Coronary Artery Disease as an Independent Predictor of Cardiovascular Mortality in COVID-19 Patients.

Background: Coronavirus disease 2019 (COVID-19) is associated with increased risk of cardiovascular mortality. However, little is known about the combined effect of coronary artery disease (CAD) and COVID-19 on mortality. We aimed to investigate the incidence of cardiovascular and all-cause mortality in COVID-19 patients with CAD. Methods: This multicenter retrospective study identified 3,336 COVID-19 patients admitted between March and December 2020. Data points were manually reviewed in the patients' electronic health records. Multivariate logistic regression was used to assess whether CAD and its subtypes were associated with mortality. Results: This study shows that CAD was not an independent predictor of all-cause mortality (odds ratio (OR): 1.512, 95% confidence interval (CI): 0.1529 - 14.95, P = 0.723). However, there was a significant increase in cardiovascular mortality in patients with CAD compared to those without (OR: 6.89, 95% CI: 2.706 - 17.53, P < 0.001). There was no significant difference in all-cause mortality in patients with left main artery and left anterior descending artery disease (OR: 1.29, 95% CI: 0.80 - 2.08, P = 0.29). However, CAD patients with a history of interventions (e.g., coronary stenting or coronary artery bypass graft) showed increased mortality compared to those solely treated by medical management (OR: 1.93, 95% CI: 1.12 - 3.33, P = 0.017). Conclusions: CAD is associated with a higher incidence of cardiovascular mortality but not all-cause mortality in COVID-19 patients. Overall, this study will help clinicians identify characteristics of COVID-19 patients with increased risk of mortality in the setting of CAD.

Causal associations between major depressive disorder and COVID-19.

Background: We aimed to evaluate whether major depressive disorder (MDD) could aggravate the outcomes of coronavirus disease 2019 (COVID-19) or whether the genetic liability to COVID-19 could trigger MDD. Aims: We aimed to assess bidirectional causal associations between MDD and COVID-19. Methods: We performed genetic correlation and Mendelian randomisation (MR) analyses to assess potential associations between MDD and three COVID-19 outcomes. Literature-based network analysis was conducted to construct molecular pathways connecting MDD and COVID-19. Results: We found that MDD has positive genetic correlations with COVID-19 outcomes (rg: 0.10-0.15). Our MR analysis indicated that genetic liability to MDD is associated with increased risks of COVID-19 infection (odds ratio (OR)=1.05, 95% confidence interval (CI): 1.00 to 1.10, p=0.039). However, genetic liability to the three COVID-19 outcomes did not confer any causal effects on MDD. Pathway analysis identified a panel of immunity-related genes that may mediate the links between MDD and COVID-19. Conclusions: Our study suggests that MDD may increase the susceptibility to COVID-19. Our findings emphasise the need to increase social support and improve mental health intervention networks for people with mood disorders during the pandemic.

A model to predict the risk of mortality in severely ill COVID-19 patients.

BACKGROUND: To investigate and select the useful prognostic parameters to develop and validate a model to predict the mortality risk for severely and critically ill patients with the coronavirus disease 2019 (COVID-19). METHODS: We established a retrospective cohort of patients with laboratory-confirmed COVID-19 (≥18 years old) from two tertiary hospitals: the People's Hospital of Wuhan University and Leishenshan Hospital between February 16, 2020, and April 14, 2020. The diagnosis of the cases was confirmed according to the WHO interim guidance. The data of consecutive severely and critically ill patients with COVID-19 admitted to these hospitals were analyzed. A total of 566 patients from the People's Hospital of Wuhan University were included in the training cohort and 436 patients from Leishenshan Hospital were included in the validation cohort. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the variables and build the mortality risk prediction model. RESULTS: The prediction model was presented as a nomograph and developed based on identified predictors, including age, chronic lung disease, C-reactive protein (CRP), D-dimer levels, neutrophil-to-lymphocyte ratio (NLR), creatinine, and total bilirubin. In the training cohort, the model displayed good discrimination with an AUC of 0.912 [95% confidence interval (CI): 0.884-0.940] and good calibration (intercept = 0; slope = 1). In the validation cohort, the model had an AUC of 0.922 [95% confidence interval (CI): 0.891-0.953] and a good calibration (intercept = 0.056; slope = 1.161). The decision curve analysis (DCA) demonstrated that the nomogram was clinically useful. CONCLUSION: A risk score for severely and critically ill COVID-19 patients' mortality was developed and externally validated. This model can help clinicians to identify individual patients at a high mortality risk.

