Dynamic evolution of an SVEIR model with variants and non-pharmaceutical interventions for controlling COVID-19

Abstract

The epidemiological characteristics and distributions of two epidemics in Fujian Province of Southeast China were attributed to the complex interactions among variant, host, and non-pharmaceutical interventions (NPIs). All reported cases in the Putian epidemic (September 8–October 2, 2021, Delta variant B.1.617.2) and Fuzhou epidemic (October 22–November 18, 2022, Omicron variant BA.5.2) were classified by sex, age group, occupation, and location in this study. Using surveillance data from the Fujian Provincial Center for Disease Control and Prevention, we established a virus-oriented SVEIR (Susceptible–Vaccinated–Exposed–Infected–Recovered) model to investigate the dynamic evolution features of these two variants and the effects of NPIs. The optimal simulations were carried out with variants and scenario investigations. The scenario investigations showed that NPIs significantly reduced the transmission risk and infection scales of COVID-19, and that the Omicron variant was more infectious than the Delta variant. Moreover, the dynamic investigations revealed the increasing tendencies from Delta to Omicron, such as the basic reproduction number, infection rate, percentage of high-risk cases, and the growth rate. Decreasing tendencies were also identified, such as the average recovery period, the awareness delay, and the percentage of symptomatic cases. This study highlighted that NPIs played critical roles in successfully containing the two epidemics. Such interventions are strongly recommended to public health policymakers.