Urban Public Epidemic Prevention and Control Model Based on Nonlinear Differential Equations

This paper proposes a new epidemiological mathematical model based on the dynamics of urban public epidemic prevention and control model. Then, the nonlinear differential equation of epidemic propagation dynamics is deduced. Secondly, this paper uses the exponential equation to fit the curve, takes three days as the optimal window time, and estimates the turning point of the urban public epidemic. Again, this paper establishes a dynamic model of dynamic experience transfer. Finally, this paper uses the COVID19 example to verify the public epidemic prevention and control problems described in the text. Experimental simulations show that the algorithm can better grasp important epidemiological dynamics.

The effects of personalised mathematic instruction supported by an intelligent tutoring system during the COVID-19 epidemic and the post-epidemic era

It is hard to find an empirical study that examines the online learning or blended learning's effect on school pupils' regular exam performance during the COVID-19 epidemic and afterwards. This study attempts to fill in this research gap. An intelligent tutoring system (ITS) was utilised in mathematics online instruction in many elementary and middle schools in China. It supports individualised teaching and learning and has positive effect on students' learning. Two case studies are introduced to illustrate the system's functions and effects on students' mathematics learning performance. In the first case, a mathematics teacher in a junior high school provided the students with differentiated assignments during the epidemic. In the second case, a teacher in a primary school utilised the ITS to implement blended learning after the epidemic. Quasi-experiments were conducted and the regular examination's data analysis result shows that the treatment group outperformed the control group.

Stress and Well-Being during the COVID-19 Pandemic in China: The Moderating Role of Communication

To examine how and when stress affect individual (i.e., psychological health) and relationship well-being (i.e., marital satisfaction) during the COVID-19 pandemic, the present study used latent profile analysis to identify the typologies of communication and investigated whether the typologies would moderate the associations between stress and individual and relationship well-being in a sample of adults living in China (N = 3,354). Results revealed that (a) stress was negatively associated with psychological health and marital satisfaction during the COVID-19 pandemic and that its effect on psychological health was greater than that on marital satisfaction and (b) four profiles were identified: low communication (10%), moderate communication (43%), positive communication (43%), and contradictory communication (5%). Further, the typologies moderated the effects of stress on psychological health and marital satisfaction, but the patterns of moderation differed in psychological health and marital satisfaction. © 2022 Taylor & Francis Group, LLC.

Modeling and Reviewing Analysis of the COVID-19 Epidemic in Algeria with Diagnostic Shadow

In this paper, we formulate a special epidemic dynamic model to describe the transmission of COVID-19 in Algeria. We derive the threshold parameter con-trol reproduction number (R0c), and present the effective control reproduction number (Rc(t)) as a real-time index for evaluating the epidemic under different control strate-gies. Due to the limitation of the reported data, we redefine the number of accumu-lative confirmed cases with diagnostic shadow and then use the processed data to do the optimal numerical simulations. According to the control measures, we divide the whole research period into six stages. And then the corresponding medical resource estimations and the average effective control reproduction numbers for each stage are given. Meanwhile, we use the parameter values which are obtained from the optimal numerical simulations to forecast the whole epidemic tendency under different control strategies.

Mixing patterns and the spread of pandemics

Integrating social mixing data into epidemic models can help policy makers better understand epidemic spread. However, empirical mixing data might not be immediately available in most populations. In a recent work, a network model methodology is proposed to construct micro-level social mixing structure when empirical data are not available.

Progress in research on human coronavirus and relevant vaccines

Coronaviruses (CoVs) are positive-sense and single-strand RNA viruses which have an extensive range of natural hosts and cause respiratory, gastrointestinal, hepatic, renal and neurological diseases of varying severities in livestock, birds and humans.Seven human coronaviruses (HCoVs) have been discovered, of which severe acute respiratory syndrome coronavirus (SAKSCoV), Middle East respiratory snydrome coronavirus (MERSCoV) and 2019 novel coronavirus (2019-nCov) may cause severe fatal pneumonia and have posed a global threat to public health.This paper reviews the progress in research on pathogenicity and vaccines of HCoV. Copyright © 2022 Changchun Institute of Biological Products. All rights reserved.

