The practice of drug emergency supply in China from a policy mix perspective (preprint)

Background This study aims to analyze relevant policy texts, explore and determine the focal points and inadequacies of the Chinese government in guaranteeing supplies of medicines, and provide advice on how to make better policies about drug supply when public health emergencies occur.Methods We selected 559 documents that guided the support of drug supply during emergencies issued by governments at both the national and provincial levels from December 1, 2019, to February 28, 2023. In addition, we developed a four-dimensional analysis framework of the issuing agency, issuing period, policy tools, and drug supply chain to analyze specific policy items, determine their basic characteristics, and quantitatively analyze them from a policy mix perspective.Results The analysis using policy tools showed that the national government tended to call on stakeholders in all aspects of drug supply to fulfil their responsibilities, and both national and provincial governments tended to use incentive tools, such as opening up urgent drug supply tracks and applying financial incentives to promote drug supply. However, managing stakeholders’ behaviors in drug supply and the capacity building to guarantee drug supply are still lacking and require improvement. From the perspective of the drug supply chain, the national government has paid much attention to the distribution of drugs, whereas attention to the supply of drug substances has been lacking. As various stages of the COVID-19 pandemic, the number of policies related to drug supply increased slowly after a surge at the beginning of the pandemic and then rapidly decreased. From the policy mix perspective, the analysis showed that incentives were lacking in drug research and development, and capacity building was not discussed much in the drug manufacturing process.Conclusions We suggest enhancing the complementarity and cohesion of the policy content issued by national and provincial governments, strengthening the coordination and connection between policymaking bodies, optimizing the internal structure of policy tools, improving the performance of various policy strategies, and using appropriate policy tools to create policies suited to various stages of emergencies and drug supply chains.

Anxiety and depression among epilepsy patients in low-risk areas for COVID-19 in the northern part of Guizhou Province, China, during the COVID-19 pandemic

BackgroundThis study was aimed to investigate whether patients with epilepsy (PWE) have higher depression and anxiety levels than the normal population in low-risk areas for coronavirus disease 2019 (COVID-19) in the northern part of Guizhou Province, China, during the COVID-19 epidemic, to evaluate their knowledge on COVID-19, and to analyze related factors for the psychological distress of PWE at this special time.MethodsThe survey was conducted online from February 28, 2020 to March 7, 2020 via a questionnaire. PWE from the outpatient clinic of epilepsy of the Affiliated Hospital of Zunyi Medical University, and healthy people matched for age and sex, participated in this study. Mental health was assessed via a generalized anxiety self-rating scale (GAD-7) and the self-rating depression scale (PHQ-9). The knowledge of COVID-19 in both groups was investigated.ResultsThere were no significant differences in the general demographics between the PWE and healthy control groups. The scores of PHQ-9 (P < 0.01) and GAD-7 (P < 0.001) were higher in the PWE group than in the healthy group. There was a significant difference in the proportions of respondents with different severities of depression and anxiety, between the two groups, which revealed significantly higher degree of depression and anxiety in PWE than in healthy people (P = 0, P = 0). Overwhelming awareness and stressful concerns for the pandemic and female patients with epilepsy were key factors that affect the level of anxiety and depression in PWE. Further, the PWE had less accurate knowledge of COVID-19 than healthy people (P < 0.001). There was no statistically significant difference between the two groups in the knowledge of virus transmission route, incubation period, susceptible population, transmission speed, clinical characteristics, and isolation measures on COVID-19 (P > 0.05). PWE knew less about some of the prevention and control measures of COVID-19 than healthy people.ConclusionsDuring the COVID-19 epidemic, excessive attention to the epidemic and the female sex are factors associated with anxiety and depression in PWE, even in low-risk areas.

Development of a universal real-time RT-PCR assay for detection of pan-SARS-coronaviruses with an RNA-based internal control.

