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The outbreak of multiple disaster sites during the coronavirus disease 2019 (COVID-19) pandemic has presented challenges due to varying access time intensity, population density, and medical resources at each site. To address these issues, this study focuses on 13 districts and counties in Wuhan, China. The importance of each research area is analyzed using the improved PageRank and TOPSIS algorithms to determine the optimal site selection plan. Additionally, a particle swarm algorithm is used to construct an emergency material dispatching model that targets both distribution and site selection costs to solve the multi-distribution center dispatching problem. The results suggest that constructing 10 distribution centers can satisfy the demand for epidemic prevention and control in Wuhan city while saving costs associated with site selection and material distribution. Compared to the previous optimal solution, the distribution and site selection costs under the optimal solution decreased by 27.9% and 17.82%, respectively. This approach can serve as a basis for dispatching emergency materials during public health emergencies.
ABSTRACT
The outbreak of multiple disaster sites during the coronavirus disease 2019 (COVID-19) pandemic has presented challenges due to varying access time intensity, population density, and medical resources at each site. To address these issues, this study focuses on 13 districts and counties in Wuhan, China. The importance of each research area is analyzed using the improved PageRank and TOPSIS algorithms to determine the optimal site selection plan. Additionally, a particle swarm algorithm is used to construct an emergency material dispatching model that targets both distribution and site selection costs to solve the multi-distribution center dispatching problem. The results suggest that constructing 10 distribution centers can satisfy the demand for epidemic prevention and control in Wuhan city while saving costs associated with site selection and material distribution. Compared to the previous optimal solution, the distribution and site selection costs under the optimal solution decreased by 27.9% and 17.82%, respectively. This approach can serve as a basis for dispatching emergency materials during public health emergencies. © 2023 by the authors.
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Based on big data on migration from the Baidu Map platform, this paper divides China's epidemic prevention and control efforts into four stages. Then, the characteristics and spatial patterns of daily population flows are studied by social network analysis. Subsequently, the exponential random graph model is used to investigate the influence of dynamic characteristics of changes in the spatial structure of the interprovincial population flow network during the postepidemic period. The spatial structure of the population flow network before, during, and after the epidemic shows significantly different characteristics, with epidemic prevention and control measures playing a significant role in restricting population flows. Interprovincial population flows have a certain degree of transmissibility, but two-way flows are not obvious. In addition, for regions with a larger resident population and a higher unemployment rate, a larger population tends to flow out. For regions with higher per capita GDP, the secondary and tertiary industries account for a relatively larger proportion, and the public environment is better. The more attractive a region is to the population, the higher is the tendency towards population inflows. Moreover, the level of medical care and epidemic prevention and control have become the main influencing factors of population movement.
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The COVID-19 epidemic is running at a high level globally, affecting all aspects of society, and medical education is no exception. With the rapid development of medical science, continuing medical education is an important way for medical workers to receive lifelong education. Meanwhile, attending continuing medical education is an inevitable requirement to ensure clinical ability. Under the background of normalization of epidemic prevention and control and the new situation of medical development, the management of continuing medical education in hospitals must follow the current situation and keep pace with the times. Therefore, the Internet support system to continuing education has emerged. This study used PDSA method to explore the construction of the regional center of continuing medical education through Internet under the background of normalization of epidemic prevention and control, aiming to promote the integration of medical education resources under the new situation, expand the learning channels of medical staff, and improve the level of medical education and teaching. © 2022 IEEE.
