Analysis of factors influencing viral shedding time in elderly patients with mild and asymptomatic Omicron infection.

Objective To analyze the potential factors influencing the viral shedding time (duration of nucleic acid positivity) in elderly patients with mild and asymptomatic infection. Methods The clinical data of 1141 elderly (>=60 years) patients with mild and asymptomatic Omicron infection who were admitted to National Exhibition and Convention Center (Shanghai) Cabin Hospital from April 14, 2022 to May 1, 2022 were retrospectively collected, viral shedding time of patients were compared between different groups (age, gender, number of vaccination, hypertension, diabetes). Pearson analysis was adopted to analyze the relationship between age and viral shedding time. Kaplan-Meier curve and Log-rank test were used to evaluate the viral shedding time in elderly patients with different clinical characteristics. Multivariate Cox proportional-hazards regression model was adopted to analyze the factors influencing viral shedding time in elderly patients with Omicron. Results Among 1441 patients, 791(54.9%) males and 650(45.1%) females. There were 513(35.6%) patients receiving 0 dose of vaccine, 29(2.0%) patients received 1 dose of vaccine, 405(28.1%) patients received 2 doses of vaccine, 494(34.3%) patients received 3 doses of vaccine. Compared with patients aged 60 to 70 years, patients aged 70 to 80 years had longer viral shedding time (P<0.001). The viral shedding time in patients with hypertension and diabetes was longer than that in patients without hypertension and diabetes (P<0.05). In terms of vaccination, the viral shedding time of patients receiving 2 or 3 doses of vaccine was significantly shorter than that of patients receiving 1 dose of vaccine or none (P<0.05). There was a positive correlation between patient age and viral shedding time, with an R2=0.029 (P<0.001). Kaplan-Meier curve showed that there existed significant difference in viral shedding time between the patients with different vaccination doses (P<0.001), and patients with age >=70, hypertension and diabetes were all associated with prolonged viral shedding time (P<0.05). Cox regression analysis showed that the age >=70 years was a risk factor for prolonged viral shedding time, and 2 or 3 doses of vaccine was a protective factor for prolonged viral shedding time (P<0.05). Conclusions Among the elderly population, the viral shedding time would gradually increase with age. Patients who received >=2 doses of vaccine would have reduced viral shedding time compared with those who received <2 doses of vaccine.Copyright © 2022 Authors. All rights reserved.

Analysis of factors influencing viral shedding time in elderly patients with mild and asymptomatic Omicron infection

Objective To analyze the potential factors influencing the viral shedding time (duration of nucleic acid positivity) in elderly patients with mild and asymptomatic infection. Methods The clinical data of 1141 elderly (>=60 years) patients with mild and asymptomatic Omicron infection who were admitted to National Exhibition and Convention Center (Shanghai) Cabin Hospital from April 14, 2022 to May 1, 2022 were retrospectively collected, viral shedding time of patients were compared between different groups (age, gender, number of vaccination, hypertension, diabetes). Pearson analysis was adopted to analyze the relationship between age and viral shedding time. Kaplan-Meier curve and Log-rank test were used to evaluate the viral shedding time in elderly patients with different clinical characteristics. Multivariate Cox proportional-hazards regression model was adopted to analyze the factors influencing viral shedding time in elderly patients with Omicron. Results Among 1441 patients, 791(54.9%) males and 650(45.1%) females. There were 513(35.6%) patients receiving 0 dose of vaccine, 29(2.0%) patients received 1 dose of vaccine, 405(28.1%) patients received 2 doses of vaccine, 494(34.3%) patients received 3 doses of vaccine. Compared with patients aged 60 to 70 years, patients aged 70 to 80 years had longer viral shedding time (P<0.001). The viral shedding time in patients with hypertension and diabetes was longer than that in patients without hypertension and diabetes (P<0.05). In terms of vaccination, the viral shedding time of patients receiving 2 or 3 doses of vaccine was significantly shorter than that of patients receiving 1 dose of vaccine or none (P<0.05). There was a positive correlation between patient age and viral shedding time, with an R2=0.029 (P<0.001). Kaplan-Meier curve showed that there existed significant difference in viral shedding time between the patients with different vaccination doses (P<0.001), and patients with age >=70, hypertension and diabetes were all associated with prolonged viral shedding time (P<0.05). Cox regression analysis showed that the age >=70 years was a risk factor for prolonged viral shedding time, and 2 or 3 doses of vaccine was a protective factor for prolonged viral shedding time (P<0.05). Conclusions Among the elderly population, the viral shedding time would gradually increase with age. Patients who received >=2 doses of vaccine would have reduced viral shedding time compared with those who received <2 doses of vaccine. Copyright © 2022 Authors. All rights reserved.