The current pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exemplifies the critical need for rapid diagnostic assays to prompt intensified virological monitoring both in human and wild animal populations. To date, there are no clinical validated assays for pan-SARS-coronavirus (pan-SARS-CoV) detection. Here, we suggest an innovative primer design strategy for the diagnosis of pan-SARS-CoVs targeting the envelope (E) gene using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Furthermore, we developed a new primer-probe set targeting human ß2-microglobulin (B2M) as an RNA-based internal control for process efficacy. The universal RT-qPCR assay demonstrated no false-positive amplifications with other human coronaviruses or 20 common respiratory viruses, and its limit of detection (LOD) was 159.16 copies/ml at 95% detection probability. In clinical validation, the assay delivered 100% sensitive results in the detection of SARS-CoV-2-positive oropharyngeal samples (n = 120), including three variants of concern (Wuhan, Delta, and Omicron). Taken together, this universal RT-qPCR assay provides a highly sensitive, robust, and rapid detection of SARS-CoV-1, SARS-CoV-2, and animal-derived SARS-related CoVs.

Cryo-EM structure of SARS-CoV-2 postfusion spike in membrane.

The entry of SARS-CoV-2 into host cells depends on the refolding of the virus-encoded spike protein from a prefusion conformation, which is metastable after cleavage, to a lower-energy stable postfusion conformation1,2. This transition overcomes kinetic barriers for fusion of viral and target cell membranes3,4. Here we report a cryogenic electron microscopy (cryo-EM) structure of the intact postfusion spike in a lipid bilayer that represents the single-membrane product of the fusion reaction. The structure provides structural definition of the functionally critical membrane-interacting segments, including the fusion peptide and transmembrane anchor. The internal fusion peptide forms a hairpin-like wedge that spans almost the entire lipid bilayer and the transmembrane segment wraps around the fusion peptide at the last stage of membrane fusion. These results advance our understanding of the spike protein in a membrane environment and may guide development of intervention strategies.

Precise modification of the surface charge of antigen enhances vaccine immunogenicity.

Aluminum (alum) adjuvant is the most extensively used protein subunit vaccine adjuvant, and its effectiveness and safety have been widely recognized. The surface charge of the antigen determines its electrostatic adsorption to alum adjuvant, which directly affects the immune efficacy of the protein vaccine. In our study, we precisely modified its surface charge by inserting charged amino acids into the flexible region of the SARS-CoV-2 receptor-binding domain (RBD), achieving electrostatic adsorption and a site-specific anchor between the immunogen and alum adjuvant. This innovative strategy extended the bioavailability of the RBD and directionally displayed the neutralizing epitopes, thereby significantly enhancing humoral and cellular immunity. Furthermore, the required dose of antigen and alum adjuvant was greatly reduced, which improved the safety and accessibility of the protein subunit vaccine. On this basis, the wide applicability of this novel strategy to a series of representative pathogen antigens such as SARS-RBD, MERS-RBD, Mpox-M1, MenB-fHbp, and Tularemia-Tul4 was further confirmed. Charge modification of antigens provides a straightforward approach for antigenicity optimization of alum-adjuvanted vaccines, which has great potential to be adopted as a global defense against infectious diseases.

Detecting nanoparticles by "listening".

In the macroscopic world, we can obtain some important information through the vibration of objects, that is, listening to the sound. Likewise, we can also get some information of the nanoparticles that we want to know by the means of "listening" in the microscopic world. In this review, we will introduce two sensing methods (cavity optomechanical sensing and surface-enhanced Raman scattering sensing) which can be used to detect the nanoparticles. The cavity optomechanical systems are mainly used to detect sub-gigahertz nanoparticle or cavity vibrations, while surface-enhanced Raman scattering is a well-known technique to detect molecular vibrations whose frequency generally exceeds terahertz. Therefore, the vibrational information of nanoparticles from low-frequency to high-frequency could be obtained by these two methods. The size of the viruses is at the nanoscale and we can regard it as a kind of nanoparticles. Rapid and ultrasensitive detection of the viruses is the key strategies to break the spread of the viruses in the community. Cavity optomechanical sensing enables rapid, ultrasensitive detection of nanoparticles through the interaction of light and mechanical oscillators and surface-enhanced Raman scattering is an attractive qualitatively analytical technique for chemical sensing and biomedical applications, which has been used to detect the SARS-CoV-2 infected. Hence, investigation in these two fields is of vital importance in preventing the spread of the virus from affecting human's life and health.

