[Cross-sectional study on the use of masks among occupational groups with high-risk positions for overseas import and pollution transmission].

Objective: To investigate the wearing of masks and the knowledge of masks among high-risk positions for overseas import and pollution transmission. Methods: From May 14 to 17, 2022, a convenient sampling method was used to conduct an online survey among 963 workers in high-risk positions for overseas import and pollution transmission in Beijing. The behaviors of individual use and wearing masks, the distribution and supervision of the unit, the knowledge of personal mask protection and the subjective feelings of wearing masks were analyzed. The χ(2) test and logistic regression model were used to analyze the influencing factors of the correct selection of masks. Results: The majority of the workers in high-risk positions for overseas import and pollution transmission were male (86.0%, 828/963), age concentration in 18-44 years old (68.2%, 657/963), and the majority of them had college or bachelor degrees (49.4%, 476/963). 79.4%(765/963) of the workers chose the right type of masks, female, 45-59 years old and high school education or above were the risk factors for correct selection of masks (P <0.05). Workers had good behaviors such as wearing/removing masks, but only 10.5% (101/963) could correctly rank the protective effect of different masks. 98.4% (948/963) of the workers believed that their work units had provided masks to their employees, and 99.1% (954/963) and 98.2%(946/963) of them had organized training and supervision on the use of masks, respectively. 47.4%(456/963) of the workers were uncomfortable while wearing masks. Conclusion: The overall selection and use of masks among occupational groups in high-risk positions for overseas import and pollution transmission in China need to be further standardized. It is necessary to strengthen supervision and inspection on the use of masks among occupational groups, and take improvement measures to improve the comfort of wearing masks.

Research hotspots and theme analysis of infection management in operating room based on Nvivo software.

Objective To analyze the research hotspots and theme in the field of infection prevention and control（infection control) management in operating room in recent six years in China, so as to provide reference for further research on infection control management in operating room. Methods The articles related to infection control management in operating room published in China National Knowledge Infrastructure（CNKI), Wanfang and VIP databases from 2015 to 2021 were selected as the research objects, and Nvivo software query, coding and cluster analysis were adopted as the main methods to visually present the research hotspots and theme groups in the field of infection management in operating rooms. Results A total of 128 literatures with 30 high-frequency keywords were included. After free coding, 8 parent nodes, 28 child nodes, 60 secondary nodes and 1 736 coding reference points were formed. Six theme groups had been formed, which were the guidelines for infection control of COVID-19 infection, construction and management of clean operating rooms, management of relevant personnel in operating rooms, management of surgical supplies, operating room environment control, theoretical support and occupational exposure control. Conclusion The research content related to infection control management in operating rooms is becoming increasingly mature, and is constantly improving in line with the development of the times. The research direction and theory are also showing a trend of diversification. In response to the huge challenge of COVID-19 situation, it is supposed to preparing for surgery protection in general hospitals actively, ensure the safety of patients and medical staff, and prevent hospital infection events. (English) [ FROM AUTHOR] 目的 分析国内近6年手术室感染预防和控制(感控)管理领域的研究热点和主题内容, 为手 术室感控管理的进一步研究提供借鉴。方法 选取2015-2021年中国知网、万方和维普等数据库刊出的手术 室感控管理相关内容的期刊论文作为研究对象, 主要采用 Nvivo软件查询、编码、聚类分析等研究方法, 以可视 化方式呈现手术室感控管理领域的研究热点和主题类团。结果 共纳入128篇文献, 30个高频关键词;经自由 编码形成8个树状节点、28个子节点、60个次节点、1736个编码参考点;形成6个主题类团, 分别为新型冠状 病毒(新冠病毒)感染疫情感染防控指引、洁净手术室建设与管理、手术室相关人员管理、手术用品管理、手术室 环境管控、理论支持与职业暴露管控。结论 手术室感控管理相关研究内容日渐成熟, 且紧扣时代发展不断完 善, 研究方向和理论也呈多元化趋势。在应对新冠病毒感染疫情的巨大挑战下积极做好综合医院的手术防护 准备工作, 保障患者和医务人员安全, 防止医院内感染事件的发生。 (Chinese) [ FROM AUTHOR] Copyright of Journal of Modern Medicine & Health is the property of Journal of Modern Medicine & Health and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Overview of Pharmaceutical Strategy for Europe (2020) and enlightenment to China's pharmaceutical field.