Analysis of public information demand during the COVID-19 pandemic based on four-stage crisis model

At the end of 2019, the outbreak of the Corona Virus Disease 2019 (COVID-19) became a grave global public health emergency. At that time, there was a lack of information about this virus. Nowadays, social media has become the main source for the public to obtain information, especially during the COVID-19 pandemic. Therefore, in order to know about the public of information demand after the outbreak, the research collects the data of hot search on Sina-microblog from 1 January 2020 to 30 December 2020, and then conducts data mining by combining text processing with topic models. Then we show the topics mined in the knowledge map. The results show that with the outbreak of the COVID-19, people's attention to the topics related to the epidemic reaches the maximum in a short time, and then decreases with fluctuation, but does not disappear immediately. Some topics fluctuate violently due to the emergence of special events. The results conformed to the four-stage crisis model in the emergency management. We analyze the role of social media in four stages for this. The findings of this study could help the government and emergency agencies to better understand the main aspects, which the public's concern about COVID-19, and accelerate public opinion guidance and emotional reassurance.

Universal SARS-CoV-2 Testing Among Obstetrical Patients (UNIVERSE-OB) in Ottawa, Canada

Objectives: Universal testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within birthing units is an effective strategy to contain infection and estimate community prevalence. Given the high-prevalence of COVID-19 cases in Ontario, the objective of this study was to determine the prevalence of active and recovered SARS-CoV-2 infection among pregnant individuals in Ottawa through universal SARS-CoV-2 and serology testing. Methods: From October 19th to November 27th, 2020, pregnant individuals admitted to triage assessment units at The Ottawa Hospital (TOH) were consented for SARS-CoV-2 testing. Swab and serology samples were analyzed using digital droplet polymerase chain reaction (ddPCR) and enzyme-linked immunosorbent assays, respectively. SARS-CoV-2 seropositivity was defined as a positive result for immunoglobulin (Ig) G, either alone or in combination with IgM and/or IgA. Results: From the 395 enrolled participants, 284 swab and 353 serology samples were collected. We found that 18 of 395 (4.6%) participants had evidence of SARS-CoV-2 exposure: 2/284 (0.70%) were positive for SARS-CoV-2 and 16/353 (4.5%) were positive for anti–SARS-CoV-2 IgG. Seropositive participants were similar to seronegative participants in terms of demographics, clinical characteristics, and pregnancy outcomes. Conclusions: The prevalence of SARS-CoV-2 ddPCR positivity and seropositivity in the obstetrical population at TOH was 0.70% and 4.5%, respectively in the fall of 2020. According to local public health data, the infection rate peaked at 0.6% during the study time period. Universal SARS-CoV-2 testing programs may help approximate community prevalence, however, justification of this strategy depends on testing capabilities and the local context of COVID-19 infection. Keywords: pregnancy;COVID-19;SARS-CoV-2;universal testing;seroprevalence

[The relationship between adenovirus infection and severe acute hepatitis of unknown etiology].

Adenovirus infection can occur in all regions or countries of the world, with no obvious seasonality, but pandemics mostly occur in winter or early spring. Adenovirus infection is self-limited among immunocompetent host with supportive care, however fatal infection can occur among immunocompromised patients, mainly affecting respiratory, gastrointestinal tract and adjunctiva and very rarely causing hepatitis, cholecystitis, pancreatitis, hemorrhagic cystitis, myocarditis, meningitis or encephalitis. Adenovirus hepatitis mainly occur in malignant tumors or organ transplantation patients, but acute severe hepatitis can occur even in immunocompetent children or adults. On 5 April 2022, WHO was notified of 10 cases of severe acute hepatitis of unknown etiology in children. As of 21 April 2022, at least 169 cases of acute hepatitis of unknown origin have been reported from 12 countries (including 11 WHO European Region countries and the United States). Adenovirus has been detected in at least 74 cases; SARS-CoV-2 was identified in 20 cases of those that were tested. Furthermore, 19 were detected with a SARS-CoV-2 and adenovirus co-infection. At present, the etiology has not been fully elucidated. The leading hypotheses center around adenovirus, and the relationship with SARS-CoV-2 needs to be further ruled out.

Effects of physical exercise on mental health and general self-efficacy of city residents in COVID-19

The purpose of this study was to investigate the relationship and impact of residents' self-efficacy and mental health in the context of COVID-19. A quantitative research approach is used in this study. This study investigated residents with a general self-efficacy questionnaire to explore the predictive effect of self-efficacy on mental health. Therefore, a questionnaires survey is employed in this study to collect primary data. While data collection, the cross-sectional research design was used, and data analysis was carried out using a statistical tool. There was a significant negative association between the epidemic's risk perception and the score of the SCL.90. The standardized burden of understanding the epidemic on its latent variables was more than 0.65 in the measurement model, indicating that the 90 percent confidence intervals for the three mediation paths did not include 0, confirming the mediation effect's establishment. This study reveals the relationship between self-efficacy and mental health and its mechanism of action, inspiring the maintenance of residents' mental health during the period of the new crown. It is concluded that there was a significant positive correlation between self-efficacy and understanding of the epidemic situation. © 2022 Sociedad Revista de Psicologia del Deporte. All rights reserved.

