论文标题
COVID-19-19
COVID-19 epidemic outcome predictions based on logistic fitting and estimation of its reliability
论文作者
论文摘要
自从2019年底的Covid-19流行病的第一次爆发以来，已经提供了有关世界所有国家的感染，死亡和恢复次数的数据，并且该数据可用于统计分析。本文的主要兴趣是，逻辑方程如何在世界上任何地区的Covid-19疫情预测结果，假设测试过程的方法论，即数据收集方法和社交行为在随着时间的流逝过程中都不会发生变化。除了社会相关性外，这项研究还具有两个科学目的：我们调查了一个简单的饱和度模型是否可以描述Covid-19的流行趋势，如果是这样，我们想确定在流行病中，拟合参数从哪个点提供可靠的预测。我们还根据逻辑模型和2020年3月27日可用的数据对几个国家的这种流行的结果进行估算。根据中国饱和案例，我们设法找到了一些标准来判断预测的可靠性。
Since the first outbreak of the COVID-19 epidemic at the end of 2019, data has been made available on the number of infections, deaths and recoveries for all countries of the World, and that data can be used for statistical analysis. The primary interest of this paper is how well the logistic equation can predict the outcome of COVID-19 epidemic in any regions of the World assuming that the methodology of the testing process, namely the data collection method and social behavior is not changing over the course of time. Besides the social relevance, this study has two scientific purposes: we investigate if a simple saturation model can describe the trend of the COVID-19 epidemic and if so, we would like to determine, from which point during the epidemic the fitting parameters provide reliable predictions. We also give estimations for the outcome of this epidemic in several countries based on the logistic model and the data available on 27 March, 2020. Based on the saturated cases in China, we have managed to find some criteria to judge the reliability of the predictions.
