Low humoral and cellular immune responses early after breakthrough infection may contribute to severe COVID-19.

Background: Little is known about the immune determinants for severe coronavirus disease 2019 (COVID-19) in individuals vaccinated against severe acute respiratory syndrome coronavirus 2. We therefore attempted to identify differences in humoral and cellular immune responses between patients with non-severe and severe breakthrough COVID-19. Methods: We prospectively enrolled hospitalized patients with breakthrough COVID-19 (severe and non-severe groups) and uninfected individuals who were vaccinated at a similar time (control group). Severe cases were defined as those who required oxygen therapy while hospitalized. Enzyme-linked immunosorbent assays and flow cytometry were used to evaluate humoral and cellular immune responses, respectively. Results: Anti-S1 IgG titers were significantly lower in the severe group than in the non-severe group within 1 week of symptom onset and higher in the non-severe group than in the control group. Compared with the control group, the cellular immune response tended to be diminished in breakthrough cases, particularly in the severe group. In multivariate analysis, advanced age and low anti-S1 IgG titer were associated with severe breakthrough COVID-19. Conclusions: Severe breakthrough COVID-19 might be attributed by low humoral and cellular immune responses early after infection. In the vaccinated population, delayed humoral and cellular immune responses may contribute to severe breakthrough COVID-19.

"Why rush to get vaccinated earlier?": Regulatory focus and COVID-19 vaccination.

OBJECTIVES: The health psychology literature has paid little attention to individuals' intention to vaccinate earlier. Building on regulatory focus theory, which proposes two distinct self-regulatory foci: promotion and prevention focus (Higgins, 1997), the present study tests whether, how, and why regulatory focus contributes to the intention to vaccinate earlier (IVE) and whether IVE predicts actual behavior. METHOD: This study used a longitudinal design with data collected at two-time points (3.5 months apart). At Time 1, 487 unvaccinated participants completed a survey assessing regulatory focus, ideal and ought reason for IVE (i.e., hopes/wishes and felt obligation/pressure regarding earlier vaccination, respectively), and IVE through leftover vaccines-vaccines that become available due to last-minute vaccination appointment cancellations. At Time 2, 364 participants reported on the attempts they made to get a leftover vaccine, whether they were vaccinated, and if so, the vaccination type (general vs. leftover vaccine), along with the date of vaccination. RESULTS: A promotion focus was associated with IVE via ideal reason (ß = .141, 95% confidence interval, CI [.085, .198]), whereas a prevention focus was associated with IVE via ought reason (ß = .031, 95% CI [.012, .057]). Furthermore, both the promotion focus (ß = .029, 95% CI [.016, .050]) and prevention focus paths (ß = .006, 95% CI [.001, .015]) extended to vaccinating via leftover vaccines. CONCLUSIONS: The present study illuminates how regulatory focus, especially promotion focus, can be a predictor of earlier vaccination. Our findings suggest that promotion-focused messages highlighting desirable outcomes of vaccination may help encourage earlier vaccination. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A COVID-19 mortality prediction model for Korean patients using nationwide Korean disease control and prevention agency database.

The experience of the early nationwide COVID-19 pandemic in South Korea led to an early shortage of medical resources. For efficient resource allocation, accurate prediction of the prognosis or mortality of confirmed patients is essential. Therefore, the aim of this study was to develop an accurate model for predicting COVID-19 mortality using epidemiolocal and clinical variables and for identifying a high-risk group of confirmed patients. Clinical and epidemiolocal variables of 4049 patients with confirmed COVID-19 between January 20, 2020 and April 30, 2020 collected by the Korean Disease Control and Prevention Agency were used. Among the 4049 total confirmed patients, 223 patients died, while 3826 patients were released from isolation. Patients who had the following risk factors showed significantly higher risk scores: age over 60 years, male sex, difficulty breathing, diabetes, cancer, dementia, change of consciousness, and hospitalization in the intensive care unit. High accuracy was shown for both the development set (n = 2467) and the validation set (n = 1582), with AUCs of 0.96 and 0.97, respectively. The prediction model developed in this study based on clinical features and epidemiological factors could be used for screening high-risk groups of patients and for evidence-based allocation of medical resources.