Mediating effect of mindfulness level on the relationship between marital quality and postpartum depression among primiparas.

BACKGROUND: Postpartum depression refers to a depressive episode or depressive symptoms up to 12 mo after delivery. Trait mindfulness has presented a protective factor for postpartum depressive symptoms and proved efficient in improving relationship satisfaction among couples. AIM: To investigate the correlations among mindfulness, marital quality, anxiety, and depression in a large city in western China during the post-corona virus infectious disease-2019 era and determine whether trait mindfulness mediates the relationship between marital quality and postpartum anxiety and depression among primiparas. METHODS: A cross-sectional study was conducted. The self-administered questionnaire was submitted online through smartphones. The levels of mindfulness, anxiety, depression, and marital quality were respectively investigated by the mindful attention awareness scale (MAAS), the self-rating anxiety scale (SAS), the self-rating depression scale (SDS), and the marriage perception scale (MPS) in these enrolled Han and Tujia primiparas. RESULTS: No statistical significance was observed in the prevalence of postpartum anxiety and depression, nor scores of MAAS and MPS-Total in different regions or ethnicities (P > 0.05). However, MPS-Marital interaction (P < 0.05), MPS-Family relationship (MPS-FR) (P < 0.01), and MPS-Marital conflict (MPS-MC) (P < 0.01) scores of urban primiparas were higher than those of rural primiparas. The MPS-MC score of Han primiparas was higher than that of Tujia primiparas (P < 0.05). Negative correlations were observed between MAAS and SAS (r = -0.457, P < 0.01), and MAAS and SDS (r = -0.439, P < 0.01). SAS has revealed a highly positive correlation with SDS (r = 0.720, P < 0.01) and a weak negative correlation with MPS (r = -0.200, P < 0.05). Besides, a weak negative correlation was observed between MAAS and MPS-MC (r = -0.184, P < 0.05), and a weak positive correlation was noticed between SAS and MPS-MC (r = -0.225, P < 0.01). Mediation analysis demonstrated a full mediation effect of mindfulness level on the relationship between MPS-FR and postpartum anxiety (P < 0.05, 95%CI: -0.384 to 0.033), MPS-MC and postpartum anxiety (P < 0.01, 95%CI: 0.027-0.193), MPS-FR and postpartum depression (P < 0.05, 95%CI: -0.365 to 0.031), and MPS-MC and postpartum depression (P < 0.01, 95%CI: 0.022-0.206). CONCLUSION: Mindfulness demonstrates negative correlations with marital conflict, postpartum anxiety and depression, and it may have cross-ethnic and trans-regional characteristics. Although the mindfulness levels have revealed no significant mediating effect between the total score of marital quality and postpartum depression in this study, it demonstrates a full mediation effect on the relationships between family relationships, marital conflict, and postpartum anxiety and depression.

All-in-one microfluidic chip for 30-min quantitative point-of-care-testing of nucleic acids

Nucleic acid testing (NAT) is directly oriented to determining the genetic material of pathogens and is characterized by its high sensitivity and specificity, which are indispensable qualities in disease diagnosis. However, standard laboratory NAT methods require joint testing by highly trained inspectors using multiple instruments in professional laboratories. The entire process requires many manual steps, and the total testing time may range from 3 to 5h, indicating that these methods cannot be used to realize the demands of on-site rapid testing. In this study, we propose a microfluidic chip for the on-site and rapid detection of nucleic acids. We utilize dynamic sealing, ultrasound, and advanced control methods and integrate the entire process of reagent pre-storage, extraction, Real-time Quantitative polymerase chain reaction (qPCR), and fluorescence detection. The sensitivity of this system is in line with current clinical standards, and the nucleic acid quantification process is completed fully automated within 30min. Compared with conventional microfluidic chips, the proposed system has the advantages of high integration, low cost, and it may be produced at a high volume. Moreover, it can be used in a wide range of screening cases in the context of the COVID-19 pandemic and exhibits broad clinical application prospects.

Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019

Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance.

Does Preoperative Hookwire Localization Influence Postoperative Acute and Chronic Pain After Video-Assisted Thoracoscopic Surgery: A Prospective Cohort Study.

Purpose: This study aimed to investigate whether preoperative computerized tomography-guided hookwire localization-associated pain could affect acute and chronic postsurgical pain (CPSP) in patients undergoing video-assisted thoracoscopic surgery (VATS). Methods: We enrolled 161 adult patients who underwent elective VATS; sixty-nine patients experienced hookwire localization (Group A) and 69 did not (Group B). Group A was further subdivided into the multiple localization group (n=35, Group Amultiple) and the single localization group (n=34, Group Asingle) according to the number of hookwires. The numerical rating scale (NRS) was used preoperatively, during recovery at the post-anesthesia care unit (PACU), and the first two days, 3 and 6 months postoperatively. Furthermore, multivariate regression analysis was used to identify the risk factors associated with CPSP. The postoperative adverse events, length of hospital stay, and satisfaction in pain management were also recorded. Results: The incidence and severity of acute postoperative pain were similar between Group A and Group B (p > 0.05). The incidence (56.5% vs 30.4%, p = 0.002) and the NRS scores (2.0 [2.0-3.0] vs 1.0 [1.0-2.0], p = 0.011) for CPSP were significantly higher in Group A than in Group B at 3 months postoperatively. On subgroup analysis, compared with Group Asingle, the intensity of CPSP (2.0 [2.0-3.0] vs 2.0 [1.0-2.0], p = 0.005) in Group Amultiple was slightly higher at 3 months postoperatively. Conversely, the CPSP incidence (60.0% vs 29.4%, p = 0.011) was significantly higher at 6 months postoperatively in Group Amultiple. The multivariate regression analysis further validated hookwire localization as a risk factor for CPSP (odds ratio: 6.199, 95% confidence interval 2.049-18.749, p = 0.001). Patient satisfaction relating to pain management at 3 months postoperatively was lower in Group A (p = 0.034). Conclusion: The preoperative pain stress of hookwire localization increased the incidence and intensity of CPSP rather than acute pain at 3 months postoperatively, especially in patients with multiple hookwires.

On the ramifications of airspace bans in aero-political conflicts: Towards a country importance ranking.

The aviation industry is facing highly volatile developments in the recent years: Following a steady growth phase with prosperous projections, the COVID-19 pandemic has hit the aviation system rather hard. While having gradually entered a recovery process in the years 2021 and 2022, with load factors close to those in the year 2019, the airspace bans between Russia, Europe, and other regions in the world, as part of the ongoing conflict centered around Russia and Ukraine, threaten the orderly operation of flights. This study explores the byproducts and potential impact of airspace bans on the aviation system and its stakeholders, by deriving a ranking of country importance and how they have the potential to influence our aviation system. While being rooted in the analysis of the Russian-Ukrainian conflict, our framework is built up in a generic way and computes an overall country importance metric. We believe that our study contributes to the better understanding of the consequences airspace bans have on our society and the severe needs for effective policies and regulations of such emerging forms of conflict resolution.

Relationship between covid-pandemic anxiety and sleep disorder with menstrual disorders among female medical workers.

