Covid-19 Excess Mortality in China: A Regional Comparison (preprint)

Estimates of Covid-19 excess mortality are often considered to reflect the true death toll of the pandemic. As such, information on excess mortality is urgently needed to better understand the impact of the pandemic and prepare for future crises. This study estimated Covid-19 excess mortality at the provincial, regional, and national levels in China and investigated its associated regional disparities. The analyses were based on population and death rates data published by the national and provincial bureaus of statistics in China. The results suggest that excess deaths in China were over 1 million during each year of the pandemic, totaling to over 4 million by the end of 2022, at an excess death rate of 15.4%. This rate was likely comparable to that of the Organization for Economic Cooperation and Development (OECD), but lower than the US rate. Striking disparities were discovered among the 31 provinces with excess death rates ranging from negative rates in two eastern provinces to over 30% in three inland provinces. Rates in western China were over twice as high as those in eastern China. Variations with each individual regions were the largest in the central region and the smallest in the Northeast, which was the hardest hit with excess death rate of over 23%. The regional disparities in excess mortality rates seem to reflect pre-existing regional inequalities in socio-economic development in China. Such findings suggest that China has far to go to mitigate regional inequalities, achieve sustainability, and prepare for the next major crises.

Sustainability Indexes as Possible Predictors of Excess Mortality across OECD Countries during the Covid-19 Pandemic (preprint)

This study considered the Sustainable Development Goals (SDG) Index, Human Development Index (HDI), and Environmental Performance Index (EPI) as sustainability indexes and explored their potential effectiveness as predictors of Covid-19 excess mortality among countries in the Organization for Economic Cooperation and Development (OECD). The results indicated strong negative correlations between each index and Covid-19 excess mortality. Each of the indexes was able to consistently predict variations in excess mortality in the regression models. Such findings contribute to the current discussion on what lessons we should take away from the Covid-19 pandemic, specifically whether sustainability indexes may be useful in assessing Covid-19 outcomes. It is valuable to further examine the role sustainable policies and practices can play in preparing for future crises, as it has been demonstrated that social, economic, and environmental factors influenced the ability of a country to mitigate the impact of Covid-19. Overall, the most effective way for a country to both prevent and prepare for the next crisis is to improve health, education, and standard of living for its people, protect the environment, and achieve sustainability.

Aerosol Jet Printing Enabled Dual-Function Electrochemical and Colorimetric Biosensor for SARS-CoV-2 Detection (preprint)

An aerosol jet printing enabled dual-function biosensor for the sensitive detection of pathogens using SARS-CoV-2 RNA as an example has been developed. A CRISPR-Cas13: guide-RNA complex is activated in the presence of a target RNA, leading to the collateral trans-cleavage of ssRNA probes that contain a horseradish peroxidase (HRP) tag. This, in turn, catalyzes the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by HRP, resulting in a color change and electrochemical signal change. The colorimetric and electrochemical sensing protocol does not require complicated target amplification and probe immobilization and exhibits a detection sensitivity in the femtomolar range. Additionally, our biosensor demonstrates a wide dynamic range of 5 orders of magnitude. This low-cost aerosol inkjet printing technique allows for an amplification-free and integrated dual-function biosensor platform, which operates at physiological temperature and is designed for simple, rapid, and accurate point-of-care (POC) diagnostics in either low-resource settings or hospitals.

Comparison of foodborne disease outbreaks data in China and the United States from 2011 to 2017 and its inspiration for the construction of monitoring system in China

The history of the establishment of foodborne disease outbreak monitoring system in the United States was introduced and the surveillance data of foodborne disease outbreaks in the United States from 2011 to 2017 were analyzed and compared with that in China. It was found that there were obvious differences in the characteristics of surveillance data of foodborne disease outbreaks between China and the United States in the same period, and microbial pathogenic factors were the main cause of foodborne disease outbreaks. Facing the challenges of global trade integration and post epidemic era of COVID-19,China's foodborne disease outbreak monitoring system should accelerate the use of new technologies to improve the ability of identification and early warning, and foodborne disease outbreak data results should further play the technical support role in the formulation of relevant food safety management measures in China.