Under the background of major innovations and changes in international pharmaceutical technology, the continuous development of informatization and digitalization of drug R & D, technology, and the COVID-19 pandemic, the European Commission (EC) issued the pharmaceutical Strategy for Europe (PSE) at the end of 2020 in order to meet the unfinished clinical needs, stimulate industry innovation, enhance the adaptability of the regulatory system, and consolidate the international status of the EC drug regulatory system. PSE is regarded as the "cornerstone" of European health policy in the next five years, which has important guiding significance for the development and management of European pharmaceutical industry. This paper combs and analyzes the background, development strategic objectives and specific measures of PSE, and puts forward policy suggestions in combination with the actual work of China's epidemic prevention and control and industry development, pharmaceutical scientific supervision and encouraging innovation.Copyright © 2022 by the Author(s).

Spatiotemporal evolution of urban theft crimes and mechanism in the context of regular COVID-19 pandemic prevention and control: A case study of Haining, Zhejiang

Existing studies show that the outbreak of the COVID-19 pandemic has a significant impact on crime occurrences. However, it remains to be empirically examined whether the regular pandemic prevention and control measures in China can significantly affect the spatial patterns of crimes. To fill this gap, this study chosed the central urban area of Haining City in Zhejiang Province, which had taken the regular pandemic prevention and control measures, as the research area. Using standard deviation ellipse and kernel density estimation methods, this study examined the spatiotemporal patterns of theft crimes between February 2018 and July 2021 in the study area. The results show that: 1) While there were no significant changes in the hourly patterns of theft crimes within a day, the monthly number of thefts in the study area decreased by an average of 53% after the outbreak of the COVID-19 pandemic and fluctuated between 100 to 200 thefts per month. The regular COVID-19 pandemic prevention and control measures had a long-term and stable inhibitory effect on the number of theft crimes in Haining City. 2) The intensity and amount of hotspots for theft crimes in the study area decreased significantly during February 2020 and July 2021 when compared with the pre-pandemic period, and the spatial distribution patterns of theft crimes were relatively stable. 3) For the 12 crime hotspots identified for the pre-pandemic period, the monthly number of crimes decreased between 52% and 78% on average after the outbreak while trajectories of their quarterly temporal changes differed significantly. The average crime drop for the 12 hotspot areas were 63%, which was higher than that for the whole study area. 4) Seven crime-control measures were identified among the regular pandemic prevention and control measures based on the routine activity theory and the crime triangle theory. Functional type of place, geographic location, and pre-pandemic local governance ability all played an important role in affecting the actual crime-control effects of the seven regular COVID-19 pandemic prevention and control measures. The results of this study are important for understanding the spatial evolution of crimes under the influence of major public health emergencies and for formulating scientific strategies for crime prevention and control. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.

Analysis of social and psychological factors influencing the treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019.

Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio OR=5.618, 95% confidence interval CI) 2.136-14.776, P0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.