[Investigation of contamination of SARS-CoV-2 in imported frozen seafood from a foreign cargo ship and risk factors for infection in stevedores in Qingdao].

Objective: To investigate the contamination status of SARS-CoV-2 in imported frozen seafood from a Russia cargo ship in Qingdao and to analyze the risk factors for infection in local stevedores. Methods: The method of "two-stage, full coverage and mixed sampling" was used to collect the seafood packaging samples for the nucleic acid detection of SARS-CoV-2 by real-time fluorescent quantitative RT-PCR. A unified questionnaire was designed to investigate 71 stevedores in two shifts through telephone interview. The stevedores were divided into two groups, with 23 in the shit with two infections was group A and 48 in the shift without infection was group B. Software Epi Info7.2 was used to identify the risk factors for SARS-CoV-2 infections in the stevedores. Results: In the frozen seafood from a Russia cargo ship, the total positive rate of SARS-CoV-2 nucleic acid in the frozen seafood was 11.53% (106/919). The positive rate of SARS-CoV-2 nucleic acid in the frozen seafood unloaded by group A (14.29%,70/490) was significantly higher than that in the frozen seafood unloaded by group B (8.39%,36/429)(χ2=7.79,P=0.01) and the viral loads detected in the frozen seafood unloaded by group A were higher than those detected in the frozen seafood unloaded by group B. The scores of personal protection and behaviors in the stevedores in group A were significantly lower than those in group B (P<0.05), and toilet use, smoking and improper hand washing before meals were the risk factors for the infection. Conclusions: The imported frozen seafood was contaminated by SARS-CoV-2 and the contamination distribution was uneven. Supervision and management of personal occupational protection and behaviors of workers engaged in imported frozen food transportation should be strengthened. It is suggested that a closed-loop monitoring and management system for the whole process of "fishing-transport- loading/unloading" should be established by marine fishery authority.

Photocatalysis over MXene-based hybrids: Synthesis, surface chemistry, and interfacial charge kinetics

Two-dimensional (2D) transition metal carbides and/or nitrides (MXenes) are a family of graphene-like 2D materials, with unique layered structures, high mechanical strength, excellent carrier mobility, and outstanding physical and chemical properties. In particular, the work function (Phi) of MXenes and Gibbs free energy of the adsorbed intermediate, such as H* (;Delta G(H)(*);), can be regulated by their surface adsorption groups (-OH, -O, and -F), enabling the applications in the field of photocatalysis. This article systematically summarizes the recent advances of synthetic routes of MXene-based photocatalysts and discusses the interfacial charge kinetics and photogenerated charge transfer mechanism of MXene-based photocatalysts. Furthermore, major challenges and further research trends of MXene-based photocatalysts are also presented. (c) 2021 Author(s).

The Customized Mathematic Instruction Supported by an Intelligent Tutoring System and Its Effect During the COVID-19 Epidemic

To cope with the covid-19 epidemic challenge for school education, many researchers have conducted studies from different point of views. However, it is hard to find empirical study to examine the online learning’s effect on school pupils’ performance represented by regular exams. This study attempts to fill in this research gap. An intelligent tutoring system, Lexue 100 was utilized in mathematics online instruction during the COVID-19 epidemic outbreak time in a junior high school in Shandong Province China. Supported by this system, the teacher provided the students with differentiated assignments including class assignment, group assignment and individual assignment, as well as error sets. Those assignments could be completed before the class, in the class or after the class. A quasi-experiment was conducted to compare the effect of this online learning supported by the individualized assignment with that of uniform assignment to all students. The treatment group and control group had the statistically not significant difference in the regular school exams before the experiment as the pretest. At the end of the experiment, the treatment group performed better than the control group in the mid-term test as the posttest, reaching a statistically significant advantage 6.83% (p < 0.01) and an effect size 0.381. The individualized homework contributed to the performance improvement. Implications for online learning design and limitations are discussed. © 2021, Springer Nature Switzerland AG.