BACKGROUND: It has been more than 2 years since the 2019 novel coronavirus disease (COVID-19) pandemic destabilized the world, adversely affecting not only physical health, but also mental health. During this time, frontline medical workers were at a greater health risk, especially female medical workers. Changes or abnormalities in the menstrual cycle-an important indicator of women's health-may jeopardize female reproductive functioning. Considering that emotional health and sleep status may be related to the menstrual cycle, this study aimed to investigate the association between menstrual cycle changes, anxiety, sleep dysfunction, and other factors among female medical workers during the COVID-19 pandemic. METHODS: A cross-sectional survey was conducted by distributing online questionnaires to female medical workers in China from February to May 2022. The study included 160 women aged 18-45 years old. The questionnaires covered data related to the participants' sociodemographic characteristics, medical and reproductive history, and lifestyle. The Rating Scale for Clinical Manifestations of Menopathy (SCMM), Self-Rating Anxiety Scale (SAS), and Sleep Dysfunction Rating Scale (SDRS) were utilized. Data were analyzed using chi-square tests, t-tests, and linear regression analysis. RESULTS: A total of 160 female medical staff were randomly selected in this research, of whom seven scored less than 3 points, 85 scored 3-11 points, and 68 scored more than 11 points on the total score of the SCMM. Compared to pre-pandemic scores, scores of dizziness and tinnitus were significantly higher during the COVID-19 pandemic. Scores corresponding to the following clinical symptoms were also higher during the pandemic: Menopathy, including hypaphrodisia, dim complexion, abnormal urination, languidness, dim menstruation, thin menstruation, dysmenorrhea, and empty or saggy lower abdomen (p < 0.05). However, pre-pandemic scores of vaginal bleeding quantity were significantly higher than those found during the COVID-19 pandemic (p < 0.05). Scores of vaginal bleeding quantity were significantly lower in cabin hospitals than other types of hospitals, and a similar finding was observed for vaginal bleeding duration (all p < 0.05). Moreover, the findings of the univariable and multivariable linear regression analysis revealed a link between consistent exercise, the underlying illness, the SDRS score, the SAS score, and the total score of SCMM (p < 0.05). CONCLUSIONS: In this study, we found that menstruation in female medical workers was affected by the COVID-19 pandemic. Furthermore, regular exercise and good physical condition were protective factors, while anxiety and insomnia were risk factors for menstrual abnormalities.

Nanotechnology-based diagnostic methods for coronavirus: From nucleic acid extraction to amplification.

The recent emergence of human coronaviruses (CoVs) causing severe acute respiratory syndrome (SARS) is posing a great threat to global public health. Therefore, the rapid and accurate identification of pathogenic viruses plays a vital role in selecting appropriate treatments, saving people's lives and preventing epidemics. Nucleic acids, including deoxyribonucleic acid (DNA) and ribonucleic acid (RNA), are natural biopolymers composed of nucleotides that store, transmit, and express genetic information. Applications of nucleic acid detection range from genotyping and genetic prognostics, to expression profiling and detection of infectious disease. The nucleic acid detection for infectious diseases is widely used, as evidenced by the widespread use of COVID-19 tests for the containment of the pandemic. Nanotechnology influences all medical disciplines and has been considered as an essential tool for novel diagnostics, nanotherapeutics, vaccines, medical imaging, and the utilization of biomaterials for regenerative medicine. In this review, the recent advances in the development of nanotechnology-based diagnostic methods for coronavirus, and their applications in nucleic acid detection are discussed in detail. The techniques for the amplification of nucleic acids are summarized, as well as the use of magnetic nanoparticles for nucleic acid extraction. Besides, current challenges and future prospects are proposed, along with the great potential of nanotechnology for the effective diagnosis of coronavirus.

Awareness and practice of preventive measures among healthcare workers in medical institutions in Beijing during influenza season on the eve of COVID-19 epidemic: A cross-sectional survey.

BACKGROUND: Influenza is an acute respiratory infectious disease caused by the influenza virus, which poses a certain threat to humans due to its short incubation period, fast transmission and strong infectivity. OBJECTIVES: To evaluate the awareness and prevention behavior against influenza among healthcare workers on the eve of the coronavirus disease 2019 (COVID-19) epidemic in Beijing, China. MATERIAL AND METHODS: Using the cross-sectional research design based on the principle of convenience sampling, an online questionnaire survey on the knowledge of flu, vaccination, medical protection behavior, and flu medication was conducted between January and February 2020. Healthcare workers from different healthcare facilities and different job positions in Beijing participated in this survey. RESULTS: A total of 1910 healthcare workers from different medical institutions and jobs were included in the study. The mean age of the participants was 32.69 ±8.72 years (range: 18-64 years). There were significant differences in knowledge about clinical signs about flu and prevention approaches among different age groups, individuals with different work experience and job titles (χ2 = 8.903-32.839; p < 0.05). Personnel with different job positions and education levels differed only in the knowledge about clinical signs of flu and identification of high-risk populations. A multivariate logistic regression analysis revealed that age (odds ratio (OR) = 0.979, 95% confidence interval (95% CI): 0.966-0.992) and education level (OR = 0.736, 95% CI: 0.588-0.921) were risk factors for hand hygiene practices, whereas job position (OR = 1.757, 95% CI: 1.146-2.695) and awareness of high-risk populations (OR = 1.405, 95% CI: 1.096-1.800) were protective factors influencing hand hygiene practices (p < 0.05). The only factor influencing mask wearing was the education level (OR = 0.610, 95% CI: 0.450-0.828). CONCLUSION: The knowledge level and preventive behavior of healthcare workers before the outbreak of COVID-19 has been insufficient.