[Challenges of and Responses to Mental Health Problems in the Post-COVID-19 Era].

Since the first outbreak of the coronavirus disease 2019 (COVID-19), prevention and control of the pandemic remains a grim issue because of the continuous emergence of new variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, and the constant emergence of new domestic outbreaks. During the COVID-19 pandemic, mental and psychological problems have increased significantly among different populations, including patients of COVID-19 and their families, health workers, college students, adolescents, children, and even the general population. At present, the COVID-19 epidemic situation in China is rather complicated. The general population is confronted with a variety of challenges, including the threat of infection or reinfection, lower efficiency in study and work, and reduced incomes, and is hence experiencing many mental health problems related to the epidemic situation. Therefore, the relevant governmental departments and health institutions in China have attached high importance to the mental health issue in the process of implementing pandemic control measures of COVID-19. Close collaboration to implement the required epidemic prevention and control measures, improvements in the mental health services for public health emergencies in China, and commitment to the protection of the mental health and well-being of the people in the post-pandemic era have become the top priorities for now. Based on a review of the mental health problems related to COVID-19 pandemic, we suggested strategies to deal with mental health problems in the post-COVID-19 era.

Spatial Accessibility and Equity Evaluation of Medical Facilities Based on Improved 2SFCA: A Case Study in Xi'an, China.

Accurate evaluation of the accessibility of medical facilities is a prerequisite for the reasonable allocation of medical resources in a city. The accessibility of medical facilities depends not only on the distance to the supply and demand points, but also on the time spent in the process, and the supply capacity of the supply points. Taking Xi'an City of Shaanxi Province as an example, this paper comprehensively considers the facility supply capacity and introduces the selection probability function based on the two-step floating catchment area (2SFCA) method. In addition, in order to approximate the residents' acceptance of different types of hospitals for long-distance medical treatment in real situations, different levels of search radius were set for the different levels of hospitals, and ArcGIS was used to measure the accessibility and evaluate the spatial layout of medical facilities in the main urban area of Xi'an. The results show that there is a significant difference in the accessibility of medical facilities in the main urban area of Xi'an, and the accessibility tends to decrease gradually from the central city to the periphery. The inequity in the allocation of medical facilities in the main urban area of Xi'an is more obvious, with about 81.64% of people having access to 54.88% of medical resources. The accessibility evaluation model established by the improved 2SFCA method can obtain more accurate and objective evaluation results. This study can provide a reference basis for urban medical facilities' planning and rational spatial layout.

A systematic review and meta-analysis of long term physical and mental sequelae of COVID-19 pandemic: call for research priority and action.