The design, implementation and pilot application of an intelligent online proctoring system for online exams

Purpose: The purpose of this study is to design and implement an intelligent online proctoring system (IOPS) by using the advantage of artificial intelligence technology in order to monitor the online exam, which is urgently needed in online learning settings worldwide. As a pilot application, the authors used this system in an authentic university online exam and checked the proctoring result. Design/methodology/approach: The IOPS adopts the B/S (Browser/Server) architecture. The server side is implemented with programming language C and Python and stores the identification data of all examinees and their important behavior change status, including facial expression, eye and mouth movement and speech. The browser side collects and analyzes multimodal data of the examinee writing the online test locally and transfers the examinee’s most important behavior status change data to the server. Real-time face recognition and voice detection are implemented with the support of open-source software. Findings: The system was integrated into a Web-based intelligent tutoring system for school mathematics education. As a pilot application, the system was also used for online proctored exam in an undergraduate seminar in Peking University during the epidemic period in 2020. The recorded log data show that all students concentrated themselves on the exam and did not leave the camera and did not speak. Originality/value: During the epidemic period of the novel coronavirus outbreak, almost all educational institutions in the world use online learning as the best way to maintain the teaching and learning schedule for all students. However, current online instruction platforms lack the function to prevent the learners from cheating in online exams and cannot guarantee the integrity and equality for all examinees as in traditional classroom exams. The literature review shows that the online proctoring system should become an important component of online exams to tackle the growing online cheating problem. Although such proctoring systems have been developed and put on the market, the practical usage of such systems in authentic exams and its effect have not been reported. Those systems are heavyweight and commercial product and cannot be freely used in education. The light-weight IOPS developed by the authors could meet the need for online exam as a stable and practical approach and could contribute to the growing online learning and distance learning. © 2021, Emerald Publishing Limited.

The impact of imported cases on the control of COVID-19 in China

To control the outbreak of COVID-19, the Chinese government has been carrying on a series of joint prevention and control measures. Current domestic situation shows an encouraging sign of improvement. However, the situation abroad is in a serious phase. Therefore, interdicting abroad inputs will be the key point at the next stage. In this paper, we establish a dynamical model incorporating with impulse to describe the transmission of SARS-CoV-2 and analyze the impact of overseas inputs on domestic prevention and control. Considering the imported cases from a typical neighboring country, we study the impacts of control measures under three different levels of control strategy. The simulations for the provinces with risk are given. The numerical experiments show that the current epidemic prevention policy can control the development of the epidemic well in the areas with less imported population;for the provinces with more imported population from the epidemic area, the effective screening and necessary isolation at immigration ports are crucial for preventing the further outbreak caused by imported cases. © 2021, Science China Press. All right reserved.

Mental health of college students of different specialties during the epidemic of coronavirus disease 2019

Objective: To investigate the mental health status of college students of different specialties during the outbreak of coronavirus disease 2019 (COVID-19) so as to provide the basis for college students' mental health assessment and psychological crisis intervention. Methods: The survey conducted among students of a university in Xi'an was composed of common questionnaires like the Self-rating Anxiety Scale (SAS) and Self-Depression Rating Scale (SDS), and the students' understanding of COVID-19. The differences among students of different specialties were compared by ANOVA and LSD-test. Results: A total of 456 students' questionnaires were collected online, with an effective rate of 93.68%. During the outbreak of the epidemic, the depression score was 42.51±10.65 points while the overall anxiety score was 38.37±7.46 points, which was higher than the Chinese adult norm score. Students of clinical medicine had a higher level of concern over and stress response to COVID-19 than those of other specialties. The average SAS and SDS sores differed significantly between the three groups (P< 0.001 for SAS, and P=0.004 for SDS). Anxiety score reached 36.28±7.25 for students of clinical medicine, 39.75±7.00 for students of specialties related to clinical medicine, and 39.35±7.89 for other non-clinical majored students. The SAS score of clinical students was significantly lower than that of students of specialties related to clinical medicine (P< 0.001) and non-clinical majored students (P=0.001). The SDS scores were significantly higher for clinical medicine related students (P=0.001) and non-clinical majored students (P=0.027) than for clinical students. Conclusion: College students had higher levels of anxiety and depression than the norm score of other adults in China during the epidemic of COVID-19. Compared with students of other specialties, those of clinical medicine were found to have a high level of concern about and stress response to the epidemic of COVID-19, but a lower level of anxiety and depression.

