Safety and immunogenicity of heterologous boosting with orally aerosolised or intramuscular Ad5-nCoV vaccine and homologous boosting with inactivated vaccines (BBIBP-CorV or CoronaVac) in children and adolescents: a randomised, open-label, parallel-controlled, non-inferiority, single-centre study.

BACKGROUND: Heterologous booster immunisation with orally administered aerosolised Ad5-nCoV vaccine (AAd5) has been shown to be safe and highly immunogenic in adults. Here, we aimed to assess the safety and immunogenicity of heterologous booster immunisation with orally administered AAd5 in children and adolescents aged 6-17 years who had received two doses of inactivated vaccine (BBIBP-CorV or CoronaVac). METHODS: We did a randomised, open-label, parallel-controlled, non-inferiority study to assess the safety and immunogenicity of heterologous booster immunisation with AAd5 (0·1 mL) or intramuscular Ad5-nCoV vaccine (IMAd5; 0·3 mL) and homologous booster immunisation with inactivated vaccine (BBIBP-CorV or CoronaVac; 0·5 mL) in children (aged 6-12 years) and adolescents (aged 13-17 years) who had received two doses of inactivated vaccine at least 3 months earlier in Hunan, China. Children and adolescents who were previously immunised with two-dose BBIBP-CorV or CoronaVac were recruited for eligibility screening at least 3 months after the second dose. A stratified block method was used for randomisation, and participants were stratified by age and randomly assigned (3:1:1) to receive AAd5, IMAd5, or inactivated vaccine. The study staff and participants were not masked to treatment allocation. Laboratory and statistical staff were masked during the study. In this interim analysis, adverse events within 14 days and geometric mean titre (GMT) of serum neutralising antibodies on day 28 after the booster vaccination, based on the per-protocol population, were used as the primary outcomes. The analysis of non-inferiority was based on comparison using a one-sided 97·5% CI with a non-inferiority margin of 0·67. This study was registered at ClinicalTrials.gov, NCT05330871, and is ongoing. FINDINGS: Between April 17 and May 28, 2022, 436 participants were screened and 360 were enrolled: 220 received AAd5, 70 received IMAd5, and 70 received inactivated vaccine. Within 14 days after booster vaccination, vaccine-related adverse reactions were reported: 35 adverse events (in 13 [12%] of 110 children and 22 [20%] of 110 adolescents) in 220 individuals in the AAd5 group, 35 (in 18 [51%] of 35 children and 17 [49%] of 35 adolescents) in 70 individuals in the IMAd5 group, and 13 (in five [14%] of 35 children and eight [23%] of 35 adolescents) in 70 individuals in the inactivated vaccine group. Solicited adverse reactions were also reported: 34 (13 [12%] of 110 children and 21 [10%] of 110 adolescents) in 220 individuals in the AAd5 group, 34 (17 [49%] of 35 children and 17 [49%] of 35 adolescents) in 70 individuals in the IMAd5 group, and 12 (five [14%] of 35 children and seven [20%] of 35 adolescents) in 70 individuals in the inactivated vaccine group. The GMTs of neutralising antibodies against ancestral SARS-CoV-2 Wuhan-Hu-1 (Pango lineage B) in the AAd5 group were significantly higher than the GMTs in the inactivated vaccine group (adjusted GMT ratio 10·2 [95% CI 8·0-13·1]; p<0·0001). INTERPRETATION: Our study shows that a heterologous booster with AAd5 is safe and highly immunogenic against ancestral SARS-CoV-2 Wuhan-Hu-1 in children and adolescents. FUNDING: National Key R&D Program of China.