The long-term physical and mental sequelae of COVID-19 are a growing public health concern, yet there is considerable uncertainty about their prevalence, persistence and predictors. We conducted a comprehensive, up-to-date meta-analysis of survivors' health consequences and sequelae for COVID-19. PubMed, Embase and the Cochrane Library were searched through Sep 30th, 2021. Observational studies that reported the prevalence of sequelae of COVID-19 were included. Two reviewers independently undertook the data extraction and quality assessment. Of the 36,625 records identified, a total of 151 studies were included involving 1,285,407 participants from thirty-two countries. At least one sequelae symptom occurred in 50.1% (95% CI 45.4-54.8) of COVID-19 survivors for up to 12 months after infection. The most common investigation findings included abnormalities on lung CT (56.9%, 95% CI 46.2-67.3) and abnormal pulmonary function tests (45.6%, 95% CI 36.3-55.0), followed by generalized symptoms, such as fatigue (28.7%, 95% CI 21.0-37.0), psychiatric symptoms (19.7%, 95% CI 16.1-23.6) mainly depression (18.3%, 95% CI 13.3-23.8) and PTSD (17.9%, 95% CI 11.6-25.3), and neurological symptoms (18.7%, 95% CI 16.2-21.4), such as cognitive deficits (19.7%, 95% CI 8.8-33.4) and memory impairment (17.5%, 95% CI 8.1-29.6). Subgroup analysis showed that participants with a higher risk of long-term sequelae were older, mostly male, living in a high-income country, with more severe status at acute infection. Individuals with severe infection suffered more from PTSD, sleep disturbance, cognitive deficits, concentration impairment, and gustatory dysfunction. Survivors with mild infection had high burden of anxiety and memory impairment after recovery. Our findings suggest that after recovery from acute COVID-19, half of survivors still have a high burden of either physical or mental sequelae up to at least 12 months. It is important to provide urgent and appropriate prevention and intervention management to preclude persistent or emerging long-term sequelae and to promote the physical and psychiatric wellbeing of COVID-19 survivors.

NPInter v5.0: ncRNA interaction database in a new era.

Noncoding RNAs (ncRNAs) play key regulatory roles in biological processes by interacting with other biomolecules. With the development of high-throughput sequencing and experimental technologies, extensive ncRNA interactions have been accumulated. Therefore, we updated the NPInter database to a fifth version to document these interactions. ncRNA interaction entries were doubled from 1 100 618 to 2 596 695 by manual literature mining and high-throughput data processing. We integrated global RNA-DNA interactions from iMARGI, ChAR-seq and GRID-seq, greatly expanding the number of RNA-DNA interactions (from 888 915 to 8 329 382). In addition, we collected different types of RNA interaction between SARS-CoV-2 virus and its host from recently published studies. Long noncoding RNA (lncRNA) expression specificity in different cell types from tumor single cell RNA-seq (scRNA-seq) data were also integrated to provide a cell-type level view of interactions. A new module named RBP was built to display the interactions of RNA-binding proteins with annotations of localization, binding domains and functions. In conclusion, NPInter v5.0 (http://bigdata.ibp.ac.cn/npinter5/) provides informative and valuable ncRNA interactions for biological researchers.

Mortality and Major Adverse Cardiovascular Events in Hospitalized Patients With Atrial Fibrillation With COVID-19.

COVID-19 results in increased incidence of cardiac arrhythmias, including atrial fibrillation (AF). However, little is known about the combined effect of AF and COVID-19 on patient outcomes. This study aimed to determine if AF, specifically new-onset AF (NOAF), is associated with increased risk of mortality and major adverse cardiovascular events (MACEs) in hospitalized patients with COVID-19. This multicenter retrospective analysis identified 2,732 patients with COVID-19 admitted between March and December 2020. Data points were manually reviewed in the patients' electronic health records. Multivariate logistic regression was used to assess if AF was associated with death or MACE. Patients with AF (6.4%) had an increased risk of mortality (risk ratio 2.249, 95% confidence interval [CI] 1.766 to 2.864, p <0.001) and MACE (risk ratio 1.753, 95% CI 1.473 to 2.085, p <0.001) compared with those with sinus rhythm. Patients with NOAF had an increased risk of mortality compared with those with existing AF (odds ratio 19.30, 95% CI 5.39 to 69.30, p <0.001); the risk of MACE was comparable between NOAF and patients with existing AF (p = 1). AF during hospitalization with COVID-19 is associated with a higher risk of mortality and MACE. NOAF in patients with COVID-19 is associated with a higher risk of mortality but a similar risk of MACE compared with patients with existing AF.

How will actual wearing time influence the protective effect of surgical masks?