PSYCHOLOGICAL DISTRESS OVER 12 MONTHS POST-DIAGNOSIS IN A NATIONAL EARLY INFLAMMATORY ARTHRITIS COHORT

BackgroundIn inflammatory arthritis patients, the concomitant decline of their mental wellbeing is an increasing concern[1,2]. It is important to not only describe the trajectory of psychological distress in early disease stages, but also understand which clinical outcome measures are most associated with these changes.ObjectivesUsing data from the National Early Inflammatory Arthritis Audit (NEIAA), we assessed trends in psychological wellbeing over 12 months after initial diagnosis and mapped these against clinical outcomes to identify significant associations.MethodsNEIAA collects data from patients referred with suspected early inflammatory arthritis in rheumatology services in England and Wales. We used data provided by 20,472 patients eligible for follow-up (diagnosis of inflammatory arthritis) between May 1st, 2018, and April 1st, 2022. Data items included baseline demographics e.g., age and gender, and clinical variables e.g., rheumatic disease comorbidity index (RDCI), DAS28, and patient reported outcomes.Psychological distress was measured by the sum score of Patient Health Questionnaire Anxiety and Depression Screener (PHQ4ADS). Using mixed effects regression models, we analysed the co-variability of PHQ4ADS with demographic factors and clinical outcomes over 12 months. Time was included as a dummy-coded covariant.ResultsThe analysis included 36% of patients (7,378 out of 20,472) who completed the baseline patient outcome survey. In this cohort, PHQ4ADS scores decreased from a baseline average of 4.7 (CI: [4.6, 4.8]) to 2.62 (CI: [2.5, 2.8]) at 12 months post-diagnosis. The proportion of patients screening positive decreased from 50.0% (CI: [48.9, 51.1]) at baseline to 23.8% (CI: [21.8, 25.9]) at 12 months.At baseline, psychological distress correlated significantly with age, gender, ethnicity, RDCI, prior depression diagnosis, and baseline DAS28 (Figure 1). No significant correlations were found between psychological distress and working diagnosis, seropositivity, or the assessment being recorded after the start of the COVID-19 pandemic. Younger ages were nonlinearly associated with higher distress levels (coefficient per decade: -0.006;p<0.001;CI: [-0.009, -0.003]) (Figure 1a). Distress levels in females were higher than that of males (coefficient: 0.5;p<0.001;CI: [0.4, 0.7]) (Figure 1b). White patients reported lower PHQ4ADS scores compared to non-white patients (coefficient: -0.7;p<0.001;CI: [-1.0, -0.4]) (Figure 1c). Higher distress levels were also associated with higher RDCI (coefficient: 0.2;p<0.001;CI: [0.1, 0.3]) and prior diagnosis of depression (coefficient: 1.8;p<0.001;CI: [1.5, 2.2]) (Figure 1d, 1e). Furthermore, higher baseline DAS28 scores correlated with more severe psychological distress (coefficient: 0.8;p<0.001;CI: [0.7, 0.8]) (Figure 1f).By 12-months, psychological distress decreased significantly overall, which correlated significantly with ethnicity (coefficient: 0.8;p=0.005;CI: [0.3, 1.4]) and baseline DAS28 (coefficient: -0.5;p<0.001;CI: [-0.6, -0.4]). Compared to white patients, the reduction was significantly greater for non-white patients, but the level of distress was no longer different at 12 months (Figure 1c). While those with higher baseline DAS28 showed a greater reduction in psychological distress, the distress levels remained higher at 12 months (Figure 1f).Figure 1.Changes in psychological distress correlated with age, gender, ethnicity, RDCI, prior depression diagnosis, and baseline DAS28.[Figure omitted. See PDF]ConclusionIn this early inflammatory arthritis cohort, mental health burden was high. Age, gender, ethnicity, RDCI, prior depression diagnosis and baseline DAS28 significantly correlated with psychological distress at baseline. Supporting mental health should be a focus of clinical care for this population and it may be beneficial to use an approach that is culturally valid for non-white patients and accounts for multimorbidity.References[1]Euesden, J, et al. Psychosomatic medicine 79.6 (2017): 638.[2]Lwin, MN, et al. Rheumatology and therapy 7.3 (2020): 457-471.AcknowledgementsThe authors would like to thank the Healthcare Quality Improvement Partnership (HQIP) as the commisioner of NEIAA, British Society for Rheumatology as the audit providers, Net Solving as the audit platform developers, and the Wellcome Trust (ST12406) for funding to support L.Z..Disclosure of InterestsLucy Zhao: None declared, James Galloway Speakers bureau: Has received honoraria from AbbVie Celgene, Chugai, Gillead, Janssen, Eli Lilly, Pfizer, Roche, and UCB, Jo Ledingham: None declared, Sarah Gallagher: None declared, Neena Garnavos: None declared, Paul Amlani-Hatcher: None declared, Nicky Wilson: None declared, Lewis Carpenter Consultant of: Statistical consultancy for Pfizer, Kirsty Bannister: None declared, Sam Norton Speakers bureau: Has received honoraria from Janssen and Pfizer.