Breakthrough infection with Omicron subvariant BF.7 induces broadly neutralizing antibodies to SARS-CoV-2 variants including XBB lineage (preprint)

Since China eased its COVID-19 response strategies in late 2022, we have been witnessing a rapid and wide spread of SARS-CoV-2 infection across the major cities, including capital Beijing, where Omicron subvariant BF.7 has been dominating the infection. Here, we show that such expansion is unlikely due to a higher binding affinity of BF.7 to human receptor angiotensin-converting enzyme 2 (ACE2) as the similar binding activities were found for other Omicron subvariants tested such as BA.1, BA.5.2, BQ.1, BQ.1.1, XBB, and XBB.1. Additionally, through study of antibody response among six different clinical cohorts, we found that primary infection with BF.7 among the unvaccinated individuals only elicited type-specific neutralizing antibodies to the infecting virus and its close related strains. By a distinct contrast, breakthrough infection with BF.7 among the vaccinated individuals, particularly those severe cases, induced strong and broadly neutralizing antibodies to a diverse panel of SARS-CoV-2 variants and Omicron subvariants including the XBB lineage. A deeper understanding of how these broadly neutralizing antibodies were generated or boosted by BF.7 breakthrough infection will hold the key for augmenting antibody immunity against diverse SARS-CoV-2 variants.

Serum miR-21 and miR-148b levels in patients with chronic hepatitis B and their predictive value for liver tissue inflammation grading and fibrosis staging

Objective: The aim of this study was to explore the predictive value of serum microRNAs (miR)-21 and miR-148b for liver histopathological inflammation grading and fibrosis staging in patients with chronic hepatitis B (CHB).

The Psychosocial Factors Affecting Chinese Outbound Exchange and Mobility Students' Academic Performance During COVID-19.

COVID-19 has affected every aspect of our life, including economic, social, and academic. Exchange and mobility students face more difficulties overseas, and Chinese students are no exception. However, e-learning has been introduced by institutions in many countries. The present study examines the psychosocial factors affecting the academic performance of Chinese outbound exchange and mobility students during the COVID-19 pandemic. The study surveys about 186 Chinese outbound exchange and mobility students. The present study performs the quantitative data analysis using Partial Least Square Structural Equation Modeling (PLS-SEM) through the Smart PLS software version 3. By confirming the measurement model and structural model assessments, the study finds that personality, social support, and language fluency are psychosocial factors that significantly influence the exchange and mobility students' academic performance. This study contributes by establishing relationships among psychosocial factors, language fluency and academic performance. Besides, practitioners can be benefitted by understanding students' psychosocial factors and its relation to academic performance during COVID-19 pandemic.

Tri-light Warning System for Hospitalized COVID-19 Patients]{A Tri-light Warning System for Hospitalized COVID-19 Patients: Credibility-based Risk Stratification under Data Shift (preprint)

Early warning of the novel coronavirus pneumonia (COVID-19) during the evolving pandemic waves is crucial for the timely treatment of patients and optimization of medical resource allocation. However, prior AI-based models often lack the reliability and performance validation under data distribution drifts, and are therefore problematic to be reliably utilized in real-world clinical practice. To address this challenge, we developed a tri-light warning system based on conformal prediction for rapidly stratification of COVID-19 inpatients. This system can automatically extract radiomic features from CT images and integrate clinical record information to output a prediction probability, as well as a credibility of each prediction. This system classifies patients in the general ward into red label (high risk) indicating a possible admission to ICU care, yellow label (uncertain risk) indicating closer monitoring, and green label (low risk) indicating a stable condition. The subsequent health policies can be further designed based on this system according to the specific needs of different hospitals. Extensive experiment from a multi-center cohort (n= 8,721) shows that our method is applicable to both the original strain and the variant strains of COVID-19. Given the rapid mutation rate of COVID-19, the proposed system demonstrates its potential to identify epidemiological risks early to improve patient stratification performance under data shift.

