SARS-CoV-2 vaccine breakthrough by Omicron and Delta variants: comparative assessments with New York State genomic surveillance data (preprint)

Background: Recently emerged variants of SARS-CoV-2 have shown greater potential to cause vaccine breakthrough infections. Methods: A matched cohort analysis used a genomic sequence dataset linked with demographic and vaccination information from New York State (NYS). Two sets of conditional logistic regression analyses were performed, one during the emergence of Delta and another during the emergence of Omicron. For each set, cases were defined as individuals with the emerging lineage, and controls were individuals infected with any other lineage. The adjusted associations of vaccination status, vaccine type, time since vaccination, and age with lineage were assessed using odds ratios (OR) and 95% confidence intervals (CI). Results: Fully vaccinated status (OR: 3, 95% CI: 2.0 - 4.9) and Boosted status (OR 6.7, 95% CI: 3.4 - 13.0) were significantly associated with having the Omicron lineage during the Omicron emergence period. Risk of Omicron infection relative to Delta generally decreased with increasing age (OR: 0.964, 95% CI 0.950 - 0.978). The Delta emergence analysis had low statistical power for the observed effect size. Conclusions: Vaccines offered less protection against Omicron, thereby increasing the number of potential hosts for the emerging variant.

Delta-Omicron recombinant SARS-CoV-2 in a transplant patient treated with Sotrovimab (preprint)

We identified a Delta-Omicron SARS-CoV-2 recombinant in an unvaccinated, immunosuppressed kidney transplant recipient who had positive COVID-19 tests in December 2021 and February 2022 and was initially treated with Sotrovimab. Viral sequencing in February 2022 revealed a 5' Delta AY.45 portion and a 3' Omicron BA.1 portion with a recombination breakpoint in the spike N-terminal domain, adjacent to the Sotrovimab quaternary binding site. The recombinant virus induced cytopathic effects with characteristics of both Delta (large cells) and Omicron (cell rounding/detachment). Monitoring of immunosuppressed COVID-19 patients treated with antiviral monoclonal antibodies is crucial to detect potential selection of recombinant variants.

Spatiotemporal analyses illuminate the competitive advantage of a SARS-CoV-2 variant of concern over a variant of interest (preprint)

The emergence of novel SARS-CoV-2 variants in late 2020 and early 2021 raised alarm worldwide and prompted reassessment of the management, surveillance, and projected future of COVID-19. Mutations that confer competitive advantages by increasing transmissibility or immune evasion have been associated with the localized dominance of single variants. Thus, elucidating the evolutionary and epidemiological dynamics among novel variants is essential for understanding the trajectory of the COVID-19 pandemic. Here we show the interplay between B.1.1.7 (Alpha) and B.1.526 (Iota) in New York (NY) from December 2020 to April 2021 through phylogeographic analyses, space-time scan statistics, and cartographic visualization. Our results indicate that B.1.526 likely evolved in the Bronx in late 2020, providing opportunity for an initial foothold in the heavily interconnected New York City (NYC) region, as evidenced by numerous exportations to surrounding locations. In contrast, B.1.1.7 became dominant in regions of upstate NY where B.1.526 had limited presence, suggesting that B.1.1.7 was able to spread more efficiently in the absence of B.1.526. Clusters discovered from the spatial-time scan analysis supported the role of competition between B.1.526 and B.1.1.7 in NYC in March 2021 and the outsized presence of B.1.1.7 in upstate NY in April 2021. Although B.1.526 likely delayed the rise of B.1.1.7 in NYC, B.1.1.7 became the dominant variant in the Metro region by the end of the study period. These results reveal the advantages endemicity may grant to a variant (founder effect), despite the higher fitness of an introduced lineage. Our research highlights the dynamics of inter-variant competition at a time when B.1.617.2 (Delta) is overtaking B.1.1.7 as the dominant lineage worldwide. We believe our combined spatiotemporal methodologies can disentangle the complexities of shifting SARS-CoV-2 variant landscapes at a time when the evolution of variants with additional fitness advantages is impending.

Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 lineages (preprint)

Emerging SARS-CoV-2 variants have shaped the second year of the COVID-19 pandemic and the public health discourse around effective control measures. Evaluating the public health threat posed by a new variant is essential for appropriately adapting response efforts when community transmission is detected. However, this assessment requires that a true comparison can be made between the new variant and its predecessors because factors other than the virus genotype may influence spread and transmission. In this study, we develop a framework that integrates genomic surveillance data to estimate the relative effective reproduction number (Rt) of co-circulating lineages. We use Connecticut, a state in the northeastern United States in which the SARS-CoV-2 variants B.1.1.7 and B.1.526 co-circulated in early 2021, as a case study for implementing this framework. We find that the Rt of B.1.1.7 was 6-10% larger than that of B.1.526 in Connecticut in the midst of a COVID-19 vaccination campaign. To assess the generalizability of this framework, we apply it to genomic surveillance data from New York City and observe the same trend. Finally, we use discrete phylogeography to demonstrate that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of B.1.1.7 were larger than those resulting from B.1.526 introductions. Our framework, which uses open-source methods requiring minimal computational resources, may be used to monitor near real-time variant dynamics in a myriad of settings.

A statewide analysis of SARS-CoV-2 transmission in New York (preprint)

New York State, in particular the New York City metropolitan area, was the early epicenter of the SARS-CoV-2 pandemic in the United States. Similar to initial pandemic dynamics in many metropolitan areas, multiple introductions from various locations appear to have contributed to the swell of positive cases. However, representation and analysis of samples from New York regions outside the greater New York City area were lacking, as were SARS-CoV-2 genomes from the earliest cases associated with the Westchester County outbreak, which represents the first outbreak recorded in New York State. The Wadsworth Center, the public health laboratory of New York State, sought to characterize the transmission dynamics of SARS-CoV-2 across the entire state of New York from March to September with the addition of over 600 genomes from under-sampled and previously unsampled New York counties and to more fully understand the breadth of the initial outbreak in Westchester County. Additional sequencing confirmed the dominance of B.1 and descendant lineages (collectively referred to as B.1.X) in New York State. Community structure, phylogenetic, and phylogeographic analyses suggested that the Westchester outbreak was associated with continued transmission of the virus throughout the state, even after travel restrictions and the on-pause measures of March, contributing to a substantial proportion of the B.1.X transmission clusters as of September 30th, 2020.

Early introductions and community transmission of SARS-CoV-2 variant B.1.1.7 in the United States (preprint)

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.