A Dynamic-Static Dual Input Deep Neural Network Algorithm for Diagnosing COVID-19 by Cough

The COVID-19 (corona virus disease 2019) has caused serious impacts worldwide. Many scholars have done a lot of research on the prevention and control of the epidemic. The diagnosis of COVID-19 by cough is non-contact, low-cost, and easy-access, however, such research is still relatively scarce in China. Mel frequency cepstral coefficients (MFCC) feature can only represent the static sound feature, while the first-order differential MFCC feature can also reflect the dynamic feature of sound. In order to better prevent and treat COVID-19, the paper proposes a dynamic-static dual input deep neural network algorithm for diagnosing COVID-19 by cough. Based on Coswara dataset, cough audio is clipped, MFCC and first-order differential MFCC features are extracted, and a dynamic and static feature dual-input neural network model is trained. The model adopts a statistic pooling layer so that different length of MFCC features can be input. The experiment results show the proposed algorithm can significantly improve the recognition accuracy, recall rate, specificity, and F1-score compared with the existing models. © 2023 Chinese Institute of Electronics. All rights reserved.

A Mask Detection Algorithm Based on Improved Yolov5s

Aiming at the severe form of new coronavirus epidemic prevention and control, a target detection algorithm is proposed to detect whether masks are worn in public places. The Ghostnet and SElayer modules with fewer design parameters replace the BottleneckCSP part in the original Yolov5s network, which reduces the computational complexity of the model and improves the detection accuracy. The bounding box regression loss function DIOU is optimized, the DGIOU loss function is used for bounding box regression, and the center coordinate distance between the two bounding boxes is considered to achieve a better convergence effect. In the feature pyramid, the depthwise separable convolution DW is used to replace the ordinary convolution, which further reduces the amount of parameters and reduces the loss of feature information caused by multiple convolutions. The experimental results show that compared with the yolov5s algorithm, the proposed method improves the mAP by 4.6% and the detection rate by 10.7 frame/s in the mask wearing detection. Compared with other mainstream algorithms, the improved yolov5s algorithm has better generalization ability and practicability. © 2022 ACM.

The impact of COVID-19 prevention and control measures on residential burglary hotspots: A case study of the core urban areas of Beijing

In order to analyze the impact of COVID-19 prevention and control measures on the hotspots of residential burglary, the data of crimes that occurred during the First Level Response period of Major Public Health Emergencies in Beijing in 2020 and the same period in 2019 were collected, and the changes of hotspots during the two periods were compared by using kernel density estimation and predictive accuracy index. Consequently, the environmental features such as street network, point of interest (POI) diversity, crime locations, and repeat victimization in significantly varied hotspot areas were investigated. The results show that: 1) After the outbreak of the pandemic, the occurrence of residential burglary in the core urban areas of Beijing dropped significantly, and daily occurrence of crimes during the First Level Response period in 2020 decreased by 66.8% compared with the same days in 2019. 2) The eight major hotspots that existed in 2019 apparently declined during the corresponding days in 2020, five of them basically disappeared, and three hotspots weakened. 3) The declined hotspots were generally clustered around traffic hubs, areas with high diversity of POIs, clustered crimes, and repeat victimizations. 4) Home isolation and social restriction strategies implemented during the First Level Response period reduced the opportunities of offenders, and the real-name inspection adopted in public places increased the exposure risk of offenders, which are the main reasons for the hotspots decline during the pandemic. This work has some implications for crime prevention and police resources optimization during the pandemic. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.