Process Development of a SARS-CoV-2 Nanoparticle Vaccine

One of the outcomes from the global COVID-19 pandemic caused by SARS-CoV-2 has been an acceleration of development timelines to provide treatments in a timely manner. For example, it has recently been demonstrated that the development of monoclonal antibody therapeutics from vector construction to IND submission can be achieved in five to six months rather than the traditional ten-to-twelve-month timeline using CHO cells [1, 2]. This timeline is predicated on leveraging existing, robust platforms for upstream and downstream processes, analytical methods, and formulation. These platforms also reduce;the requirement for ancillary studies such as cell line stability, or long-term product stability studies. Timeline duration was further reduced by employing a transient cell line for early material supply and using a stable cell pool to manufacture toxicology study materials. The development of non-antibody biologics utilizing traditional biomanufacturing processes in CHO cells within a similar timeline presents additional challenges, such as the lack of platform processes and additional analytical assay development. In this manuscript, we describe the rapid development of a robust and reproducible process for a two-component self-assembling protein nanoparticle vaccine for SARS-CoV-2. Our work has demonstrated a successful academia-industry partnership model that responded to the COVID-19 global pandemic quickly and efficiently and could improve our preparedness for future pandemic threats. Graphical abstract

Multi-weight Susceptible-Infected Model for Predicting COVID-19 in China

The mutant strains of COVID-19 caused a global explosion of infections, including many cities of China. In 2020, a hybrid AI model was proposed by Zheng et al., which accurately predicted the epidemic in Wuhan. As the main part of the hybrid AI model, ISI method makes two important assumptions to avoid over-fitting. However, the assumptions cannot be effectively applied to new mutant strains. In this paper, a more general method, named the multi-weight susceptible-infected model (MSI) is proposed to predict COVID-19 in Chinese Mainland. First, a Gaussian pre-processing method is proposed to solve the problem of data fluctuation based on the quantity consistency of cumulative infection number and the trend consistency of daily infection number. Then, we improve the model from two aspects: changing the grouped multi-parameter strategy to the multi-weight strategy, and removing the restriction of weight distribution of viral infectivity. Experiments on the outbreaks in many places in China from the end of 2021 to May 2022 show that, in China, an individual infected by Delta or Omicron strains of SARS-CoV-2 can infect others within 3-4 days after he/she got infected. Especially, the proposed method effectively predicts the trend of the epidemics in Xi'an, Tianjin, Henan, and Shanghai from December 2021 to May 2022.

Who's Next: Rising Star Prediction via Diffusion of User Interest in Social Networks

Finding items with potential to increase sales is of great importance in online market. In this paper, we propose to study this novel and practical problem: rising star prediction. We call these potential items Rising Star , which implies their ability to rise from low-turnover items to best-sellers in the future. Rising stars can be used to help with unfair recommendation in e-commerce platform, balance supply and demand to benefit the retailers and allocate marketing resources rationally. Although the study of rising star can bring great benefits, it also poses challenges to us. The sales trend of rising star fluctuates sharply in the short-term and exhibits more contingency caused by some external events (e.g., COVID-19 caused increasing purchase of the face mask) than other items, which cannot be solved by existing sales prediction methods. To address above challenges, in this paper, we observe that the presence of rising stars is closely correlated with the early diffusion of user interest in social networks, which is validated in the case of Taocode (an intermediary that diffuses user interest in Taobao). Thus, we propose a novel framework, RiseNet, to incorporate the user interest diffusion process with the item dynamic features to effectively predict rising stars. Specifically, we adopt a coupled mechanism to capture the dynamic interplay between items and user interest, and a special designed GNN based framework to quantify user interest. Our experimental results on large-scale real-world datasets provided by Taobao demonstrate the effectiveness of our proposed framework.