Myopia progression and associated factors of refractive status in children and adolescents in Tibet and Chongqing during the COVID-19 pandemic

Objectives To investigate myopia progression and associated factors of refractive status among children and adolescents in Tibet and Chongqing in China during the COVID-19 pandemic. Methods A population-based cross-sectional study was conducted to compare rates of myopia and high myopia, axial length (AL), spherical equivalent (SE), outdoor activity time, digital device use, and frequency of visual examinations for children and adolescents affected by myopia in Chongqing and Tibet in 2021. Results A total of 2,303 students from Chongqing and 1,687 students from Tibet were examined. The overall prevalence of myopia and high myopia in these two groups were 53.80 and 7.04% vs. 43.86 and 1.30%, respectively in each case. The Chongqing students had a longer AL than the group from Tibet (23.95 vs. 23.40 mm, respectively;p < 0.001). The mean SE of the students with myopic parents in Tibet was lower than that of the students in Chongqing with myopic parents (−2.57 ± 2.38 diopters (D) vs. −2.30 ± 2.34 D, respectively) (p < 0.001). Conversely, the mean SE of the students from urban areas in Chongqing was lower than that of the students in Tibet (−2.26 ± 2.25 D vs. −1.75 ± 1.96 D, respectively;p < 0.001). The Chongqing students exhibited lower SE (−2.44 ± 2.22 D) than their Tibetan counterparts (mean SE: −1.78 ± 1.65 D (p = 0.0001) when spending more than 2.5 h outdoors. For example, 61.35% of the students in Tibet spent more than 2.5 h outdoors daily, compared with 43.04% of the students in Chongqing. Correspondingly, the proportion of students using digital devices in Tibet (64.43%) was lower than that in Chongqing (100%). For the latter, 38.62% of the students in Chongqing spent more than 2.5 h online using digital devices compared to 10.49% of the students in Tibet. Greater monitoring of visual status was observed for the Chongqing students (mean SE: −1.90 ± 1.98 D) compared with students in Tibet (mean SE: −2.68 ± 1.85 D) (p = 0.0448), with the frequency of optimal examinations being every 6 months. Outdoor activity time was identified as a common risk factor for myopia in both of the populations examined, with odds ratios (ORs) of 1.84 (95% CI: 1.79–1.90) in Chongqing and 0.84 (95% CI: 0.73–0.96) in Tibet. Digital screen time was associated with myopia and high myopia in Chongqing, with ORs of 1.15 (95% CI: 1.08–1.22) and 1.06 (95% CI: 0.94–1.77), respectively. Digital screen time was also found to be a risk factor for high myopia in Tibet (OR: 1.21, 95% CI: 0.77–1.61). The type of digital devices used was also associated with myopia and high myopia in Tibet (OR: 1.33, 95% CI: 1.06–1.68 and OR: 1.49, 95% CI: 0.84–2.58, respectively). Finally, examination frequency was found to correlate with high myopia in the Tibet group (OR: 1.79, 95% CI: 0.66–2.71). Conclusion Based on our data, we observed that the prevalence of refractive errors in children and adolescents was significantly lower in Tibet than in Chongqing. These results are potentially due to prolonged outdoor activity time, and the type and time of use for digital devices that characterize the group of children and adolescents from Tibet. It is recommended that parents and children in Chongqing would benefit from increased awareness regarding myopia progression and its prevention.