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PurposeDecision-making problems in emergency plan selection for epidemic prevention and control (EPAC) are generally characterized by risky and uncertainty due to multiple possible emergency states and vagueness of decision information. In the process of emergency plan selection for EPAC, it is necessary to consider several obvious features, i.e. different states of epidemics, dynamic evolvement process of epidemics and decision-makers' (DMs') psychological factors such as risk preference and loss aversion.Design/methodology/approachIn this paper, a novel decision-making method based on cumulative prospect theory (CPT) is proposed to solve emergency plan selection of an epidemic problem, which is generally regarded as hybrid-information multi-attribute decision-making (HI-MADM) problems in major epidemics. Initially, considering the psychological factors of DMs, the expectations of DMs are chosen as reference points to normalize the expectation vectors and decision information with three different formats. Subsequently, the matrix of gains and losses is established according to the reference points. Furthermore, the prospect value of each alternative is obtained and the comprehensive prospect values of alternatives under different states are calculated. Accordingly, the ranking of alternatives can be obtained.FindingsThe validity and robustness of the proposed method are demonstrated by a case calculation of emergency plan selection. Meanwhile, sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and TODIM (an acronym in Portuguese for interactive and MADM) method illustrate the effectiveness and superiority of the proposed method.Originality/valueAn emergency plan selection method is proposed for EPAC based on CPT, taking into account the psychological factors of DMs.HighlightsThis paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.
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Purpose: By serving and providing a guide for other regional places, this study aims to advance and guide the epidemic prevention and control methods, and practices and strengthen people's ability to respond to COVID-19 and other future potential public health risks. Design/methodology/approach: A comparative analysis was conducted that the COVID-19 epidemic development trend and prevention and control effects both in Beijing and Shanghai. In fact, regarding the COVID-19 policy and strategic areas, the differences between governmental, social, and professional management were discussed and explored. To prevent and be ready for potential pandemics, experience and knowledge were used and summarized. Findings: The strong attack of the Omicron variant in early 2022 has posed challenges to epidemic prevention and control practices in many Chinese cities. Shanghai, which had achieved relatively good performance in the fight against the epidemic, has exposed limitations in its epidemic prevention and control system in the face of Omicron. In fact, the city of Beijing has undertaken prompt and severe lockdown measures and achieved rather good results in epidemic prevention and control because of learning from Shanghai's experience and lessons; adhering to the overall concept of "dynamic clearing," implementing precise prevention and monitoring, enhancing community control, and making emergency plans and preparations. All these actions and measures are still essential in the shift from pandemic response to pandemic control. Research limitations/implications: Different places have introduced different urgent policies to control the spread of the pandemic. Strategies to control COVID-19 have often been based on preliminary and limited data and have tended to be slow to evolve as new evidence emerges. Hence, the effects of these anti-epidemic policies need to be further tested.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2 , Beijing/epidemiology , Communicable Disease Control/methods , China/epidemiology , Pandemics/prevention & controlABSTRACT
We live in a world of borders, which influence our perception and movement. Traditional mapping techniques show limitations as borders have become shifting and complex, and borders' multi-scale and multi-spatial properties have been strengthened significantly. To fill the knowledge gap, we explored the multi-spatiality of borders and provided approaches for border symbol design and visualization by taking the coronavirus-hit border city, Ruili, China, as an example. This work could shed light on multi-spatial geographic visualization and policy-making.
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Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a serious threat to international public health. The SARS-COV-2 gene continues to mutate in COVID-19 outbreaks. Mutation mainly manifests in 3 forms: point mutation, gene recombination and epigenetic modification. Viral mutations are driven by multiple factors, with mutation rates modulated at 3 levels, the nature of virus, host-virus interactions and natural selection. Therefore, it is particularly important to strengthen the monitoring of the global novel coronavirus genome and the protection of immunosuppressed populations. In the early stage of virus evolution, the mutant strains exhibit greater transmissibility and less virulence than the wild-type strain, although 5 variants of concern (VOCs) showed different stability, transmission capacity, adaptability and pathogenicity. So physical interventions need to be further strengthened. As herd immunity is established, novel mutant strains tend to mutate against vaccines and antibodies. In that case, VOCs, especially the prevailing Omicron variant, bring challenges to the prevention and control of COVID-19 worldwide. The existing and potential prevention, diagnosis and treatment approaches for COVID-19 were summarized. In the vaccination part, the protective efficacy of COVID-19 vaccine against VOCs and the factors influencing the efficacy of COVID-19 vaccine were analyzed. In the detection part, the detection methods based on nucleic acid, antigen and antibody were summarized in order to satisfy the requirements for point-of-care testing and timely recognition of novel variants. And in the treatment part, the potential therapeutic drugs and targets of SARS-CoV-2 were summarized. Drug targets are generally divided into extracellular targets and intracellular targets. In general, this review proposes possible countermeasures by analyzing the impact of mutations on global epidemic prevention and control, hoping to provide theoretical basis for possible large-scale epidemic prevention and control in the future. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.
