1964. Pre-existing Population Immunity and SARS-CoV-2 Variant Dynamics in the United States: An Ecological Study. (15th December 2022)

• Record Type: Journal Article
• Authors: Ankomah, Pierre; Siedner, Mark; Bhattacharyya, Roby P
• Is Part Of: Open forum infectious diseases. Volume 9:(2022)Supplement 2
• Publication Date: 2022-12-15
• Subjects: Communicable diseases -- Periodicals; Medical microbiology -- Periodicals; Infection -- Periodicals; 616.9
• DOI: 10.1093/ofid/ofac492.1589
• Languages: English
• ISSNs: 2328-8957

Abstract

Abstract: Background: The relative advantage of each new variant of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) depends on its inherent transmissibility and capacity to evade pre-existing immunity. Delta and Omicron are variants of concern that have immune-evasive properties and rapidly displaced variants that preceded their emergence. In the United States, SARS-CoV-2 immunity varies considerably by state, which provides a natural experiment to evaluate the effect of population-level immunity on takeover dynamics of new variants. We hypothesized that if immune evasion was a major driver of fitness compared with previously prevalent variants, Delta and Omicron would become the dominant variants faster in states with higher immunity. Methods: We evaluated changes in variant proportion per week from the first detection of Delta or Omicron in a state until they consistently represented >90% of all sequenced genomes. We used logistic growth curves to characterize the dynamics of variant takeover, evaluating three outcomes: 1) takeover rate, defined as the maximum slope of the logistic curve; 2) takeover date, i.e., the estimated date at which variant proportion reached 50% in a state; and 3) time from emergence to dominance, the time taken for variant proportion to increase from 10% to 50%. Next, we estimated the relative proportion of each state that was immune from a combination of infection and full vaccination (for Delta) or boosting (for Omicron) prior to variant takeover. For each outcome, we fit linear regression models to estimate the relationship between population immunity and Delta or Omicron takeover. Results: We found no statistically significant association between takeover rate of Delta or Omicron and immunity (Fig. 1A, B). In contrast, we observed a later takeover date (p< 0.001) and slower time from emergence to dominance (p=0.046) for Omicron in more immune states (Fig. 1D, F). There was a similar but not statistically significant trend for Delta in delayed takeover date (Fig. 1C). Figure 1. Delta and Omicron variant takeover and population immunity in different US states. (A, B) Slope of logistic curve characterizing weekly changes in variant proportion (takeover rate) in different states with 95% confidence intervals; (C, D) estimated initial calendar date at which a variant reached 50% of sequenced SARS-CoV-2 genomes in different states (takeover date); (E, F) estimated time taken for variant proportion to increase from 10% to 50% of sequenced SARS-CoV-2 genomes in different states with 95% confidence intervals. States are identified by standard two-letter abbreviations; states in the same census geographic region are plotted with the same color. Left panel: Delta, Right panel: Omicron. Immunity is estimated by the combined proportion of the state's population with SARS-CoV-2 infection prior to detection of the new variant in the state and either fully vaccinated (for Delta) or boosted (for Omicron) two weeks prior to takeover. Pearson correlation coefficient (R) and p-value test results are shown for each plot. Conclusion: These results suggest that despite their immune-evasive properties, population-level immunity did not enhance the rates at which Delta or Omicron became dominant variants. Instead, it may have decreased rates of onward transmission among immune individuals and delayed variant takeover. Disclosures: Pierre Ankomah, MD PhD, Aditum Bio: Advisor/Consultant.