Mental health and fatigue status of the medical workforce during the COVID-19 outbreak in the Yangzhou city, China

Background When the coronavirus disease 2019 (COVID-19) erupted in Yangzhou, China, at the end of July 2021, medical workers in Yangzhou immediately joined the frontline for the fight against the pandemic. This study aimed to identify the mental health and fatigue experienced by the medical workers in Yangzhou during the COVID-19 outbreak. Methods We included 233 medical workers who participated in the front-line work for more than 1 month through the questionnaire, including doctors, nurses, medical technicians and medical students. The generalized anxiety disorder-7 (GAD-7), patient health questionnaire-9 (PHQ-9), and Fatigue self-assessment scale (FSAS) were administered to the participants and their responses were evaluated. Results A total of 233 eligible questionnaires were received. Among them, 130 people (57.08%) were probably anxious and 141 (60.52%) people were clinically depressed. Poor sleep was considered an independent risk factor for anxiety (OR = 7.164, 95% CI: 3.365 15.251, p = 0.000) and depression (OR = 6.899, 95% CI: 3.392 14.030, p = 0.000). A high PHQ-9 score was considered an independent risk factor for general fatigue (OR = 1.697, 95% CI: 1.481 1.944, p = 0.000). Mental fatigue (OR = 1.092, 95% CI: 1.027 1.161, p = 0.005) and fatigue response to sleep/rest (OR = 1.043, 95% CI: 1.011 1.076 p = 0.008) were considered independent risk factors for general fatigue. Conclusion Poor quality of sleep led to probable anxiety, depression, and general fatigue. Mental fatigue and fatigue response to sleep/rest were independent risk factors for depression, which merits attention for battling COVID-19.

Efficacy, immunogenicity and safety of COVID-19 vaccines in older adults: a systematic review and meta-analysis

Background Older adults are more susceptible to severe health outcomes for coronavirus disease 2019 (COVID-19). Universal vaccination has become a trend, but there are still doubts and research gaps regarding the COVID-19 vaccination in the elderly. This study aimed to investigate the efficacy, immunogenicity, and safety of COVID-19 vaccines in older people aged ≥ 55 years and their influencing factors. Methods Randomized controlled trials from inception to April 9, 2022, were systematically searched in PubMed, EMBASE, the Cochrane Library, and Web of Science. We estimated summary relative risk (RR), rates, or standardized mean difference (SMD) with 95% confidence interval (CI) using random-effects meta-analysis. This study was registered with PROSPERO (CRD42022314456). Results Of the 32 eligible studies, 9, 21, and 25 were analyzed for efficacy, immunogenicity, and safety, respectively. In older adults, vaccination was efficacious against COVID-19 (79.49%, 95% CI: 60.55−89.34), with excellent seroconversion rate (92.64%, 95% CI: 86.77−96.91) and geometric mean titer (GMT) (SMD 3.56, 95% CI: 2.80−4.31) of neutralizing antibodies, and provided a significant protection rate against severe disease (87.01%, 50.80−96.57). Subgroup and meta-regression analyses consistently found vaccine types and the number of doses to be primary influencing factors for efficacy and immunogenicity. Specifically, mRNA vaccines showed the best efficacy (90.72%, 95% CI: 86.82−93.46), consistent with its highest seroconversion rate (98.52%, 95% CI: 93.45−99.98) and GMT (SMD 6.20, 95% CI: 2.02−10.39). Compared to the control groups, vaccination significantly increased the incidence of total adverse events (AEs) (RR 1.59, 95% CI: 1.38−1.83), including most local and systemic AEs, such as pain, fever, chill, etc. For inactivated and DNA vaccines, the incidence of any AEs was similar between vaccination and control groups (p > 0.1), while mRNA vaccines had the highest risk of most AEs (RR range from 1.74 to 7.22). Conclusion COVID-19 vaccines showed acceptable efficacy, immunogenicity and safety in older people, especially providing a high protection rate against severe disease. The mRNA vaccine was the most efficacious, but it is worth surveillance for some AEs it caused. Increased booster coverage in older adults is warranted, and additional studies are urgently required for longer follow-up periods and variant strains.

HMCES protein promotes the replication of porcine epidemic diarrhea virus in Vero cells

Objective: To identify the key host protein that can regulate the replication of porcine epidemic diarrhea virus (PEDV).