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The COVID-19 has had a profound impact on human society, the elderly, as a vulnerable group, are the most affected. Based on two cases of disease narrative collected by the department of neurology of a hospital in Guiyang, this paper analyzed the shortcomings of elderly care in the context of epidemic prevention and control. The overall health information literacy of the elderly was low, which made it difficult to obtain correct epidemic related information. The lifestyle of the elderly has changed during the epidemic prevention and control stag. The long time isolation at home has reduced their constitution and made them prone to illness, thus affecting the quality of healthy elderly care. In this stage, the psychological burden of the middle-aged and elderly people has been increasing, which reduced the life satisfaction and subjective well-being of the elderly, and increased the risk of depression. In view of these outstanding problems, this paper proposed corresponding measures, aiming to improve the quality of life and physical and mental health of the elderly during the epidemic prevention and control stage, and provide reference for realizing healthy aging in China. © 2023, Editorial department of Chinese Medical Ethics. All rights reserved.
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This book systematically assesses the risk of 21 major infectious diseases threatening BRI countries. It consists of 14 chapters. Chapter 1 is an overview. Chapter 2 introduces the history of health cooperation between China and other BRI countries. Chapters 3-14 introduce the prevalence of major infectious diseases threatening BRI countries such as cholera, vaccine preventable diseases (polio, measles, meningitis, Japanese encephalitis, diphtheria, hepatitis A), tuberculosis, influenza, and insect-borne diseases (Dengue fever, Zika virus disease, yellow fever, Chikungunya, Rift Valley fever), plague, malaria, Ebola virus disease, MERS, schistosomiasis, COVID-19 and AIDS, and risk factors, principles and cases of their prevention and control. It is a useful reference book in the research of infectious disease control and prevention, and provides historical experience and lessons learned. It also provides decision support for international cooperation among BRI countries in the field of epidemic prevention and control in the future. © People's Medical Publishing House, PR of China 2021, corrected publication 2021.
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During the prevention and control of the COVID-19，the decrease in routine medical care has spread across countries in various degrees，also affecting the management of chronic disease accordingly. The policies and schemes of prevention and control of the COVID-19 in China have been adjusted since December 2022，health care system has been facing serious challenges，bringing increased pressure on primary care. Based on the experiences of other countries，this paper suggests that primary care in China should pay attention to the promoting of self-management for patients with chronic diseases，providing proactive service for patients with complex situations and high demand，strengthening the application and research of telemedicine，intensifying the community connection of primary care services，focusing on the improvement of the compensation mechanism of health services. © 2023 Chinese General Practice. All rights reserved.
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Volunteer service is an important way for contemporary Chinese college students to carry out social practice, and an effective carrier for strengthening ideological and political work in the new era. During the prevention and control of the COVID-19, college students, as a solid force in the volunteer team, actively participated in the anti-epidemic volunteer service, which not only improved their practical ability, but also practiced the core socialist values and inherited the excellent traditional Chinese culture. Based on the existing practical experience in volunteer service, Beijing University of Chinese Medicine has made use of multiple channels and resources to improve the volunteer training system, strengthen the guarantee of volunteer service, realize the high-quality leapfrog development of college students' volunteer service, and provide experience and reference for the innovation of college students' volunteer service in the new era. © 2023, Editorial department of Chinese Medical Ethics. All rights reserved.