The protection effects of wearing masks against viruses and bacteria have been verified many times over previous pandemics and infectious diseases. However, the supply of the surgical masks can barely meet the surging demand at the early stage (first 12 months) of the outbreak of a pandemic. Thus, it is essential to use surgical masks wisely in such urgent times. In this work, we selected two types of surgical masks and systematically explored how actual wearing time influences the protective performances of the masks. Each type of surgical masks was worn for 4, 10, 24, 32 and 48 h, respectively, and the results show that with the increase of actual wearing time, both particulate filtration efficiency (PFE) and bacterial filtration efficiency (BFE) of the masks decline. After wearing for 32 h, the PFEs of both types of masks were still far above the corresponding standard (>= 30%, according to YY0469-2011). After wearing for 10 h, the BFEs of both masks were over 95% (which is regarded as the safe value), whereas after 24 and 32 h of wearing, the BFE of one type of mask decreased obviously to 91.6% and 80.0%, respectively. Based on these results, it is rational to conclude that the wearing time of surgical masks should be no more than 10 h.

On-Site Quantification and Infection Risk Assessment of Airborne SARS-CoV-2 Virus Via a Nanoplasmonic Bioaerosol Sensing System in Healthcare Settings.

On-site quantification and early-stage infection risk assessment of airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high spatiotemporal resolution is a promising approach for mitigating the spread of coronavirus disease 2019 (COVID-19) pandemic and informing life-saving decisions. Here, a condensation (hygroscopic growth)-assisted bioaerosol collection and plasmonic photothermal sensing (CAPS) system for on-site quantitative risk analysis of SARS-CoV-2 virus-laden aerosols is presented. The CAPS system provided rapid thermoplasmonic biosensing results after an aerosol-to-hydrosol sampling process in COVID-19-related environments including a hospital and a nursing home. The detection limit reached 0.25 copies/µL in the complex aerosol background without further purification. More importantly, the CAPS system enabled direct measurement of the SARS-CoV-2 virus exposures with high spatiotemporal resolution. Measurement and feedback of the results to healthcare workers and patients via a QR-code are completed within two hours. Based on a dose-responseµ model, it is used the plasmonic biosensing signal to calculate probabilities of SARS-CoV-2 infection risk and estimate maximum exposure durations to an acceptable risk threshold in different environmental settings.

Bowel ischaemia in COVID-19 infection: a scoping review protocol.

INTRODUCTION: COVID-19 disease was declared as a pandemic by WHO since March 2020 and can have a myriad of clinical presentations affecting various organ systems. Patients with COVID-19 are known to have an increased risk of thromboembolism, including cardiovascular, pulmonary and cerebral ischaemic events. However, an increasing number of case studies have reported that COVID-19 infection is also associated with gastrointestinal ischaemia. This scoping review aims to collate the current evidence of COVID-19-related gastrointestinal ischaemia and raise awareness among healthcare professionals of this lesser known, but serious, non-pulmonary complication of COVID-19 infection. METHODS: The proposed scoping review will be conducted as per the Arksey and O'Malley methodological framework (2005) the Joanna Briggs Institute methodology for scoping reviews. A systematic search will be undertaken on different databases including EMBASE, PubMed and MEDLINE. Two independent reviewers will screen titles, abstracts and full-text articles according to the inclusion criteria and extract relevant data from the included articles. Results will be presented in a tabular form with a narrative discussion. ETHICS AND DISSEMINATION: Ethical approval will not be required for this scoping review. This scoping review will provide an extensive overview of the association between COVID-19 infection and bowel ischaemia. Further ethical and methodological challenges will also be discussed in our findings to define a new research agenda. Findings will be disseminated through peer-reviewed publications and presentations at both national and international conferences.

Tricyclic Aza-Andrographolide Derivatives from Late-Stage Hydroamination and Their Anti-human Coronavirus (Anti-HCoV) Activity.

A late-stage functionalization (LSF) of the natural product andrographolide for the efficient assembly of a range of structurally interesting and diverse tricyclic-aza derivatives was developed. The key to the diversification is a photo-catalyzed intramolecular hydroamination reaction, and acridinium derivatives were demonstrated to be the optimal catalysts. Additionally, the synthesized tricyclic aza-andrographolide derivatives were found to inhibit human coronavirus with high potency.

