RESUMO
As of 4/20/2022, approximately 23% of the eligible US population was unvaccinated. We studied COVID-19 infections during the Omicron (B.1.1.529) wave in unvaccinated US adults, stratified by pre-Omicron antibody levels. Anti-spike serologic testing was performed prior to the Omicron wave in the United States (9/23/21-11/5/21) and participants were surveilled to determine incident COVID-19. Only 12% of those who entered the wave with antibodies reported a test-confirmed COVID-19 infection, compared to 35% of those without antibodies prior to the Omicron wave. Effectiveness of these anti-RBD antibodies in this unvaccinated population was 67%. Among people with antibodies, titer did not appear to be associated with risk of test-confirmed Omicron infection.
RESUMO
Vaccine-induced SARS-CoV-2 antibody responses are attenuated in solid organ transplant recipients (SOTRs) and breakthrough infections are more common. Additional SARS-CoV-2 vaccine doses increase anti-spike IgG in some SOTRs, but it is uncertain whether neutralization of variants of concern (VOCs) is enhanced. We tested 47 SOTRs for clinical and research anti-spike IgG, pseudoneutralization (ACE2 blocking), and live-virus neutralization (nAb) against VOCs before and after a third SARS-CoV-2 vaccine dose (70% mRNA, 30% Ad26.COV2.S) with comparison to 15 healthy controls after two mRNA vaccine doses. We used correlation analysis to compare anti-spike IgG assays and focused on thresholds associated with neutralizing activity. A third SARS-CoV-2 vaccine dose increased median anti-spike (1.6-fold) and receptor-binding domain (1.5-fold) IgG, as well as pseudoneutralization against VOCs (2.5-fold versus Delta). However, IgG and neutralization activity were significantly lower than healthy controls (p<0.001); 32% of SOTRs had zero detectable nAb against Delta after third vaccination. Correlation with nAb was seen at anti-spike IgG >4 AU on the clinical assay and >10^4 AU on the research assay. These findings highlight benefits of a third vaccine dose for some SOTRs and the need for alternative strategies to improve protection in a significant subset of this population.
RESUMO
BackgroundGlobal demand for a COVID-19 vaccine will exceed the initial limited supply. Identifying individuals at highest risk of COVID-19 death may help allocation prioritization efforts. Personalized risk prediction that uses a broad range of comorbidities requires a cohort size larger than that reported in prior studies. MethodsMedicare claims data was used to identify patients age 65 years or older with diagnosis of COVID-19 between April 1, 2020 and August 31, 2020. Demographic characteristics, chronic medical conditions, and other patient risk factors that existed before the advent of COVID-19 were identified. A random forest model was used to empirically explore factors associated with COVID-19 death. The independent impact of factors identified were quantified using multivariate logistic regression with random effects. ResultsWe identified 534,023 COVID-19 patients of whom 38,066 had an inpatient death. Demographic characteristics associated with COVID-19 death included advanced age (85 years or older: aOR: 2.07; 95% CI, 1.99-2.16), male sex (aOR, 1.88; 95% CI, 1.82-1.94), and non-white race (Hispanic: aOR, 1.74; 95% CI, 1.66-1.83). Leading comorbidities associated with COVID-19 mortality included sickle cell disease (aOR, 1.73; 95% CI, 1.21-2.47), chronic kidney disease (aOR, 1.32; 95% CI, 1.29-1.36), leukemias and lymphomas (aOR, 1.22; 95% CI, 1.14-1.30), heart failure (aOR, 1.19; 95% CI, 1.16-1.22), and diabetes (aOR, 1.18; 95% CI, 1.15-1.22). ConclusionsWe created a personalized risk prediction calculator to identify candidates for early vaccine and therapeutics allocation (www.predictcovidrisk.com). These findings may be used to protect those at greatest risk of death from COVID-19.