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Objective: To develop a SARS-CoV-2 antigen detection management system for Chinese residents under community grid management, which is supported by "health information technology" and "neural network image recognition", so as to give full play to the advantages of "grid management". This system is applied to the normalized prevention and control of COVID-19 epidemic. Method(s): The model of image recognition algorithm was built based on deep learning and convolution neural network (CNN) artificial intelligence algorithm. The improved Canny edge detection algorithm was used to monitor and locate the image edge, and then the image segmentation and judgment value calculation were completed according to projection method. The system construction was completed combing with the grid number design. Result(s): The proposed method had been tested and showed the accuracy of the algorithm. With a certain robustness, the algorithm error was proved to be small. Based on the image recognition algorithm model, the development of SARS-CoV-2 antigen detection management system covering user login, paper-strip test image upload, paper-strip test management, grid management, grid warning and regional traffic management was completed. Conclusion(s): Antigen detection is an important supplementary means of COVID-19 epidemic prevention and control in the new stage. The SARS-CoV-2 antigen detection management system for Chinese residents under community grid managemen based on image recognition enables mobile communication devices to recognize the image of SARS-CoV-2 antigen detection results, which is helpful to form a grid management mode for the epidemic and improve the management framework of epidemic monitoring, detection, early warning and prevention and control.Copyright © 2023 The Authors
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In view of the spread of COVID-19 epidemic and many problems existing in the community, such as potential safety hazards, diluted interpersonal relationships, and out-of-place management, a system of one-stop intelligent environmental protection communities based on the Internet was proposed. It not only improves the ability of community staff, provides great convenience for residents and community workers, cares for vulnerable groups, and promotes a happy and harmonious neighborhood life, but also scores residents and staff while monitoring the community environment for safety with the technology application of thermal imaging recognition, PaddleHub-based face and mask recognition. This new system design is easy to implement at low cost and has a simple structure with many functions. The technologies for face and mask recognition proposed in this paper are based on PaddleHub. Experiments on MaskedFace-Net provided by Haute-Alsace University and the pretrained parameters loaded by PaddleHub showed that the accuracy rate with mask recognition was 94.3290 percent using this method. © 2022 ACM.
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Coronavirus disease-19 (COVID-19) has been spreading all over the world for more than two years. Though several kinds of vaccines are currently available, emergence of new variants, spike mutations and immune escape have raised new challenges. Pregnant women are vulnerable to respiratory infections due to their altered immune defence and surveillance functions. Besides, whether pregnant persons should receive a COVID-19 vaccine is still under debate because limited data are available on the efficacy and safety of receiving a vaccine during pregnancy. Physiological features and lack of effective protection making pregnant women at high risk of getting infected. Another concern is that pregnancy may trigger the onset of underlying existing neurological disease, which is highly similar to those neurological symptoms of pregnant women caused by COVID-19. These similarities interfere with diagnosis and delay timely and effective management. Therefore, providing efficient emergency support for pregnant women suffering from neurological symptoms caused by COVID-19 remains a challenge among neurologists and obstetricians. To improve the diagnosis and treatment efficiency of pregnant women with neurological symptoms, we propose an emergency management framework based on the clinicians' experience and available resources. This emergency care system aimed at addressing the conundrums faced by the emergency guarantee system under COVID-19 pandemic and could serve as a potential multisystem project for clinical practice and medical education.
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The COVID-19 pandemic has led to a generally high level of state anxiety resulting from the high contagiousness of the disease and strict prevention and control policies. The present study mainly focused on the relationship between the individual intolerance of uncertainty and state anxiety in the regular epidemic prevention and control phase in China, and aimed to investigate the mediating role of information overload and rumination, as well as the moderating role of self-compassion. A total of 992 Chinese residents from 31 provinces participated in this study, and completed questionnaires regarding intolerance of uncertainty, information overload, self-compassion, rumination, and state anxiety. Descriptive statistics and correlation analyses, as well as tests for mediating effects and moderated chain mediating effects, were performed on the data using SPSS 26.0 and Process 3.5 macro program. The findings indicated that intolerance of uncertainty significantly predicted individual state anxiety. Information overload mediates the effects of intolerance of uncertainty and state anxiety. Rumination also mediates the effect of uncertainty intolerance on state anxiety. Information overload and rumination have a chain mediation effect on the link between intolerance of uncertainty and state anxiety. Self-compassion mediates the effect of information overload on rumination. The results illuminate theoretical and practical implications in the regular epidemic prevention and control phases and reveal the protective role of self-compassion.