Mathematical modeling for COVID-19 with focus on intervention strategies and cost-effectiveness analysis.

The realistic assessments of public health intervention strategies are of great significance to effectively combat the COVID-19 epidemic and the formation of intervention policy. In this paper, an extended COVID-19 epidemic model is devised to assess the severity of the pandemic and explore effective control strategies. The model is characterized by ordinary differential equations with seven-state variables, and it incorporates some parameters associated with the interventions (i.e., media publicity, home isolation, vaccination and face-mask wearing) to investigate the impacts of these interventions on the spread of the COVID-19 epidemic. Some dynamic behaviors of the model, such as forward and backward bifurcation, are analyzed. Specifically, we calibrate the model parameters using actual COVID-19 infected data in Brazil by Markov Chain Monte Carlo algorithm such that we can study the effects of interventions on a practical case. Through a comprehensive exploration of model design and analysis, model calibration, sensitivity analysis, implementation of optimal control problems and cost-effectiveness analysis, the rationality of our model is verified, and the effective strategies to combat the epidemic in Brazil are revealed. The results show that the asymptomatic infected individuals are the main drivers of COVID-19 transmission, and rapid detection of asymptomatic infections is critical to combat the COVID-19 epidemic in Brazil. Interestingly, the effect of the vaccination rate associated with pharmaceutical intervention on the basic reproduction number is much lower than that of non-pharmaceutical interventions (NPIs). Our study also highlights the importance of media publicity. To reduce the infected individuals, the multi-pronged NPIs have considerable positive effects on controlling the outbreak of COVID-19. The infections are significantly decreased by the early implementation of media publicity complemented with home isolation and face-mask wearing strategy. When the cost of implementation is taken into account, the early implementation of media publicity complemented with a face-mask wearing strategy can significantly mitigate the second wave of the epidemic in Brazil. These results provide some management implications for controlling COVID-19.

Public anxiety through various stages of COVID-19 coping: Evidence from China.

As countries underwent the initiation, peak, post-peak, and early vaccination stages of COVID-19, the changing risk perception, coping behaviors and corresponding psychological stress experienced by the public over time was rarely reported. We conducted a national scale panel study using social-psychological data collected from 5,983 questionnaires to investigate the interactions between anxiety level, risk perception and coping behavior during different stages of COVID-19 in China. We found that sustained perceiving worries of being infected, first due to domestic and then global pandemic, contributed to the persistent high proportion of respondents with anxiety disorders which even gradually increased over time (56.1% during initiation to 60.4% during early vaccination). Gender was the strongest predictor of anxiety at all stages, with females having less confidence in COVID-19 control and always suffering from much higher anxiety levels than males even during the post peak stage. Excessive protective behavior and frequency of access to COVID-related news also contributed to public anxiety. Additionally, public risk perception was significantly associated with their willingness to vaccinate. The findings verify the feasibility of taking stage-specific and gender-based risk communication strategies to alleviate the pandemic-related public anxiety and promote vaccination by influencing public risk perception and guiding coping behaviors.

Social alignment matters: Following pandemic guidelines is associated with better wellbeing.

BACKGROUND: In response to the Covid-19 pandemic, most countries implemented physical distancing measures. Many mental health experts warned that through increasing social isolation and anxiety, these measures could negatively affect psychosocial wellbeing. However, socially aligning with others by adhering to these measures may also be beneficial for wellbeing. METHODS: We examined these two contrasting hypotheses using cross-national survey data (N = 6675) collected fortnightly from participants in 115 countries over 3 months at the beginning of the pandemic. Participants reported their wellbeing, perceptions of how vulnerable they were to Covid-19 (i.e., high risk of infection) and how much they, and others in their social circle and country, were adhering to the distancing measures. RESULTS: Linear mixed-effects models showed that being a woman, having lower educational attainment, living alone and perceived high vulnerability to Covid-19 were risk factors for poorer wellbeing. Being young (18-25) was associated with lower wellbeing, but longitudinal analyses showed that young people's wellbeing improved over 3 months. In contrast to widespread views that physical distancing measures negatively affect wellbeing, results showed that following the guidelines was positively associated with wellbeing even for people in high-risk groups. CONCLUSIONS: These findings provide an important counterpart to the idea that pandemic containment measures such as physical distancing negatively impacted wellbeing unequivocally. Despite the overall burden of the pandemic on psychosocial wellbeing, social alignment with others can still contribute to positive wellbeing. The pandemic has manifested our propensity to adapt to challenges, particularly highlighting how social alignment can forge resilience.

