论文标题
与比利时，法国，意大利，瑞士和纽约市数据相比
Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data
论文作者
论文摘要
使用经典的易感感染的经过恢复的流行病学模型，得出了Covid-19患者占用的床数的分析公式。分析曲线适用于比利时，法国，纽约市和瑞士的数据，相关系数超过98.8％，这表明使用此类宏观数据不需要更精细的模型。该拟合用于提取流行病上升阶段的加倍时间的估计，平均恢复时间以及需要医疗干预的人，平均住院时间。在不同的暴发之间可以观察到很大的变化。
Using the classical Susceptible-Infected-Recovered epidemiological model, an analytical formula is derived for the number of beds occupied by Covid-19 patients. The analytical curve is fitted to data in Belgium, France, New York City and Switzerland, with a correlation coefficient exceeding 98.8%, suggesting that finer models are unnecessary with such macroscopic data. The fitting is used to extract estimates of the doubling time in the ascending phase of the epidemic, the mean recovery time and, for those who require medical intervention, the mean hospitalization time. Large variations can be observed among different outbreaks.
