Suicide risk is elevated among military service members who recently transitioned to civilian life. Identifying high-risk service members before this transition could facilitate provision of targeted preventive interventions. We investigated the feasibility of doing this by attempting to develop a prediction model for self-reported suicide attempts (SAs) after leaving or being released from active duty in the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS). This study included two self-report panel surveys (LS1: 2016-2018, LS2: 2018-2019) administered to respondents who previously participated while on active duty in one of three Army STARRS 2011-2014 baseline self-report surveys. We focus on respondents who left active duty >12 months before their LS survey (n = 8899). An ensemble machine learning model using predictors available prior to leaving active duty was developed in a 70% training sample and validated in a 30% test sample. The 12-month self-reported SA prevalence (SE) was 1.0% (0.1). Test sample AUC (SE) was 0.74 (0.06). The 15% of respondents with highest predicted risk included nearly two-thirds of 12-month SAs and over 80% of medically serious 12-month SAs. These results show that it is possible to identify soldiers at high post-transition self-report SA risk before the transition. Future model development is needed to examine prediction of SAs assessed by administrative data and using surveys administered closer to the time of leaving active duty.

In the ENSEMBLE randomized, placebo-controlled phase 3 trial (NCT04505722), estimated single-dose Ad26.COV2.S vaccine efficacy (VE) was 56% against moderate to severe-critical COVID-19. SARS-CoV-2 Spike sequences were determined from 484 vaccine and 1,067 placebo recipients who acquired COVID-19. In this set of prespecified analyses, we show that in Latin America, VE was significantly lower against Lambda vs. Reference and against Lambda vs. non-Lambda [family-wise error rate (FWER) p < 0.05]. VE differed by residue match vs. mismatch to the vaccine-insert at 16 amino acid positions (4 FWER p < 0.05; 12 q-value ≤ 0.20); 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 antibody-epitope escape scores and 4 NTD neutralization-impacting features; and decreased (p = 0.011) with neutralization resistance level to vaccinee sera. VE against severe-critical COVID-19 was stable across most sequence features but lower against the most distant viruses.

Questions remain regarding the effect of baseline host and exposure factors on vaccine efficacy (VE) across pathogens and vaccine platforms. We report placebo-controlled data from four Phase 3 COVID-19 trials during the early period of the pandemic. This was a cross-protocol analysis of four randomized, placebo-controlled efficacy trials (Moderna/mRNA1273, AstraZeneca/AZD1222, Janssen/Ad26.COV2.S, and Novavax/NVX-CoV2373) using a harmonized design. Trials were conducted in the United States and international sites in adults ≥ 18 years of age. VE was assessed for symptomatic and severe COVID-19. We analyzed 114,480 participants from both placebo and vaccine arms, enrolled July 2020 to February 2021, with follow up through July 2021. VE against symptomatic COVID-19 showed little heterogeneity across baseline socio-demographic, clinical or exposure characteristics, in either univariate or multivariate analysis, regardless of vaccine platform. Similarly, VE against severe COVID-19 in the single trial (Janssen) with sufficient endpoints for analysis showed little evidence of heterogeneity. COVID-19 VE is not influenced by baseline host or exposure characteristics across efficacy trials of different vaccine platforms and countries when well matched to circulating virus strains. This supports use of these vaccines, regardless of platform type, as effective tools in the near term for reducing symptomatic and severe COVID-19, particularly for older individuals and those with common co-morbidities during major variant shifts. Clinical trial registration numbers: NCT04470427, NCT04516746, NCT04505722, and NCT04611802.

Measuring immune correlates of disease acquisition and protection in the context of a clinical trial is a prerequisite for improved vaccine design. We analysed binding and neutralizing antibody measurements 4 weeks post vaccination as correlates of risk of moderate to severe-critical COVID-19 through 83 d post vaccination in the phase 3, double-blind placebo-controlled phase of ENSEMBLE, an international randomized efficacy trial of a single dose of Ad26.COV2.S. We also evaluated correlates of protection in the trial cohort. Of the three antibody immune markers we measured, we found most support for 50% inhibitory dilution (ID50) neutralizing antibody titre as a correlate of risk and of protection. The outcome hazard ratio was 0.49 (95% confidence interval 0.29, 0.81; P = 0.006) per 10-fold increase in ID50; vaccine efficacy was 60% (43%, 72%) at non-quantifiable ID50 (<2.7 IU50 ml-1) and increased to 89% (78%, 96%) at ID50 = 96.3 IU50 ml-1. Comparison of the vaccine efficacy by ID50 titre curves for ENSEMBLE-US, the COVE trial of the mRNA-1273 vaccine and the COV002-UK trial of the AZD1222 vaccine supported the ID50 titre as a correlate of protection across trials and vaccine types.