Infect. 2020 Dec;9(1):2465-2473. doi: 10.1080/22221751.2020.1843973.
We previously described a mathematical model to simulate the course of the COVID-19 pandemic and try to predict how this outbreak might evolve in the following two months when the pandemic cases will drop significantly. Our original paper prepared in March 2020 analyzed the outbreaks of COVID-19 in the US and its selected states to identify the rise, peak, and decrease of cases within a given geographic population, as well as a rough calculation of accumulated total cases in this population from the beginning to the end of June 2020. The current report will describe how well the later actual trend from March to June fit our model and prediction. Similar analyses are also conducted to include countries other than the US. From such a wide global data analysis, our results demonstrated that different US states and countries showed dramatically different patterns of pandemic trend. The values and limitations of our modelling are discussed.
我们之前描述了一个数学模型来模拟 COVID-19 大流行的过程，并试图预测当大流行病例显著下降时，未来两个月疫情可能会如何演变。我们在 2020 年 3 月准备的原始论文分析了 COVID-19 在美及其选定的州的爆发情况，以确定在特定地理人群中病例的上升、高峰和下降情况，以及从 2020 年 3 月至 6 月底在该人群中累计总病例的粗略计算。本报告将描述从 3 月到 6 月的实际趋势与我们的模型和预测的拟合程度。还对包括美国以外的国家进行了类似的分析。从如此广泛的全球数据分析中，我们的结果表明，不同的美国州和国家显示出大流行趋势的明显不同模式。讨论了我们建模的价值和局限性。
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