Investigation on mental health status and psychological service demands of volunteers during the epidemic

Objective: To comprehend the mental health status and its influencing factors of volunteers during the epidemic. Methods: In March 2020, through the network platform, 384 volunteers who participated in the epidemic prevention and control work in Jinshan District of Shanghai were surveyed by cluster sampling. Perceived stress scale (PSS-10), generalized anxiety disorder (GAD-7) and patient health questionnaire (PHQ-9) were used to evaluate the stress status, anxiety symptoms and depression symptoms of the subjects, and the psychological service demands of the subjects were investigated. Results: Totally 361 valid questionnaires were received with the recovery rate of 94.01%. It was found that 101 people (27.98%) had stress symptoms, 65 people (18.01%) had anxiety symptoms, and 67 people (18.56%) had depression symptoms. Among these, 61 people (16.90%) had two or more types of positive symptoms at the same time. Logistic regression analysis showed that more than 12 hours of volunteer service per week was a risk factor for stress (OR = 2.100, P < 0.05), while the familiarity with COVID-19 epidemic was a risk factor for anxiety (OR = 2.507), depression (OR = 2.674) and high-risk psychological status (OR = 2.742) (P < 0.05). People with stress, anxiety, depression and high-risk mental health status had stronger demands for mental health services (P < 0.05). Conclusions: In the early stage of the epidemic, the mental health of volunteers participating in prevention and control of epidemic in Jinshan District of Shanghai was not bad. However, it is still suggested that we should improve the construction of volunteer service system and pay attention to the physical and mental health of volunteers, establish a reasonable rest system and personal protection and social support system, emphasize the publicity and education of mental health, and provide necessary mental health services for volunteers in serious public health events.

SARS-CoV-2 Surveillance Through China Influenza Surveillance Information System - China, December 1, 2022 to February 12, 2023.

Introduction: The World Health Organization (WHO) proposed using influenza surveillance systems to carry out coronavirus disease 2019 (COVID-19) surveillance due to the similarity between the two diseases in some respiratory symptoms. To assess the prevalence of COVID-19, we analyzed the influenza-like illness (ILI) and positive rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detections in ILI patients reported to the influenza Surveillance Information System (CNISIS) since late 2022. Methods: Data related to ILI were reported by national surveillance sentinel hospitals. Positive testing for SARS-CoV-2 and influenza viruses was conducted using real-time reverse transcription polymerase chain reaction (rRT-PCR) detection by the national influenza surveillance network laboratories. Surveillance data were reported to CNISIS. Results: Beginning on December 12, 2022 (Week 50), the ILI percentage increased dramatically, peaking in Week 51 at 12.1%. Subsequently, the ILI percentage began to decline rapidly from Week 52, 2022, and by Week 6, 2023 (February 6-12), the ILI and ILI percentage had returned to the levels observed at the beginning of December 2022. From December 1, 2022 to February 12, 2023, 115,844 specimens were tested for both SARS-CoV-2 and influenza virus. Of these, 30,381 (26.2%) were positive for SARS-CoV-2 and 1,763 (1.5%) were positive for influenza virus. The positive rate of SARS-CoV-2 tests peaked at 74.1% around December 23 and 25. Conclusions: Sentinel-based surveillance, previously established for influenza, is an effective way to track the circulation trend of SARS-CoV-2 during community-level epidemics. There was no co-prevalence of SARS-CoV-2 and influenza virus during the outbreak of SARS-CoV-2, even during the winter influenza season. However, it is important to remain vigilant for the potential rise of influenza activities following the COVID-19 epidemic.

Trends of SARS-CoV-2 Infection Among Couriers in Risky Business After the Optimization of Prevention and Control Measures - China, December 2022 to January 2023.

Introduction: On December 7, 2022, China implemented "Ten New Measures" to optimize prevention and control measures for coronavirus disease 2019 (COVID-19). The purpose of this study was to evaluate the national and regional trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among couriers in China from December 2022 to January 2023. Methods: Data from the National Sentinel Community-based Surveillance in China was utilized, including participants from 31 provincial-level administrative divisions and Xinjiang Production and Construction Corps. Participants were tested for SARS-CoV-2 infection twice a week from December 16, 2022 to January 12, 2023. Infection was defined as a positive result for SARS-CoV-2 nucleic acid or antigen. The daily average newly positive rate of SARS-CoV-2 infection and the estimated daily percentage change (EDPC) were calculated. Results: In this cohort, 8 rounds of data were collected. The daily average newly positive rate of SARS-CoV-2 infection decreased from 4.99% in Round 1 to 0.41% in Round 8, with an EDPC of -33.0%. Similar trends of the positive rate were also observed in the eastern (EDPC: -27.7%), central (EDPC: -38.0%) and western regions (EDPC: -25.5%). Couriers and community population showed a similar temporal trend, with the peak daily average newly positive rate of couriers being higher than that of community population. After Round 2, the daily average newly positive rate of couriers decreased sharply, becoming lower than that of community population in the same period. Conclusions: The peak of SARS-CoV-2 infection among couriers in China has passed. As couriers are a key population for SARS-CoV-2 infection, they should be monitored continuously.