Civil Aviation Customer Satisfaction Automatic Evaluation System

In 2021, the airline industry was affected by COVID-19, and many airlines suffered losses. The main reason for the loss were the decline in revenue and the surge in costs. Therefore, in terms of creating the competitive advantage of airlines, "price war" is no longer applicable, and improving service quality has become an effective means. Customer satisfaction is the most effective indicator to measure service quality. In this study, a satisfaction evaluation system is established based on structural equation model and customer satisfaction importance matrix. Then, a questionnaire is designed to analyze the influence of different factors on customer satisfaction. The research finds that brand image and perceived quality have a great impact on customer satisfaction. In addition, some suggestions for airlines to improve customer satisfaction are given. © 2023 SPIE.

Travel behavior adjustment based epidemic spreading model and prediction for COVID-19

Owing to the continuous variant of the COVID-19 virus, the present epidemic may persist for a long time, and each breakout displays strongly region/time-dependent characteristics. Predicting each specific burst is the basic task for the corresponding strategies. However, the refinement of prevention and control measures usually means the limitation of the existing records of the evolution of the spread, which leads to a special difficulty in making predictions. Taking into account the interdependence of people' s travel behaviors and the epidemic spreading, we propose a modified logistic model to mimic the COVID-19 epidemic spreading, in order to predict the evolutionary behaviors for a specific bursting in a megacity with limited epidemic related records. It continuously reproduced the COVID-19 infected records in Shanghai, China in the period from March 1 to June 28, 2022. From December 7, 2022 when Mainland China adopted new detailed prevention and control measures, the COVID-19 epidemic broke out nationwide, and the infected people themselves took "ibuprofen” widely to relieve the symptoms of fever. A reasonable assumption is that the total number of searches for the word "ibuprofen” is a good representation of the number of infected people. By using the number of searching for the word "ibuprofen” provided on Baidu, a famous searching platform in Mainland China, we estimate the parameters in the modified logistic model and predict subsequently the epidemic spreading behavior in Shanghai, China starting from December 1, 2022. This situation lasted for 72 days. The number of the infected people increased exponentially in the period from the beginning to the 24th day, reached a summit on the 31st day, and decreased exponentially in the period from the 38th day to the end. Within the two weeks centered at the summit, the increasing and decreasing speeds are both significantly small, but the increased number of infected people each day was significantly large. The characteristic for this prediction matches very well with that for the number of metro passengers in Shanghai. It is suggested that the relevant departments should establish a monitoring system composed of some communities, hospitals, etc. according to the sampling principle in statistics to provide reliable prediction records for researchers. © 2023 Chinese Physical Society.

Establishment of medical service protocols in large public hospitals for the prevention and control of coronavirus disease 2019.

Coronavirus disease 2019(COVID-19) poses a challenge to hospitals for the prevention and control of public health emergencies. As the main battlefield of preventing and controlling COVID-19, large public hospitals should develop service protocols of diagnosis and treatment for outpatient, emergency, hospitalization, surgery, and discharge. The construction of medical protocols should be based on the risk factors of key points and focused on pre-inspection triage and screening, to establish a rapid response mechanism to deal with exogenous and endogenous risk factors. Implementation of all-staff training and assessment, strengthening the information system, and use of medical internet service are important. This study explores the construction of medical protocols in large public hospitals during the pandemic, and provides a reference for the orderly diagnosis and treatment in hospitals during the pandemic.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Spatial Interactions and the Spread of COVID-19: A Network Perspective

We use unique data on the travel history of confirmed patients at a daily frequency across 31 provinces in China to study how spatial interactions influence the geographic spread of pandemic COVID-19. We develop and simultaneously estimate a structural model of dynamic disease transmission network formation and spatial interaction. This allows us to understand what externalities the disease risk associated with a single place may create for the entire country. We find a positive and significant spatial interaction effect that strongly influences the duration and severity of pandemic COVID-19. And there exists heterogeneity in this interaction effect: the spatial spillover effect from the source province is significantly higher than from other provinces. Further counterfactual policy analysis shows that targeting the key province can improve the effectiveness of policy interventions for containing the geographic spread of pandemic COVID-19, and the effect of such targeted policy decreases with an increase in the time of delay.