The Psychosocial Factors Affecting Chinese Outbound Exchange and Mobility Students’ Academic Performance During COVID-19

COVID-19 has affected every aspect of our life, including economic, social, and academic. Exchange and mobility students face more difficulties overseas, and Chinese students are no exception. However, e-learning has been introduced by institutions in many countries. The present study examines the psychosocial factors affecting the academic performance of Chinese outbound exchange and mobility students during the COVID-19 pandemic. The study surveys about 186 Chinese outbound exchange and mobility students. The present study performs the quantitative data analysis using Partial Least Square Structural Equation Modeling (PLS-SEM) through the Smart PLS software version 3. By confirming the measurement model and structural model assessments, the study finds that personality, social support, and language fluency are psychosocial factors that significantly influence the exchange and mobility students’ academic performance. This study contributes by establishing relationships among psychosocial factors, language fluency and academic performance. Besides, practitioners can be benefitted by understanding students’ psychosocial factors and its relation to academic performance during COVID-19 pandemic.

Whole-process management system of COVID-19 vaccination based on SpringBoot+Vue

After the large-scale vaccination of the coronavirus disease 2019(COVID-19), the traditional manual registration cannot track each vaccine from production to vaccination, as well as the vaccinators. It is easy to cause the lack and omission of registration information, and is not conducive to analyze the data of large-scale vaccine and vaccination. Therefore, this paper uses the front-end and back-end separated patterns with front-end using Vue and Elment-UI technology, and back-end using SpringBoot and Mybatis-Plus framework. It designs and realizes the whole-process management system of novel coronavirus vaccine, from vaccine logistics and vaccine warehousing management, to vaccination and post-vaccination tracking, and then to the forum management of vaccinators. The system aims to achieve "whole-process, traceable" management goal of vaccines. The system is feasible and practical, which can alleviate the problem of manual recording and collation of medical staff in vaccine management, and provide a convenient and information-based vaccination platform for medical staff and vaccinators. In addition, the system can collect the data on the whole process of vaccines and provide strong data support for scientific research work.

How to build a novel burst disease diagnostics for hunting potential infection source: the enlightenment from screening patients via combining viral and antibody testing at the COVID-19 pandemic early stage (preprint)

Purpose: We aimed to summarize the diagnostic strategies used to identify potential patients with COVID-19 among inbound overseas travelers in Xiamen, China.Methods: From October 2020 to December 2020, 180,000 inbound overseas travelers were subjected to government quarantine in Xiamen, China. We evaluated the screening efficiency of combining viral and antibody testing strategies to identify potential patients with COVID-19. Results: The COVID-19 positive rate was 0.17% (306/180,000). There was no difference between the combined PCR and antibody and the PCR testing strategy for screening COVID-19(2.0 [IQR,2.0–3.0] vs. 2.0[IQR,2.0–2.0]; P= 0.175). The results for the combined screening strategy were available 4 days earlier than those for the PCR testing strategy (3.0 [IQR, 3.0–3.0] vs. 7.0[IQR, 7.0–14.0], P=0.000). Compared with the non-key screening population, the key screening population showed less PCR rounds (2.0 [IQR, 2.0–2.0] vs. 2.0[IQR, 2.0–3.0]; (P=0.008) and time (3.0[IQR, 3.0–3.0] vs. 7.0[IQR, 7.0–14.0]; P=0.000) for screening COVID-19. Conclusion: Combining viral and antibody testing strategies is effective; it allows timely identification of the source of COVID-19 infection. Moreover, this strategy can be used for close contacts or sub-close contacts of patients with COVID-19 to reduce the risk of SARS-CoV-2 transmission.

