论文标题
我们可以使用易感感染感染的(SIR)模型从死亡和感染性病例数据中估算什么? COVID-19大流行的案例研究
What Can We Estimate from Fatality and Infectious Case Data using the Susceptible-Infected-Removed (SIR) model? A case Study of Covid-19 Pandemic
论文作者
论文摘要
2019年底首次报道了几乎所有国家的迅速传播的Covid-19。由于其高度感染力,全世界的国家都采取了极为严格的措施来控制其传播。自从这个主要大流行的最早阶段以来,学者们进行了大量研究,以了解疾病,开发药物,疫苗和测试,并建模其传播。在这些研究中,对于早期阶段的流行参数的估计,已经投入了大量努力,对于受到Covid-19的影响的国家来说,预测流行病的过程,但是控制过程中控制的变化使模型过程变得复杂。在本文中,使用早期数据讨论了基本繁殖数量的确定基本繁殖数,感染周期的平均持续时间,流行波峰值的估计。在2020年1月22日至2020年4月18日期间,每日病例报告和日常死亡人数使用易感性感染的(SIR)模型评估。对于每个国家 /地区,分析了在5%误差范围内拟合累积感染性病例数据的SIR模型。据观察,只有在流行病的传播已经结束的情况下(对于中国和韩国,在本案中,传染性时期的基本繁殖数量和平均持续时间才能估算。然而,可以从归一化数据中稳健地估算受感染个体比例的拐点的最大和时机的时间和时机。通过将预测与实际数据进行比较来验证估计值表明,只要保留了锁定措施,就可以实现除美国以外的所有国家的预测。
The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its spread. Since the earliest stages of this major pandemic, academics have done a huge amount of research in order to understand the disease, develop medication, vaccines and tests, and model its spread. Among these studies, a great deal of effort has been invested in the estimation of epidemic parameters in the early stage, for the countries affected by Covid-19, hence to predict the course of the epidemic but the variability of the controls over the course of the epidemic complicated the modeling processes. In this article, the determination of the basic reproduction number, the mean duration of the infectious period, the estimation of the timing of the peak of the epidemic wave is discussed using early phase data. Daily case reports and daily fatalities for ten countries over the period January 22, 2020 - April 18, 2020 are evaluated using the Susceptible-Infected-Removed (SIR) model. For each country, the SIR models fitting cumulative infective case data within 5% error are analysed. It is observed that the basic reproduction number and the mean duration of the infectious period can be estimated only in cases where the spread of the epidemic is over (for China and South Korea in the present case). Nevertheless, it is shown that the timing of the maximum and timings of the inflection points of the proportion of infected individuals can be robustly estimated from the normalized data. The validation of the estimates by comparing the predictions with actual data has shown that the predictions were realised for all countries except USA, as long as lock-down measures were retained.