A Multimodal Human-Computer Interaction System and Its Application in Smart Learning Environments

A multimodal human-computer interaction system is composed of the comprehensive usage of various input and output channels. For the information input, apart from the traditional keyboard typing, mouse clicking, screen touching, the latest speech and face recognition technology can be used. For the output, the traditional screen display, the latest speech and facial expression synthesis and gesture generation can be used. After literature review of related works, this paper at first presents such a system, MMISE (Multimodal Interaction System for Education), about its architecture and working mechanism, POOOIIM (Pedagogical Objective Oriented Output, Input and Implementation Mechanism) illustrated with practical examples. Then this paper introduces this system’s pilot applications in the epidemic time of novel coronavirus in 2020. © 2020, Springer Nature Switzerland AG.

Strategies Derived from COVID-19 Outbreak Containment for Improving the Long-term Mechanism of Developing the Community Public Health Team

Background: Community-based containment of COVID-19 outbreak in 2020 in China has revealed that community public health professionals involving in the containment are insufficient and their distribution is uneven,so it is urgently to strengthen and improve the development of community public health(CPH) teams. Objective: To summarize and analyze the main problems in long-term development of CPH teams and community-based COVID-19 containment,and based on this,to develop strategies for improving long-term construction of CPH teams amid COVID-19. Methods We collected the data during February to April 2020 by reviewing the contents of Essential Information of Community Health Professionals in Beijing legally reported to Beijing Municipal Health Commission. We analyzed the trend of changes in the quantity,structure,post attraction and distribution inequality(using Gini coefficient) of incumbent CPH professionals during 10 consecutive years(2010-2019) using descriptive analysis. Results: The annual growth rate of the number of CPH professionals was 5.58%(from 2 139 in 2010 to 3 488 in 2019),which was higher than that of community staff(3.25%) and health professionals(3.26%) in the same period. The average age of CPH professionals was(35.9±10.7) years in 2010,and (37.6±9.4) years in 2019. The proportion of young people(under 30 years old) decreased(χ2=197.252,P<0.001)compared to 2010. In 2010,those with three-year college degree were the majority(41.37%),while in 2019,those with 5-year college degree were the majority(46.33%). The percentage of those with an intermediate or senior professional title increased from 26.60% to 38.27%. The percentage of Beijing natives decreased from 74.10% to 70.99%. The percentage of officially budgeted decreased from 82.89% to 78.21%. Except those retired normally,a total of 1 327 cases flowed out. The number and percentage of cases flowed out increased yearly. Gini coefficients for CPH professionals distribution by the number of population and geography were 0.300 1,and 0.763 6,respectively in 2010,and were 0.222 8,and 0.696 6,respectively in 2019. Conclusion: The number of CPH professionals,as same as the structure of education and professional titles,has been gradually optimized during long-term construction in Beijing. Local government-led community health system can ensure a high level of equity in the distribution of CPH professionals based on population and ensure the effective implementation of epidemic containment and other community public health services.However,some problems have gradually revealed,such as gradually increased average age of CPH professionals,and decreased post attraction,which are worth noting and thinking for the sake of further optimizing the long-term mechanism of developing the CPH team. Copyright © 2020 by the Chinese General Practice.

Privacy-preserving image search (PPIS): Secure classification and searching using convolutional neural network over large-scale encrypted medical images

The real-time sharing and retrieval of medical data, such as medical imaging data, via cloud systems can facilitate timely medical/disease diagnosis, for example during pandemics (e.g., COVID-19). While encryption can be used to ensure that patients’ private and medical information are not accessible by unauthorised individuals, it is challenging for cloud servers to search for and locate encrypted medical images (e.g. those relating to similar medical conditions). In this paper, we propose a novel and practical classification and retrieval method to search for and locate relevant cases over encrypted images. Specifically, we construct a privacy-preserving Convolutional Neural Network (CNN) framework that allows the classification and searching of secure, content-based, large-scale encrypted images (including large-size medical images) with homomorphic encryption. We analyze the security of our proposed method to ensure that no sensitive information from the encrypted images is leaked. Using four real-world datasets (i.e., chest X-Ray images, retinal OCT images, blood cell images, and Caltech101 image set), we evaluate and demonstrate the utility of our privacy-preserving method for searching images performed as well as CNN-based classification and searching of original images. This is an important step towards practical automated clinical diagnoses. © 2020 Elsevier Ltd