Trends of SARS-CoV-2 Infection in Sentinel Community-Based Surveillance After the Optimization of Prevention and Control Measures - China, December 2022-January 2023.

Introduction: On December 7, 2022, China implemented the "Ten New Measures" to optimize its prevention and control measures for coronavirus disease 2019 (COVID-19). To provide the latest data after the optimization, we evaluated trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among the community population in China. Methods: We utilized data from the National Sentinel Community-Based Surveillance (NSCS) system in China to assess trends of SARS-CoV-2 infection. NSCS is a national community-based surveillance cohort with 0.42 million participants from all 31 provincial-level administrative divisions (PLADs) and Xinjiang Production and Construction Corps (XPCC). Participants were tested for infection twice a week (a total of eight rounds) from December 16, 2022 to January 12, 2023. SARS-CoV-2 infection was defined as testing positive for SARS-CoV-2 nucleic acid or antigen. We calculated the daily average of newly positive rates of SARS-CoV-2 infection. Results: In this national cohort, the daily average newly positive rate of SARS-CoV-2 infection decreased from 4.13% in Round 1 (December 16-19, 2022) to 0.69% in Round 8 (January 10-12, 2023). The epidemic peak occurred in Round 2 (December 20-22, 2022). Similar trends were observed in urban areas (decreasing from 4.65% to 0.73%), rural areas (decreasing from 2.83% to 0.57%), the eastern region (decreasing from 4.18% to 0.67%), the central region (decreasing from 5.43% to 0.61%), and the western region (decreasing from 3.01% to 0.77%). Conclusions: NSCS data showed that the peak of SARS-CoV-2 infection in China had passed. SARS-CoV-2 infection in community populations in China is currently at a low epidemic level.

Trends of SARS-CoV-2 Infection in Rural Area in Sentinel Community-Based Surveillance - China, December 2022 to January 2023.

Introduction: In late 2022, a rapid transmission of Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred throughout China. The purpose of this study was to provide the latest data and evaluate trends of SARS-CoV-2 infection in rural China among the community population. Methods: Data on SARS-CoV-2 infection among approximately 90,000 participants in rural China were collected by the National Sentinel Community-Based Surveillance (NSCS) system. Participants were tested for SARS-CoV-2 infection (defined as positive for SARS-CoV-2 nucleic acid or antigen) twice weekly from December 16, 2022 to January 12, 2023. The daily average of newly positive rate and its estimated daily percentage change were calculated to describe the national and regional trends of SARS-CoV-2 infection in rural China. Results: In rural China, the daily average new positive rate of SARS-CoV-2 infection peaked at 4.79% between December 20-22, 2022 and then decreased to 0.57% between January 10-12, 2023, with an average decrease of 29.95% per round. The peak of new SARS-CoV-2 infection was slightly earlier and lower in North China (5.28% between December 20-22, 2022) than in South China (5.63% between December 23-26, 2022), and then converged from December 30, 2022 to January 2, 2023. The peak of 6.09% occurred between December 20-22, 2022 in eastern China, while the peak of 5.99% occurred later, between December 27-29, 2022, in central China. Conclusions: Overall, the epidemic wave in rural China peaked between December 20-22, 2022, and passed quickly following the optimization of prevention and control measures. Currently, SARS-CoV-2 infection in community populations in rural China is sporadic.

