Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework

作者：Zhan, Choujun; Zheng, Yufan; Shao, Lujiao; Chen, Guanrong; Zhang, Haijun^*

来源：Information Sciences, 2023, 628: 469-487.

DOI：10.1016/j.ins.2023.02.001

• COVID-19 pandemic
• Multi-directional mutation
• Multiple variants
• Epidemiological model
• Public health intervention

The COVID-19 pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is a single-stranded positive-stranded RNA virus with a high multi -direc-tional mutation rate. Many new variants even have an immune-evading property, which means that some individuals with antibodies against one variant can be reinfected by other variants. As a result, the realistic is still suffering from new waves of COVID-19 by its new variants. How to control the transmission or even eradicate the COVID-19 pandemic remains a critical issue for the whole world. This work presents an epidemiological framework for mimicking the multi-directional mutation process of SARS-CoV-2 and the epidemic spread of COVID-19 under realistic scenarios considering multiple variants. The proposed framework is used to evaluate sin-gle and combined public health interventions, which include non-pharmaceutical interventions, pharmaceutical interventions, and vaccine interventions under the existence of multi-directional mutations of SARS-CoV-2. The results suggest that several combined intervention strategies give optimal results and are feasible, requiring only moderate levels of individual interventions. Fur-thermore, the results indicate that even if the mutation rate of SARS-CoV-2 decreased 100 times, the pandemic would still not be eradicated without appropriate public health interventions.