Online technological STEM education project management

With a strong demand for online education and project management in deeper scope and larger scale to better fit COVID-19 pandemic situation, exploring new knowledge of online education to make it more effective became vital with the new challenges of STEM education. To resolve the above problem, this paper focuses on various aspects of online STEM education project management where the Enhanced Noyce Explorers, Scholars, Teachers (E-NEST) three-tiered structure was implemented during the COVID-19 period. Two City University of New York (CUNY) institutions, New York City College of Technology (City Tech) and Borough of Manhattan Community College (BMCC) used the three-tiered structure referred to as Explorer, Scholar and Teacher which incorporated advancements in teaching internships, professional development workshops and mentorships remotely. Built upon the theories of engagement, capacity and continuity (ECC) and team-based learning (TBL), this remote learning model and infrastructure had a positive impact on STEM education and project management. The technological tools utilized included Zoom, Google Meet, Microsoft teams, Blackboard Collaborate Ultra, Skype and SurveyMonkey. The results from qualitative and quantitative data including project evaluation, online surveys and focus group interviews demonstrate that the modified remote learning and management tools were effective. This indicated that the E-NEST model greatly supported student success and faculty in online learning and project management meetings. The E-NEST STEM education project was compared to two other project management models along with the previous NEST curriculum. Faculty emphasized practicing project management proactively and utilized best practices of classroom and time management consistent with Project Management Body of Knowledge (PMBOK) and Project Cycle Management (PCM) guidelines. The comparisons attest that the E-NEST project developed excellent and innovative online platforms for student learning with project management and ECC and TBL applications. Hereafter, this research can be used to constructively develop more online STEM education learning models and platforms and integrate new practice and technology globally. These ideas can contribute to future research that could be applied internationally to STEM education projects in K-12 and higher education institutions.

The Psychological Effect of COVID-19 on Home-Quarantined Nursing Students in China.

Coronavirus disease 2019 (COVID-19) has significantly caused socioeconomic impacts. However, little is known about the psychological effect of COVID-19 on home-quarantined nursing students. The present study aimed to identify the prevalence and major determinants of anxiety, depression and post-traumatic stress symptoms (PTSS) in Chinese nursing students during the COVID-19 pandemic quarantine period. An online survey was conducted on a sample of 6,348 home-quarantined nursing students. Mental health status was assessed by the Generalized Anxiety Disorder 7-Item Scale (GAD-7), the Patient Health Questionnaire 9-Item Scale (PHQ-9) and the Post Traumatic Stress Disorder Check List-Civilian version (PCL-C), respectively. Logistic regression analyses were performed to identify risk factors of anxiety, depression and PTSS. The overall prevalence of anxiety was 34.97%, and the rates of "mild," "moderate," and "severe" anxiety were 26.24, 7.04, and 1.69%, respectively. Depression was detected in 40.22% of the nursing students, and the prevalence of "mild," "moderate," "moderately severe," and "severe" depression was 27.87, 7.18, 4.08, and 1.09%, respectively. The overall prevalence of PTSS was 14.97%, with the prevalence of "mild" and "moderate-to-severe" PTSS reported at 7.04 and 7.93%, respectively. Male gender and insufficient social support were common risk factors for anxiety, depression and PTSS. In conclusion, about one-third, two-fifths, and one-seventh of Chinese nursing students had anxiety, depression and PTSS during the period of home quarantine, respectively. Timely and appropriate psychological interventions for nursing students should be implemented to reduce the psychological harm caused by COVID-19 pandemic.