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Faced with the current time-sensitive COVID-19 pandemic, the overburdened healthcare systems resulted in a strong demand to develop newer methods to control the spread of the pandemic. Big data and artificial intelligence (AI) have been leveraged amid the COVID-19 pandemic; however, little is known about its use for supporting public health efforts. In epidemic surveillance and containment, efforts are needed to treat critical patients, track and manage the health status of residents, isolate suspected cases, develop vaccines and antiviral drugs. The applications of emerging practices of artificial intelligence and big data have become powerful "weapons" to fight against the pandemic and provide strong support in pandemic prevention and control, such as early warning, analysis and judgment, interruption and intervention of epidemic, to achieve goals of early detection, early report, early diagnosis, early isolation and early treatment, and these are the decisive factors to control the spread of the epidemic and reduce the mortality. This paper systematically summarizes the application of big data and AI in epidemic, and describes practical cases and challenges with emphasis in epidemic prevention and control. The included studies showed that big data and AI have the potential strength to fight against COVID-19. However, many of the proposed methods are not yet widely accepted. Thus, the most rewarding research will be on methods promising value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for practice.
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Big data technology plays an important role in the prevention and control of public health emergencies such as the COVID-19 pandemic. Current studies on model construction, such as SIR infectious disease model, 4R crisis management model, etc., have put forward decision-making suggestions from different perspectives, which also provide a reference basis for the research in this paper. This paper conducts an exploratory study on the construction of a big data prevention and control model for public health emergencies by using the grounded theory, a qualitative research method, with literature, policies, and regulations as research samples, and makes a grounded analysis through three-level coding and saturation test. Main results are as follows: (1) The three elements of data layer, subject layer, and application layer play a prominent role in the digital prevention and control practice of epidemic in China and constitute the basic framework of the "DSA" model. (2) The "DSA" model integrates cross-industry, cross-region, and cross-domain epidemic data into one system framework, effectively solving the disadvantages of fragmentation caused by "information island". (3) The "DSA" model analyzes the differences in information needs of different subjects during an outbreak and summarizes several collaborative approaches to promote resource sharing and cooperative governance. (4) The "DSA" model analyzes the specific application scenarios of big data technology in different stages of epidemic development, effectively responding to the disconnection between current technological development and realistic needs.
Subject(s)
COVID-19 , Public Health , Humans , Public Health/methods , COVID-19/epidemiology , COVID-19/prevention & control , Emergencies , Big Data , Pandemics/prevention & control , Grounded TheoryABSTRACT
The COVID-19 has had a profound impact on human society, the elderly, as a vulnerable group, are the most affected. Based on two cases of disease narrative collected by the department of neurology of a hospital in Guiyang, this paper analyzed the shortcomings of elderly care in the context of epidemic prevention and control. The overall health information literacy of the elderly was low, which made it difficult to obtain correct epidemic related information. The lifestyle of the elderly has changed during the epidemic prevention and control stag. The long time isolation at home has reduced their constitution and made them prone to illness, thus affecting the quality of healthy elderly care. In this stage, the psychological burden of the middle-aged and elderly people has been increasing, which reduced the life satisfaction and subjective well-being of the elderly, and increased the risk of depression. In view of these outstanding problems, this paper proposed corresponding measures, aiming to improve the quality of life and physical and mental health of the elderly during the epidemic prevention and control stage, and provide reference for realizing healthy aging in China. © 2023, Editorial department of Chinese Medical Ethics. All rights reserved.
ABSTRACT
Volunteer service is an important way for contemporary Chinese college students to carry out social practice, and an effective carrier for strengthening ideological and political work in the new era. During the prevention and control of the COVID-19, college students, as a solid force in the volunteer team, actively participated in the anti-epidemic volunteer service, which not only improved their practical ability, but also practiced the core socialist values and inherited the excellent traditional Chinese culture. Based on the existing practical experience in volunteer service, Beijing University of Chinese Medicine has made use of multiple channels and resources to improve the volunteer training system, strengthen the guarantee of volunteer service, realize the high-quality leapfrog development of college students' volunteer service, and provide experience and reference for the innovation of college students' volunteer service in the new era. © 2023, Editorial department of Chinese Medical Ethics. All rights reserved.