A Self-Supervised Detail-Sensitive ViT-Based Model for COVID-19 X-ray Image Diagnosis: SDViT

COVID-19 has led to a severe impact on the society and healthcare system, with early diagnosis and effective treatment becoming critical. The Chest X-ray (CXR) is the most time-saving and cost-effective tool for diagnosing COVID-19. However, manual diagnosis through human eyes is time-consuming and tends to introduce errors. With the challenge of a large number of infections and a shortage of medical resources, a fast and accurate diagnosis technique is required. Manual detection is time-consuming, depends on individual experience, and tends to easily introduce errors. Deep learning methods can be used to develop automated detection and computer-aided diagnosis. However, they require a large amount of data, which is not practical due to the limited annotated CXR images. In this research, SDViT, an approach based on transformers, is proposed for COVID-19 diagnosis through image classification. We propose three innovations, namely, self-supervised learning, detail correction path (DCP), and domain transfer, then add them to the ViT Transformer architecture. Based on experimental results, our proposed method achieves an accuracy of 95.2381%, which is better performance compared to well-established methods on the X-ray Image dataset, along with the highest precision (0.952310), recall (0.963964), and F1-score (0.958102). Extensive experiments show that our model achieves the best performance on the synthetic-covid-cxr dataset as well. The experimental results demonstrate the advantages of our design for the classification task of COVID-19 X-ray images.

Severe Acute Respiratory Syndrome Coronavirus 2 Delta Vaccine Breakthrough Transmissibility in Alachua County, Florida.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant has caused a dramatic resurgence in infections in the United Sates, raising questions regarding potential transmissibility among vaccinated individuals. METHODS: Between October 2020 and July 2021, we sequenced 4439 SARS-CoV-2 full genomes, 23% of all known infections in Alachua County, Florida, including 109 vaccine breakthrough cases. Univariate and multivariate regression analyses were conducted to evaluate associations between viral RNA burden and patient characteristics. Contact tracing and phylogenetic analysis were used to investigate direct transmissions involving vaccinated individuals. RESULTS: The majority of breakthrough sequences with lineage assignment were classified as Delta variants (74.6%) and occurred, on average, about 3 months (104 ±â€…57.5 days) after full vaccination, at the same time (June-July 2021) of Delta variant exponential spread within the county. Six Delta variant transmission pairs between fully vaccinated individuals were identified through contact tracing, 3 of which were confirmed by phylogenetic analysis. Delta breakthroughs exhibited broad viral RNA copy number values during acute infection (interquartile range, 1.2-8.64 Log copies/mL), on average 38% lower than matched unvaccinated patients (3.29-10.81 Log copies/mL, P < .00001). Nevertheless, 49% to 50% of all breakthroughs, and 56% to 60% of Delta-infected breakthroughs exhibited viral RNA levels above the transmissibility threshold (4 Log copies/mL) irrespective of time after vaccination. CONCLUSIONS: Delta infection transmissibility and general viral RNA quantification patterns in vaccinated individuals suggest limited levels of sterilizing immunity that need to be considered by public health policies. In particular, ongoing evaluation of vaccine boosters should specifically address whether extra vaccine doses curb breakthrough contribution to epidemic spread.

Low-frequency variants in mildly symptomatic vaccine breakthrough infections presents a doubled-edged sword.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) has raised questions regarding vaccine protection against SARS-CoV-2 infection, transmission, and ongoing virus evolution. Twenty-three mildly symptomatic "vaccination breakthrough" infections were identified as early as January 2021 in Alachua County, Florida, among individuals fully vaccinated with either the BNT162b2 (Pfizer) or the Ad26 (Janssen/J&J) vaccines. SARS-CoV-2 genomes were successfully generated for 11 of the vaccine breakthroughs, and 878 individuals in the surrounding area and were included for reference-based phylogenetic investigation. These 11 individuals were characterized by infection with VOCs, but also low-frequency variants present within the surrounding population. Low-frequency mutations were observed, which have been more recently identified as mutations of interest owing to their location within targeted immune epitopes (P812L) and association with increased replicative capacity (L18F). We present these results to posit the nature of the efficacy of vaccines in reducing symptoms as both a blessing and a curse-as vaccination becomes more widespread and self-motivated testing reduced owing to the absence of severe symptoms, we face the challenge of early recognition of novel mutations of potential concern. This case study highlights the critical need for continued testing and monitoring of infection and transmission among individuals regardless of vaccination status.