Clinical features and prognosis of COVID-19 patients with metabolic syndrome: A multicenter, retrospective study Características clínicas y pronóstico de los pacientes con COVID-19 y síndrome metabólico: un estudio multicéntrico y retrospectivo

Background Few studies have investigated the impacts of metabolic syndrome (MS) on coronavirus disease 2019 (COVID-19). We described the clinical features and prognosis of confirmed COVID-19 patients with MS during hospitalization and after discharge. Methods Two hundred and thirty-three COVID-19 patients from the hospitals in 8 cities of Jiangsu, China were retrospectively included. Clinical characteristics of COVID-19 patients were described and risk factors of severe illness were analyzed by logistic regression analysis. Results Forty-five (19.3%) of 233 COVID-19 patients had MS. The median age of COVID-19 patients with MS was significantly higher than non-MS patients (53.0 years vs. 46.0 years, P = 0.004). There were no significant differences of clinical symptoms, abnormal chest CT images, and treatment drugs between two groups. More patients with MS had severe illness (33.3% vs. 6.4%, P < 0.001) and critical illness (4.4% vs. 0.5%, P = 0.037) than non-MS patients. The proportions of respiratory failure and acute respiratory distress syndrome in MS patients were also higher than non-MS patients during hospitalization. Multivariate analysis showed that concurrent MS (odds ratio [OR] 7.668, 95% confidence interval [CI] 3.062–19.201, P < 0.001) and lymphopenia (OR 3.315, 95% CI 1.306–8.411, P = 0.012) were independent risk factors of severe illness of COVID-19. At a median follow-up of 28 days after discharge, bilateral pneumonia was found in 95.2% of MS patients, while only 54.7% of non-MS patients presented bilateral pneumonia. Conclusions 19.3% of COVID-19 patients had MS in our study. COVID-19 patients with MS are more likely to develop severe complications and have worse prognosis. More attention should be paid to COVID-19 patients with MS.

Water Transmission Increases the Intensity of COVID-19 Outbreaks

India suffered from a devastating 2021 spring outbreak of coronavirus disease 2019 (COVID-19), surpassing any other outbreaks before. However, the reason for the acceleration of the outbreak in India is still unknown. We describe the statistical characteristics of infected patients from the first case in India to June 2021, and trace the causes of the two outbreaks in a complete way, combined with data on natural disasters, environmental pollution and population movements etc. We found that water-to-human transmission accelerates COVID-19 spreading. The transmission rate is 382% higher than the human-to-human transmission rate during the 2020 summer outbreak in India. When syndrome coronavirus 2 (SARS-CoV-2) enters the human body directly through the water-oral transmission pathway, virus particles and nitrogen salt in the water accelerate viral infection and mutation rates in the gastrointestinal tract. Based on the results of the attribution analysis, without the current effective interventions, India could have experienced a third outbreak during the monsoon season this year, which would have increased the severity of the disaster and led to a South Asian economic crisis.

Implementation of Cloud Computing Protocol in E-Learning for Future Wireless Systems

Schooling system is rapidly shifting according to time. The 4G and 5G machineries are engineered to work flawlessly in heterogeneous platforms unlike 2G, 3G, and 4G wireless networks. New educational techniques are introduced for different environmental needs and E-learning, which is getting popular around the world, and wireless networking plays the vital role in it. E-learning is the requirement of every educational institute. There are a number of problems in the existing prototypes which need to be addressed and improved. This study provides the prototype for E-learning to make the higher education system more efficient. Especially, for the students who need distance learning and an online learning system, this research proposes a user-friendly cloud network infrastructure environment. Machine learning and cloud have strong relation in cloud computing;we store big amount of customer data but to analyze the data and create chatbots, we need machine learning algorithms. We need to enhance the existing prototype for the betterment of the higher education system in rural areas such a time of this COVID-19 pandemic. For this purpose, the existing prototype is critically examined. To achieve this factor why and how E-learning is familiar to the students of rural areas in developing countries, it was analyzed, as the method of education using a platform and interpreting the results. The researcher tried to discover the reason why E-learning is not being applied in higher education. Furthermore, attempts were made to change the existing model by adding the component “Cloud-based structure” that complements and fits the environment of the education system and benefits the long-term sustainability of higher education.