Abstract
Evaluating the characteristics of emerging SARS-CoV-2 variants of concern is essential to inform pandemic risk assessment. A variant may grow faster if it produces a larger number of secondary infections (“R advantage”) or if the timing of secondary infections (generation time) is better. So far, assessments have largely focused on deriving the R advantage assuming the generation time was unchanged. Yet, knowledge of both is needed to anticipate the impact. Here, we develop an analytical framework to investigate the contribution of both the R advantage and generation time to the growth advantage of a variant. It is known that selection on a variant with larger R increases with levels of transmission in the community. We additionally show that variants conferring earlier transmission are more strongly favored when the historical strains have fast epidemic growth, while variants conferring later transmission are more strongly favored when historical strains have slow or negative growth. We develop these conceptual insights into a new statistical framework to infer both the R advantage and generation time of a variant. On simulated data, our framework correctly estimates both parameters when it covers time periods characterized by different epidemiological contexts. Applied to data for the Alpha and Delta variants in England and in Europe, we find that Alpha confers a+54% [95% CI, 45-63%] R advantage compared to previous strains, and Delta +140% [98-182%] compared to Alpha, and mean generation times are similar to historical strains for both variants. This work helps interpret variant frequency dynamics and will strengthen risk assessment for future variants of concern.
Keywords: SARS-CoV-2; adaptation; epidemiology; evolutionary biology; global health; variants of concern; viruses.
【저자키워드】 viruses, SARS-CoV-2, Epidemiology, variants of concern, global health, Evolutionary biology, adaptation, 【초록키워드】 viruses, Europe, pandemic, knowledge, variant, SARS-CoV-2 variant, Delta, risk, Transmission, delta variant, variants, Risk assessment, global health, Epidemic, Secondary infection, Characteristics, Community, Alpha, epidemiological, adaptation, estimate, assessment, England, Strains, secondary infections, Delta variants, Frequency, strain, Generation time, assessments, growth, help, alpha and delta variants, statistical framework, parameter, growth advantage, develop, characterized, increase, faster, Evaluating, the timing, 【제목키워드】 SARS-CoV-2 variant, Epidemics, Selection, profile,