Risk Factors for Death Among the First 80 543 Coronavirus Disease 2019 (COVID-19) Cases in China: Relationships Between Age, Underlying Disease, Case Severity, and Region.

BACKGROUND: Knowledge of COVID-19 epidemiology remains incomplete and crucial questions persist. We aimed to examine risk factors for COVID-19 death. METHODS: A total of 80 543 COVID-19 cases reported in China, nationwide, through 8 April 2020 were included. Risk factors for death were investigated by Cox proportional hazards regression and stratified analyses. RESULTS: Overall national case-fatality ratio (CFR) was 5.64%. Risk factors for death were older age (≥80: adjusted hazard ratio, 12.58; 95% confidence interval, 6.78-23.33), presence of underlying disease (1.33; 1.19-1.49), worse case severity (severe: 3.86; 3.15-4.73; critical: 11.34; 9.22-13.95), and near-epicenter region (Hubei: 2.64; 2.11-3.30; Wuhan: 6.35; 5.04-8.00). CFR increased from 0.35% (30-39 years) to 18.21% (≥70 years) without underlying disease. Regardless of age, CFR increased from 2.50% for no underlying disease to 7.72% for 1, 13.99% for 2, and 21.99% for ≥3 underlying diseases. CFR increased with worse case severity from 2.80% (mild) to 12.51% (severe) and 48.60% (critical), regardless of region. Compared with other regions, CFR was much higher in Wuhan regardless of case severity (mild: 3.83% vs 0.14% in Hubei and 0.03% elsewhere; moderate: 4.60% vs 0.21% and 0.06%; severe: 15.92% vs 5.84% and 1.86%; and critical: 58.57% vs 49.80% and 18.39%). CONCLUSIONS: Older patients regardless of underlying disease and patients with underlying disease regardless of age were at elevated risk of death. Higher death rates near the outbreak epicenter and during the surge of cases reflect the deleterious effects of allowing health systems to become overwhelmed.

DATLMedQA: A Data Augmentation and Transfer Learning Based Solution for Medical Question Answering

With the outbreak of COVID-19 that has prompted an increased focus on self-care, more and more people hope to obtain disease knowledge from the Internet. In response to this demand, medical question answering and question generation tasks have become an important part of natural language processing (NLP). However, there are limited samples of medical questions and answers, and the question generation systems cannot fully meet the needs of non-professionals for medical questions. In this research, we propose a BERT medical pretraining model, using GPT-2 for question augmentation and T5-Small for topic extraction, calculating the cosine similarity of the extracted topic and using XGBoost for prediction. With augmentation using GPT-2, the prediction accuracy of our model outperforms the state-of-the-art (SOTA) model performance. Our experiment results demonstrate the outstanding performance of our model in medical question answering and question generation tasks, and its great potential to solve other biomedical question answering challenges.

SARS-CoV-2 competes with host mRNAs for efficient translation by maintaining the mutations favorable for translation initiation.

During SARS-CoV-2 proliferation, the translation of viral RNAs is usually the rate-limiting step. Understanding the molecular details of this step is beneficial for uncovering the origin and evolution of SARS-CoV-2 and even for controlling the pandemic. To date, it is unclear how SARS-CoV-2 competes with host mRNAs for ribosome binding and efficient translation. We retrieved the coding sequences of all human genes and SARS-CoV-2 genes. We systematically profiled the GC content and folding energy of each CDS. Considering that some fixed or polymorphic mutations exist in SARS-CoV-2 and human genomes, all algorithms and analyses were applied to both pre-mutate and post-mutate versions. In SARS-CoV-2 but not human, the 5-prime end of CDS had lower GC content and less RNA structure than the 3-prime part, which was favorable for ribosome binding and efficient translation initiation. Globally, the fixed and polymorphic mutations in SARS-CoV-2 had created an even lower GC content at the 5-prime end of CDS. In contrast, no similar patterns were observed for the fixed and polymorphic mutations in human genome. Compared with human RNAs, the SARS-CoV-2 RNAs have less RNA structure in the 5-prime end and thus are more favorable of fast translation initiation. The fixed and polymorphic mutations in SARS-CoV-2 are further amplifying this advantage. This might serve as a strategy for SARS-CoV-2 to adapt to the human host.