Using a System Pharmacology Method to Search for the Potential Targets and Pathways of Yinqiaosan against COVID-19.

The first reported case of coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei, China. Thereafter, it spread through China and worldwide in only a few months, reaching a pandemic level. It can cause severe respiratory illnesses such as pneumonia and lung failure. Since the onset of the disease, the rapid response and intervention of traditional Chinese medicine (TCM) have played a significant role in the effective control of the epidemic. Yinqiaosan (YQS) was used to treat COVID-19 pneumonia, with good curative effects. However, a systematic overview of its active compounds and the therapeutic mechanisms underlying its action has yet to be performed. The purpose of the current study is to explore the compounds and mechanism of YQS in treating COVID-19 pneumonia using system pharmacology. A system pharmacology method involving drug-likeness assessment, oral bioavailability forecasting, virtual docking, and network analysis was applied to estimate the active compounds, hub targets, and key pathways of YQS in the treatment of COVID-19 pneumonia. With this method, 117 active compounds were successfully identified in YQS, and 77 potential targets were obtained from the targets of 95 compounds and COVID-19 pneumonia. The results show that YQS may act in treating COVID-19 pneumonia and its complications (atherosclerosis and nephropathy) through Kaposi sarcoma-related herpesvirus infection and the AGE-RAGE signaling pathway in diabetic complications and pathways in cancer. We distinguished the hub molecular targets within pathways such as TNF, GAPDH, MAPK3, MAPK1, EGFR, CASP3, MAPK8, mTOR, IL-2, and MAPK14. Five of the more highly active compounds (acacetin, kaempferol, luteolin, naringenin, and quercetin) have anti-inflammatory and antioxidative properties. In summary, by introducing a systematic network pharmacology method, our research perfectly forecasts the active compounds, potential targets, and key pathways of YQS applied to COVID-19 and helps to comprehensively clarify its mechanism of action.

Characterization of Constituents with Potential Anti-Inflammatory Activity in Chinese Lonicera Species by UHPLC-HRMS Based Metabolite Profiling.

This study centered on detecting potentially anti-inflammatory active constituents in ethanolic extracts of Chinese Lonicera species by taking an UHPLC-HRMS-based metabolite profiling approach. Extracts from eight different Lonicera species were subjected to both UHPLC-HRMS analysis and to pharmacological testing in three different cellular inflammation-related assays. Compounds exhibiting high correlations in orthogonal projections to latent structures discriminant analysis (OPLS-DA) of pharmacological and MS data served as potentially activity-related candidates. Of these candidates, 65 were tentatively or unambiguously annotated. 7-Hydroxy-5,3',4',5'-tetramethoxyflavone and three bioflavonoids, as well as three C32- and one C34-acetylated polyhydroxy fatty acid, were isolated from Lonicera hypoglauca leaves for the first time, and their structures were fully or partially elucidated. Of the potentially active candidate compounds, 15 were subsequently subjected to pharmacological testing. Their activities could be experimentally verified in part, emphasizing the relevance of Lonicera species as a source of anti-inflammatory active constituents. However, some compounds also impaired the cell viability. Overall, the approach was found useful to narrow down the number of potentially bioactive constituents in the complex extracts investigated. In the future, the application of more refined concepts, such as extract prefractionation combined with bio-chemometrics, may help to further enhance the reliability of candidate selection.