Understanding the use of digital finance among older internet users in urban China: Evidence from an online convenience sample

Inclusive digital financial services should welcome older populations and make them beneficiaries of the digital and financial revolution. To understand older adults' experience of using digital financial tools, we conducted an online survey of 268 older internet users aged 60 or above from urban areas of 14 Chinese provinces after China's nationwide COVID-19 lockdown in 2021. Our results revealed that older internet surfers were active in digital financial activities and engaged most with activities that were highly compatible with their lifestyles. Active users significantly differed from inactive users in sociodemographics, confirming that a digital divide related to social stratification exists among older internet users. Digital finance active users were also distinguished from inactive users' attitudes and perceptions toward digital finance. Logistic regression results indicated that perceived usefulness, access to proper devices for digital finance, risk perceptions, and perceived exclusion if not using technology were associated with their adoption of these advanced tools. Older adults reported the perceived inconvenience of in-person financial services during the lockdown. They also expressed a willingness to participate in relevant training if provided. The findings of this study could help aging-related practitioners to understand older adults' engagement in digital finance and guide policy and project design in the area of financial inclusion of the aging population.

Build an Agent-Based Model for COVID-19 Effect of Mitigation Policies

Non-Drug Intervention (NDI) is one of the important means to prevent and control the outbreak of coronavirus disease 2019 (COVID-19), and the implementation of this series of measures plays a key role in the development of the epidemic. The purpose of this paper is to study the impact of different mitigation measures on the situation of the COVID 19, and effectively respond to the prevention and control situation in the "post-epidemic era". The present work is based on the Susceptible-Exposed-Infectious-Remove-Susceptible (SEIRS) Model, and adapted the agent-based model (ABM) to construct the epidemic prevention and control model framework to simulate the COVID-19 epidemic from three aspects: social distance, personal protection, and bed resources. The experiment results show that the above NDI are effective mitigation measures for epidemic prevention and control, and can play a positive role in the recurrence of COVID-19, but a single measure cannot prevent the recurrence of infection peaks and curb the spread of the epidemic;When social distance and personal protection rules are out of control, bed resources will become an important guarantee for epidemic prevention and control. Although the spread of the epidemic cannot be curbed, it can slow down the recurrence of the peak of the epidemic;When people abide by social distance and personal protection rules, the pressure on bed resources will be eased. At the same time, under the interaction of the three measures, not only the death toll can be reduced, but the spread of the epidemic can also be effectively curbed. © 2022 ACM.

Simulation Analysis of COVID-19 Epidemic Model in Wuhan Based on SIR Model

Based on SIR model, combined with the mode of COVID-19 epidemic spread in Wuhan, the SIR model of COVID-19 epidemic spread is constructed, which mainly includes three aspects: simulation of the average number of infected people in COVID-19, simulation of cross-infection in COVID-19 and simulation of contact infection in COVID-19. Using the results of these three simulations, we can predict the spread of COVID-19 epidemic in the region, and find out the methods to prevent and control the outbreak or spread of the epidemic. © 2023 SPIE.

Analysis of avian disease transmission risk and prevention measures in China

Many zoonotic diseases are found in wild animals and present a serious risk to human health, in particularly the virus carried by birds flying freely around the world is hard to control. There are three main bird migration routes which cover the most areas of China. It is important to investigate and fully understand the types of avian transmitted diseases in key areas on the bird migration routines and its impacts on both birds and human health. However, no literature is available in how about the risk of virus carried by migrating birds, and how to predict and reduce this risk of virus spreading to human being so far. In this paper, we first reviewed the main pathogen types carried by birds, including coronaviruses, influenza viruses, parasites, Newcastle disease virus (NDV), etc., and then discussed the spread risk of avian viruses to human being and animals in key areas of biosafety prevention. We also analyzed and discussed the risk of cross-spread of diseases among different bird species in nature reserves located on bird migration routes which provide sufficient food sources for migratory birds and attract numerous birds. Diseases transmitted by wild birds pose a serious threat to poultry farms, where high density of poultry may become avian influenza virus (AIV) reservoirs, cause a risk of avian influenza outbreaks. Airports are mostly built in suburban areas or remote areas with good ecological environment. There are important transit places for bird migration and densely populated areas, which have serious risk of disease transmission. Finally, this paper puts forward the following prevention suggestions from three aspects. First, establish and improve the monitoring and prediction mechanism of migratory birds, and use laser technology to prevent contact between wild birds and poultry. Second, examine and identify virus types carried by birds in their habitats and carry out vaccination. Third, protect the ecological environment of bird habitat, and keep wild birds in their natural habitat, so as to reduce the contact between wild birds and human and poultry, and thus reduce the risk of virus transmission.