Compelling Evidence Suggesting the Codon Usage of SARS-CoV-2 Adapts to Human After the Split From RaTG13.

SARS-CoV-2 needs to efficiently make use of the resources from hosts in order to survive and propagate. Among the multiple layers of regulatory network, mRNA translation is the rate-limiting step in gene expression. Synonymous codon usage usually conforms with tRNA concentration to allow fast decoding during translation. It is acknowledged that SARS-CoV-2 has adapted to the codon usage of human lungs so that the virus could rapidly proliferate in the lung environment. While this notion seems to nicely explain the adaptation of SARS-CoV-2 to lungs, it is unable to tell why other viruses do not have this advantage. In this study, we retrieve the GTEx RNA-seq data for 30 tissues (belonging to over 17 000 individuals). We calculate the RSCU (relative synonymous codon usage) weighted by gene expression in each human sample, and investigate the correlation of RSCU between the human tissues and SARS-CoV-2 or RaTG13 (the closest coronavirus to SARS-CoV-2). Lung has the highest correlation of RSCU to SARS-CoV-2 among all tissues, suggesting that the lung environment is generally suitable for SARS-CoV-2. Interestingly, for most tissues, SARS-CoV-2 has higher correlations with the human samples compared with the RaTG13-human correlation. This difference is most significant for lungs. In conclusion, the codon usage of SARS-CoV-2 has adapted to human lungs to allow fast decoding and translation. This adaptation probably took place after SARS-CoV-2 split from RaTG13 because RaTG13 is less perfectly correlated with human. This finding depicts the trajectory of adaptive evolution from ancestral sequence to SARS-CoV-2, and also well explains why SARS-CoV-2 rather than other viruses could perfectly adapt to human lung environment.

Fast evolution of SARS-CoV-2 driven by deamination systems in hosts.

As an RNA virus, the fast evolution of SARS-CoV-2 is driven by the extensive RNA deamination by the host cells.

Spatiotemporal visualization for the global COVID-19 surveillance by balloon chart.

BACKGROUND: Considering the widespread of coronavirus disease 2019 (COVID-19) pandemic in the world, it is important to understand the spatiotemporal development of the pandemic. In this study, we aimed to visualize time-associated alterations of COVID-19 in the context of continents and countries. METHODS: Using COVID-19 case and death data from February to December 2020 offered by Johns Hopkins University, we generated time-associated balloon charts with multiple epidemiological indicators including crude case fatality rate (CFR), morbidity, mortality and the total number of cases, to compare the progression of the pandemic within a specific period across regions and countries, integrating seven related dimensions together. The area chart is used to supplement the display of the balloon chart in daily new COVID-19 case changes in UN geographic regions over time. Javascript and Vega-Lite were chosen for programming and mapping COVID-19 data in browsers for visualization. RESULTS: From February 1st to December 20th 2020, the COVID-19 pandemic spread across UN subregions in the chronological order. It was first reported in East Asia, and then became noticeable in Europe (South, West and North), North America, East Europe and West Asia, Central and South America, Southern Africa, Caribbean, South Asia, North Africa, Southeast Asia and Oceania, causing several waves of epidemics in different regions. Since October, the balloons of Europe, North America and West Asia have been rising rapidly, reaching a dramatically high morbidity level ranging from 200 to 500/10 000 by December, suggesting an emerging winter wave of COVID-19 which was much bigger than the previous ones. By late December 2020, some European and American countries displayed a leading mortality as high as or over 100/100 000, represented by Belgium, Czechia, Spain, France, Italy, UK, Hungary, Bulgaria, Peru, USA, Argentina, Brazil, Chile and Mexico. The mortality of Iran was the highest in Asia (over 60/100 000), and that of South Africa topped in Africa (40/100 000). In the last 15 days, the CFRs of most countries were at low levels of less than 5%, while Mexico had exceptional high CFR close to 10%. CONCLUSIONS: We creatively used visualization integrating 7-dimensional epidemiologic and spatiotemporal indicators to assess the progression of COVID-19 pandemic in terms of transmissibility and severity. Such methodology allows public health workers and policy makers to understand the epidemics comparatively and flexibly.