ABSTRACT
It is of interest to pinpoint SARS-CoV-2 sequence features defining vaccine resistance. In the ENSEMBLE randomized, placebo-controlled phase 3 trial, estimated single-dose Ad26.COV2.S vaccine efficacy (VE) was 56% against moderate to severe–critical COVID-19. SARS-CoV-2 Spike sequences were measured from 484 vaccine and 1,067 placebo recipients who acquired COVID-19 during the trial. In Latin America, where Spike diversity was greatest, VE was significantly lower against Lambda than against Reference and against all non-Lambda variants [family-wise error rate (FWER) p < 0.05]. VE also differed by residue match vs. mismatch to the vaccine-strain residue at 16 amino acid positions (4 FWER p < 0.05; 12 q-value ≤ 0.20). VE significantly decreased with physicochemical-weighted Hamming distance to the vaccine-strain sequence for Spike, receptor-binding domain, N-terminal domain, and S1 (FWER p < 0.001); differed (FWER ≤ 0.05) by distance to the vaccine strain measured by 9 different antibody-epitope escape scores and by 4 NTD neutralization-impacting features; and decreased (p = 0.011) with neutralization resistance level to vaccine recipient sera. VE against severe–critical COVID-19 was stable across most sequence features but lower against viruses with greatest distances. These results help map antigenic specificity of in vivo vaccine protection.
Subject(s)
COVID-19 , Encephalomyelitis, Acute DisseminatedABSTRACT
Summary SARS-CoV-2 continues to evolve and the vaccine efficacy against variants is challenging to estimate. It is now common in phase III vaccine trials to provide vaccine to those randomized to placebo once efficacy has been demonstrated, precluding a direct assessment of placebo controlled vaccine efficacy after placebo vaccination. In this work we extend methods developed for estimating vaccine efficacy post placebo vaccination to allow variant specific time varying vaccine efficacy, where time is measured since vaccination. The key idea is to infer counterfactual strain specific placebo case counts by using surveillance data that provide the proportions of the different strains. This blending of clinical trial and observational data allows estimation of strain-specific time varying vaccine efficacy, or sieve effects, including for strains that emergent after placebo vaccination. The key requirements are that surveillance strain distribution accurately reflect the strain distribution for a placebo group, throughout follow-up after placebo group vaccination and that at least one strain is present before and after placebo vaccination. For illustration, we develop a Poisson approach for an idealized design under a rare disease assumption and then use a proportional hazards modeling to better reflect the complexities of field trials with staggered entry, crossover, and smoothly varying strain specific vaccine efficacy We evaluate these by theoretical work and simulations, and demonstrate that useful estimation of the efficacy profile is possible for strains that emerge after vaccination of the placebo group. An important principle is to incorporate sensitivity analyses to guard against mis-specfication of the strain distribution. We also provide an approach for use when genotyping of the infecting strains of the trial participants has not been done.
ABSTRACT
ImportanceSARS-CoV-2 viral trajectory has not been well-characterized in documented incident infections. These data will inform SARS-CoV-2 natural history, transmission dynamics, prevention practices, and therapeutic development. ObjectiveTo prospectively characterize early SARS-CoV-2 viral shedding in persons with incident infection. DesignProspective cohort study. SettingSecondary data analysis from a multicenter study in the U.S. ParticipantsThe samples derived from a randomized controlled trial of 829 community-based asymptomatic participants recently exposed (<96 hours) to persons with SARS-CoV-2. Participants collected daily mid-turbinate swabs for SARS-CoV-2 detection by polymerase-chain-reaction and symptom diaries for 14-days. Persons with negative swab for SARS-CoV-2 at baseline who developed infection during the study were included in the analysis. ExposureLaboratory-confirmed SARS-CoV-2 infection. Main outcomes and measuresThe observed SARS-CoV-2 viral shedding characteristics were summarized and shedding trajectories were examined using a piece-wise linear mixed-effects modeling. Whole viral genome sequencing was performed on samples with cycle threshold (Ct)<34. ResultsNinety-seven persons (57% women, median age 37-years) developed incident infections during 14-days of follow-up. Two-hundred fifteen sequenced samples were assigned to 15 lineages that belonged to the G614 variant. Forty-two (43%), 18(19%), and 31(32%) participants had viral shedding for 1 day, 2-6 days, and [≥]7 days, with median peak viral load Ct of 38.5, 36.7, and 18.3, respectively. Six (6%) participants had 1-6 days of observed viral shedding with censored duration. The peak average viral load was observed on day 3 of viral shedding. The average Ct value was lower, indicating higher viral load, in persons reporting COVID-19 symptoms than asymptomatic. Using the statistical model, the median time from shedding onset to peak viral load was 1.4 days followed by a median of 9.7 days before clearance. Conclusions and RelevanceIncident SARS-CoV-2 G614 infection resulted in a rapid viral load peak followed by slower decay and positive correlation between peak viral load and shedding duration; duration of shedding was heterogeneous. This longitudinal evaluation of the SARS-CoV-2 G614 variant with frequent molecular testing may serve as a reference for comparing emergent viral lineages to inform clinical trial designs and public health strategies to contain the spread of the virus. KEY POINTSO_ST_ABSQuestionC_ST_ABSWhat are the early SARS-CoV-2 G614 viral shedding characteristics in persons with incident infection? FindingsIn this prospective cohort of 97 community-based participants who collected daily mid-turbinate swabs for SARS-CoV-2 detection after recent exposure to SARS-CoV-2, viral trajectory was characterized by a rapid peak followed by slower decay. Peak viral load correlated positively with symptoms. The duration of shedding was heterogeneous. MeaningA detailed description of the SARS-CoV-2 G614 viral shedding trajectory serves as baseline for comparison to new viral variants of concern and inform models for the planning of clinical trials and transmission dynamics to end this pandemic.