High-Resolution Spatio-Temporal Model for County-Level COVID-19 Activity in the U.S

We present an interpretable high-resolution spatio-temporal model to estimate COVID-19 deaths together with confirmed cases 1 week ahead of the current time, at the county level and weekly aggregated, in the United States. A notable feature of our spatio-temporal model is that it considers the (1) temporal auto- and pairwise correlation of the two local time series (confirmed cases and deaths from the COVID-19), (2) correlation between locations (propagation between counties), and (3) covariates such as local within-community mobility and social demographic factors. The within-community mobility and demographic factors, such as total population and the proportion of the elderly, are included as important predictors since they are hypothesized to be important in determining the dynamics of COVID-19. To reduce the model's high dimensionality, we impose sparsity structures as constraints and emphasize the impact of the top 10 metropolitan areas in the nation, which we refer to (and treat within our models) as hubs in spreading the disease. Our retrospective out-of-sample county-level predictions were able to forecast the subsequently observed COVID-19 activity accurately. The proposed multivariate predictive models were designed to be highly interpretable, with clear identification and quantification of the most important factors that determine the dynamics of COVID-19. Ongoing work involves incorporating more covariates, such as education and income, to improve prediction accuracy and model interpretability.

Reactive force field-based molecular dynamics simulation of the interaction between plasma reactive oxygen species and the receptor-binding domain of the spike protein in the capsid protein of SARS-CoV-2

Under the pressures of the current global pandemic, researchers have been working hard to find a reliable way to suppress infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and prevent the spread of COVID-19. Studies have shown that the recognition and binding of human angiotensin-converting enzyme 2 by the receptor-binding domain (RBD) of the spike protein on the surface of SARS-CoV-2 is a crucial step in viral invasion of human receptor cells, and blocking this process could inhibit the virus from invading normal human cells. Plasma treatment can disrupt the structure of the RBD and effectively block the binding process. However, the mechanism by which plasma blocks recognition and binding is not clear. In this study, the reaction between reactive oxygen species (ROS) in plasma and a molecular model of the RBD was simulated using a reactive molecular dynamics method. The results showed that the destruction of the RBD by ROS was triggered by hydrogen ion reactions: O and OH ed H atoms from the RBD, while the H atoms of H2O2 and HO2 were ed by the RBD. This hydrogen ion resulted in the breakage of C-H, N-H, O-H and C=O bonds and the formation of C=C and C=N bonds. The addition reaction of OH increased the number of O-H bonds and caused the formation of C-O, N-O and O-H bonds. The dissociation of N-H bonds led to the destruction of the original peptide bond structure and amino acid residues, changed the type of amino acid residues and caused the conversion of N-C and N=C and C=O and C-O. The simulation partially elucidated the microscopic mechanism of the interaction between ROS in plasma and the capsid protein of SARS-CoV-2, providing theoretical support for the control of SARS-CoV-2 infection by plasma, a contribution to overcoming the global pandemic.

Unmasking the Actual COVID-19 Case Count

This report presents a novel approach to estimate the total number of COVID-19 cases in the United States, including undocumented infections, by combining the Centers for Disease Control and Prevention's influenza-like illness surveillance data with aggregated prescription data. We estimated that the cumulative number of COVID-19 cases in the United States by 4 April 2020 was > 2.5 million.