Patterns and influencing factors of COVID-19 vaccination willingness among college students in China.

BACKGROUND: Vaccination is an important preventive measure against the coronavirus disease 19 (COVID-19) pandemic. We aimed to examine the willingness to vaccination and influencing factors among college students in China. METHODS: From March 18 to April 26, 2021, we conducted a cross-sectional online survey among college students from 30 universities in Wuhan, Hubei Province, China. The survey was composed of the sociodemographic information, psychological status, experience during pandemic, the willingness of vaccination and related information. Students' attitudes towards vaccination were classified as 'vaccine acceptance', 'vaccine hesitancy', and 'vaccine resistance'. Multinomial logistic regression analyses were performed to identify the influencing factors associated with vaccine hesitancy and resistance. RESULTS: Among 23,143 students who completed the survey, a total of 22,660 participants were included in the final analysis with an effective rate of 97.9% after excluding invalid questionnaires. A total of 60.6% of participants would be willing to receive COVID-19 vaccine, 33.4% were hesitant to vaccination, and 6.0% were resistant to vaccination. Social media platforms and government agencies were the main sources of information vaccination. Worry about the efficacy and adverse effects of vaccine were the top two common reason of vaccine hesitancy and resistance. Multiple multinomial logistic regression analysis identified that participants who worried about the adverse effects of vaccination were more likely to be vaccine hesitancy (aOR = 2.44, 95% CI = 2.30, 2.58) and resistance (aOR = 2.71, 95% CI = 2.40, 3.05). CONCLUSION: More than half of college students are willing to receive the COVID-19 vaccine, whereas nearly one-third college students are still hesitant or resistant. It is crucial to provide sufficient and scientific information on the efficacy and safety of vaccine through social media and government agencies platforms to promote vaccine progress against COVID-19 and control the pandemic in China.

Exploring New Characteristics: Using Deep Learning and 3D Reconstruction to Compare the Original COVID-19 and Its Delta Variant Based on Chest CT.

Purpose: Computer-aided diagnostic methods were used to compare the characteristics of the Original COVID-19 and its Delta Variant. Methods: This was a retrospective study. A deep learning segmentation model was applied to segment lungs and infections in CT. Three-dimensional (3D) reconstruction was used to create 3D models of the patient's lungs and infections. A stereoscopic segmentation method was proposed, which can subdivide the 3D lung into five lobes and 18 segments. An expert-based CT scoring system was improved and artificial intelligence was used to automatically score instead of visual score. Non-linear regression and quantitative analysis were used to analyze the dynamic changes in the percentages of infection (POI). Results: The POI in the five lung lobes of all patients were calculated and converted into CT scores. The CT scores of Original COVID-19 patients and Delta Variant patients since the onset of initial symptoms were fitted over time, respectively. The peak was found to occur on day 11 in Original COVID-19 patients and on day 15 in Delta Variant patients. The time course of lung changes in CT of Delta Variant patients was redetermined as early stage (0-3 days), progressive and peak stage (4-16 days), and absorption stage (17-42 days). The first RT-PCR negative time in Original COVID-19 patients appeared earlier than in Delta Variant patients (22 [17-30] vs. 39 [31-44], p < 0.001). Delta Variant patients had more re-detectable positive RT-PCR test results than Original COVID-19 patients after the first negative RT-PCR time (30.5% vs. 17.1%). In the early stage, CT scores in the right lower lobe were significantly different (Delta Variant vs. Original COVID-19, 0.8 ± 0.6 vs. 1.3 ± 0.6, p = 0.039). In the absorption stage, CT scores of the right middle lobes were significantly different (Delta Variant vs. Original COVID-19, 0.6 ± 0.7 vs. 0.3 ± 0.4, p = 0.012). The left and the right lower lobes contributed most to lung involvement at any given time. Conclusion: Compared with the Original COVID-19, the Delta Variant has a longer lung change duration, more re-detectable positive RT-PCR test results, different locations of pneumonia, and more lesions in the early stage, and the peak of infection occurred later.