Design and Coverage Path Planning of a Disinfection Robot

Eliminating pathogen exposure is an important approach to control outbreaks of epidemics such as COVID-19 (coronavirus disease 2019). To deal with pathogenic environments, using disinfection robots is a practicable choice. This research formulates a 3D (three-dimensional) spatial disinfection strategy for a disinfection robot. First, a disinfection robot is designed with an extensible control framework for the integration of additional functions. The robot has eight degrees of freedom that can handle disinfection tasks in complex 3D environments where normal disinfection robots lack the capability to ensure complete disinfection. An ingenious clamping mechanism is designed to increase flexibility and adaptability. Secondly, a new coverage path planning algorithm targeted at the spraying area is used. This algorithm aims to achieve an optimal path via the rotating calipers algorithm after transformation between a 2D (two-dimensional) array and 3D space. Finally, the performance of the designed robot is tested through a series of simulations and experiments in various spaces that humans usually live in. The results demonstrate that the robot can effectively perform disinfection tasks both in computer simulation and in reality.

The Relationship between Movement Control Order Impact Factors and Construction Project Performance

The Malaysian government's pursuit of the Movement Control Order (MCO) had a severe impact on the performance of the construction project, which was hampered as a result of their actions. It becomes even more difficult when the region around construction projects is defined as a "red zone". This situation affects the performance of construction projects, which is related to project delays, increase in construction costs, waste of construction materials, labourers who have not received any salary, lack of labour, and etc. This paper attempts to investigate the relationship between MCO impact factors and the performance of construction projects in Malaysia. The quantitative technique was applied in this study. The contractors registered under the Construction Development Board (CIDB) in the state of Selangor were chosen as the respondents. In total, 100 respondents participated and gave full support for this study. This relationship was investigated using a correlation analysis technique. The highest impact is the construction cost. The construction costs increased due to the increase in the prices of construction materials and machinery, lack of labours, and additional expenses for COVID-19 precautions. The findings found that the larger the negative impact of MCO's actions during the COVID-19 outbreak on time, cost, and resources, the worse the performance of Malaysian projects will be in general. These factors should be considered by the government before a decision is made. For future research, it is suggested to look at how the regulation can assist the construction stakeholders to ensure the MCO does not have a big impact on the construction projects.

Secondary school students' school-related stressors during the coronavirus disease (COVID-19) pandemic in Sabah, Malaysia

IntroductionDue to the rapid spread of the COVID-19 pandemic and the disruption of education systems worldwide, secondary schools in Malaysia have shifted to online classes to ensure educational continuity. Therefore, it was necessary to investigate the various effects of the COVID-19 pandemic on secondary school students. MethodsA self-reported survey with closed and open-ended questions was used to collect data involving 1,067 secondary school students from eight schools in Sabah, Malaysia. The participants were mostly male (53.4%), with a mean age of 14.8 (SD = 1.64). The study involved students from various levels/grades, including transition class, forms 1-5, lower six, and upper six. ResultsStudents faced a variety of school-related stressors, including academic failure due to a poor online course;general mental health issues;a poor internet connection;a lack of in-person interaction;a SOP restriction;an inability to focus;too many homework assignments;burnout;becoming lazier;home conditions;and financial difficulties. DiscussionThe implications for classroom practice, policy formulation, and future research are examined.