We mapped the 2020-2023 daily Covid-19 case data from the World Health Organization (WHO) to the original SIR model of Karmack and McKendrick for multiple pandemic recurrences due to the evolution of the virus to different variants in forty countries worldwide. The aim of the study was to determine how the SIR parameters are changing as the virus evolved into variants. Each peak in cases was analyzed separately for each country and the parameters: r_eff (pandemic R-parameter), L_eff (average number of days an individual is infective) and α (the rate of infection for contacts between the set of susceptible persons and the set of infected persons) were computed. Each peak was mapped to circulating variants for each country and the SIR parameters (r_eff, L_eff, α) were averaged over each variant using their values in peaks where 70% of the variant sequences identified belonged to a single variant. This analysis showed that on average, compared to the original Wuhan variant (α = 0.2), the parameter α has increased to α = 0.5 for the Omicron variants. The value of r_eff has decreased from around 3.8 to 2.0 and L_eff has decreased from 15 days to 10 days. This is as would be expected of a virus that is coming to equilibrium by evolving to increase its infectivity while reducing the effects of infections on the host.

中文翻译：

---

全球 Covid-19 多个变体数据的参数化：SAR-Cov2 病毒如何演变？

我们将世界卫生组织 (WHO) 的 2020-2023 年每日 Covid-19 病例数据映射到 Karmack 和 McKendrick 的原始 SIR 模型，以了解由于病毒在全球 40 个国家进化为不同变体而导致的多次大流行复发。该研究的目的是确定当病毒进化成变种时，SIR 参数如何变化。分别分析每个国家/地区的每个病例峰值和参数：r _eff（流行病 R 参数）、L _eff（个体感染的平均天数）和 α（易感人群之间接触的感染率）和感染者的集合）进行了计算。每个峰值都映射到每个国家的流行变体，并且使用峰值中的值对每个变体的 SIR 参数（r _eff、 L _eff、α）进行平均，其中 70% 的已识别变体序列属于单个变体。该分析表明，平均而言，与原始武汉变种（α = 0.2）相比，Omicron 变种的参数 α 已增加至 α = 0.5。 r _eff值从 3.8 左右下降到 2.0，L _{eff 值}从 15 天下降到 10 天。这正如人们所期望的那样，病毒通过进化来增加其传染性，同时减少感染对宿主的影响，从而达到平衡。