Omicron COVID-19 Immune Correlates Analysis of a Third Dose of mRNA-1273 in the COVE Trial (preprint)

In the coronavirus efficacy (COVE) phase 3 efficacy trial of the mRNA-1273 vaccine, IgG binding antibody (bAb) concentration against Spike (BA.1 strain) and neutralizing antibody (nAb) titer against Spike (BA.1 strain) pseudovirus were assessed as correlates of risk of Omicron COVID-19 and as correlates of relative boost efficacy in per-protocol recipients of a third (booster) dose. Markers were measured on the day of the boost (BD1) and 28 days later (BD29). For SARS-CoV-2 naive individuals, BD29 Spike IgG-BA.1 strain bAbs and BD29 BA.1-strain nAbs inversely correlated with Omicron COVID-19: hazard ratio (HR) per 10-fold marker increase [95% confidence interval (CI)] = 0.16 (0.03, 0.79); P=0.024 and 0.31 (0.10, 0.96); P = 0.042, respectively. These markers also inversely correlated with Omicron COVID-19 in non-naive individuals: HR = 0.15 (0.04, 0.63); P = 0.009 and 0.28 (0.07, 1.08); P = 0.06, trend. Fold-rise in markers from BD1 to BD29 had similarly strong inverse correlations. For SARS-CoV-2 naive individuals, overall booster relative (three-dose vs two-dose) efficacy was 46% (95% CI: 20%, 64%) and correlated with BA.1 strain nAb titer at exposure. At 56, 251, and 891 arbitrary units (AU)/ml (10th, 50th, and 90th percentile), the booster relative efficacies were -8% (95% CI: -126%, 48%), 50% (25%, 67%), and 74% (49%, 87%), respectively. Similar relationships were observed for Spike IgG-BA.1 strain bAbs and for the markers measured at BD29. The performance of bAb and nAb markers as correlates of protection against Omicron COVID-19 supports their continued use as surrogate endpoints for mRNA vaccination against Omicron COVID-19.

Immune Correlates of Protection by mRNA-1273 Immunization against SARS-CoV-2 Infection in Nonhuman Primates (preprint)

Immune correlates of protection can be used as surrogate endpoints for vaccine efficacy. The nonhuman primate (NHP) model of SARS-CoV-2 infection replicates key features of human infection and may be used to define immune correlates of protection following vaccination. Here, NHP received either no vaccine or doses ranging from 0.3-100 micrograms of mRNA-1273, a mRNA vaccine encoding the prefusion-stabilized SARS-CoV-2 spike (S-2P) protein encapsulated in a lipid nanoparticle. mRNA-1273 vaccination elicited robust circulating and mucosal antibody responses in a dose-dependent manner. Viral replication was significantly reduced in bronchoalveolar lavages and nasal swabs following SARS-CoV-2 challenge in vaccinated animals and was most strongly correlated with levels of anti-S antibody binding and neutralizing activity. Consistent with antibodies being a correlate of protection, passive transfer of vaccine-induced IgG to naive hamsters was sufficient to mediate protection. Taken together, these data show that mRNA-1273 vaccine-induced humoral immune responses are a mechanistic correlate of protection against SARS-CoV-2 infection in NHP.

Assessing Vaccine Durability in Randomized Trials Following Placebo Crossover (preprint)

Randomized vaccine trials are used to assess vaccine efficacy and to characterize the durability of vaccine induced protection. If efficacy is demonstrated, the treatment of placebo volunteers becomes an issue. For COVID-19 vaccine trials, there is broad consensus that placebo volunteers should be offered a vaccine once efficacy has been established. This will likely lead to most placebo volunteers crossing over to the vaccine arm, thus complicating the assessment of long term durability. We show how to analyze durability following placebo crossover and demonstrate that the vaccine efficacy profile that would be observed in a placebo controlled trial is recoverable in a trial with placebo crossover. This result holds no matter when the crossover occurs and with no assumptions about the form of the efficacy profile. We only require that the vaccine efficacy profile applies to the newly vaccinated irrespective of the timing of vaccination. We develop different methods to estimate efficacy within the context of a proportional hazards regression model and explore via simulation the implications of placebo crossover for estimation of vaccine efficacy under different efficacy dynamics and study designs. We apply our methods to simulated COVID-19 vaccine trials with durable and waning vaccine efficacy and a total follow-up of two years.

Assessing Durability of Vaccine Effect Following Blinded Crossover in COVID-19 Vaccine Efficacy Trials (preprint)

BackgroundSeveral candidate vaccines to prevent COVID-19 disease have entered large-scale phase 3 placebo-controlled randomized clinical trials and some have demonstrated substantial short-term efficacy. Efficacious vaccines should, at some point, be offered to placebo participants, which will occur before long-term efficacy and safety are known. MethodsFollowing vaccination of the placebo group, we show that placebo-controlled vaccine efficacy can be derived by assuming the benefit of vaccination over time has the same profile for the original vaccine recipients and the placebo crossovers. This reconstruction allows estimation of both vaccine durability and potential vaccine-associated enhanced disease. ResultsPost-crossover estimates of vaccine efficacy can provide insights about durability, identify waning efficacy, and identify late enhancement of disease, but are less reliable estimates than those obtained by a standard trial where the placebo cohort is maintained. As vaccine efficacy estimates for post-crossover periods depend on prior vaccine efficacy estimates, longer pre-crossover periods with higher case counts provide better estimates of late vaccine efficacy. Further, open-label crossover may lead to riskier behavior in the immediate crossover period for the unblinded vaccine arm, confounding vaccine efficacy estimates for all post-crossover periods. ConclusionsWe advocate blinded crossover and continued follow-up of trial participants to best assess vaccine durability and potential delayed enhancement of disease. This approach allows placebo recipients timely access to the vaccine when it would no longer be proper to maintain participants on placebo, yet still allows important insights about immunological and clinical effectiveness over time.

Semi-parametric modeling of SARS-CoV-2 transmission in Orange County, California using tests, cases, deaths, and seroprevalence data (preprint)

Mechanistic modeling of SARS-CoV-2 transmission dynamics and frequently estimating model parameters using streaming surveillance data are important components of the pandemic response toolbox. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, we propose a Bayesian modeling framework that integrates multiple surveillance data streams. Our model uses both SARS-CoV-2 diagnostics test and mortality time series to estimate our model parameters, while also explicitly integrating seroprevalence data from cross-sectional studies. Importantly, our data generating model for incidence data takes into account changes in the total number of tests performed. We model transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparameterically. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March, 2020 and March, 2021 and find that 33-62% of the Orange County residents experienced SARS-CoV-2 infection by the end of February, 2021. Despite this high number of infections, our results show that the abrupt end of the winter surge in January, 2021, was due to both behavioral changes and a high level of accumulated natural immunity.