Antigenic cartography using hamster sera identifies SARS-CoV-2 JN.1 evasion seen in human XBB.1.5 booster sera (preprint)

Antigenic assessments of SARS-CoV-2 variants inform decisions to update COVID-19 vaccines. Primary infection sera are often used for assessments, but such sera are rare due to population immunity from SARS-CoV-2 infections and COVID-19 vaccinations. Here, we show that neutralization titers and breadth of matched human and hamster pre-Omicron variant primary infection sera correlate well and generate similar antigenic maps. The hamster antigenic map shows modest antigenic drift among XBB sub-lineage variants, with JN.1 and BA.4/BA.5 variants within the XBB cluster, but with five to six-fold antigenic differences between these variants and XBB.1.5. Compared to sera following only ancestral or bivalent COVID-19 vaccinations, or with post-vaccination infections, XBB.1.5 booster sera had the broadest neutralization against XBB sub-lineage variants, although a five-fold titer difference was still observed between JN.1 and XBB.1.5 variants. These findings suggest that antibody coverage of antigenically divergent JN.1 could be improved with a matched vaccine antigen.

Comparative Analysis of SARS-CoV-2 Antigenicity across Assays and in Human and Animal Model Sera (preprint)

The antigenic evolution of SARS-CoV-2 requires ongoing monitoring to judge the immune escape of newly arising variants. A surveillance system necessitates an understanding of differences in neutralization titers measured in different assays and using human and animal sera. We compared 18 datasets generated using human, hamster, and mouse sera, and six different neutralization assays. Titer magnitude was lowest in human, intermediate in hamster, and highest in mouse sera. Fold change, immunodominance patterns and antigenic maps were similar among sera. Most assays yielded similar results, except for differences in fold change in cytopathic effect assays. Not enough data was available for conclusively judging mouse sera, but hamster sera were a consistent surrogate for human first-infection sera.

Post-vaccination Omicron infections induce broader immunity across antigenic space than prototype mRNA COVID-19 booster vaccination or primary infection (preprint)

The rapid emergence of new SARS-CoV-2 variants challenges vaccination strategies. Here, we measured antigenic diversity among variants and interpreted neutralizing antibody responses following single and multiple exposures in longitudinal infection and vaccine cohorts. Antigenic cartography using primary infection antisera showed that BA.2, BA.4/BA.5, and BA.2.12.1 are distinct from BA.1 and closer to the Beta cluster. Three doses of an mRNA COVID-19 vaccine increased breadth to BA.1 more than to BA.4/BA.5 or BA.2.12.1. Omicron BA.1 post-vaccination infection elicited antibody landscapes characterized by broader immunity across antigenic space than three doses alone, although with less breadth than expected to BA.2.12.1 and BA.4/BA.5. Those with Omicron BA.1 infection after two or three vaccinations had similar neutralizing titer magnitude and antigenic breadth. Accounting for antigenic differences among variants of concern when interpreting neutralizing antibody titers aids understanding of complex patterns in humoral immunity and informs selection of future COVID-19 vaccine strains.

Quantifying Asymptomatic Infection and Transmission of COVID-19 in New York City using Observed Cases, Serology and Testing Capacity (preprint)

The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13% to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with pre-symptomatic ones. If asymptomatic infections transmit at similar rates than symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, pre-symptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection sub-populations have reproductive numbers lower than 3. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of SARS-Cov-2 should be reconsidered. Significance StatementAs health officials face another wave of COVID-19, they require estimates of the proportion of infected cases that develop symptoms, and the extent to which symptomatic and asymptomatic cases contribute to community transmission. Recent asymptomatic testing guidelines are ambiguous. Using an epidemiological model that includes testing capacity, we show that most infections are asymptomatic but contribute substantially to community transmission in the aggregate. Their individual transmissibility remains uncertain. If they transmit as well as symptomatic infections, the epidemic may spread at faster rates than current models often assume. If they do not, then each symptomatic case generates on average a higher number of secondary infections than typically assumed. Regardless, controlling transmission requires community-wide interventions informed by extensive, well-documented asymptomatic testing.