Job burnout and its influencing factors among primary healthcare workers during the COVID-19 epidemic in Guangzhou, China, 2021-2022: from the perspective of institutional operation and management.

BACKGROUND: The purpose of this study was to explore the job burnout of primary healthcare workers in Guangzhou during the prevention and control of COVID-19 epidemic and its influencing factors from the perspective of institutional operation and management in 2021-2022. METHODS: A cross-sectional study involved 866 primary healthcare workers from different districts of Guangzhou, China. The Chinese version of the Maslach Burnout Inventory-General Survey (MBI-GS) was utilized to assess job burnout. From the perspective of organizational operation and management, the possible causes of job burnout among primary healthcare workers during COVID-19 have been categorized into 7 major aspects. Univariate and multivariate logistic regression analyses were conducted to identify influencing factors for job burnout in primary healthcare workers. RESULTS: The detection rate of job burnout among primary healthcare workers was 78.29%. Men (OR = 2.39) and whose institution was located in urban-rural fringe (OR = 1.56) were more likely to detect job burnout. Conversely, institution heads showed a lower risk of job burnout. From the perspective of institutional operation and management, workers who were not satisfied with personnel management (OR = 2.41), materials and vehicles (OR = 2.89), subsidies and compensation (OR = 2.18), humanistic care (OR = 2.11), superior management (OR = 8.32) were found to have a higher risk of job burnout. CONCLUSION: The detection rate of job burnout among primary healthcare workers in Guangzhou was relatively high during the period of COVID-19. When there is another sudden major epidemic, the managers of institutions can focus on and deal with the problems related to the operation and management of institutions such as personnel management, materials and vehicles, subsidies and compensation, humanistic care, and superior management, so as to provide logistical support for the workers and alleviate their job burnout.

The support dilemma of stroke inpatients and family caregivers under COVID-19 prevention and control: a qualitative study in China.

China has implemented a strict isolation system in hospitals since the COVID-19 pandemic, that adversely affected the psychology of inpatients and their caregivers. Face-to-face, semi-structured interviews with 22 stroke inpatients from two municipal hospitals were conducted to explore the psychological, emotional and related support needs of stroke inpatients and their family caregivers under this environment. Results which showed that external support for stroke inpatients and their family caregivers was insufficient highlight the necessity for developing specific nursing interventions that meet the psychological and emotional needs of inpatients and the caregivers.

Factors associated with sleep quality among nurse managers during regular prevention and control of the COVID-19 in China: a cross-sectional study.

BACKGROUND: Nurse managers play a pivotal role in quality patient care and staff satisfaction and retention. An overwhelming amount of work tasks and responsibilities might result in their sleep problems which are expected to aggravate in the context of the COVID-19, thereby affecting their overall health and work quality. However, little attention has been paid to sleep quality among nurse managers. This study aimed to investigate the prevalence of sleep disorders among nurse managers and identify related factors of sleep quality during regular prevention and control of the COVID-19 pandemic in China. METHODS: This cross-sectional online survey was conducted in 14 hospitals on a sample of 327 nurse managers in China. Participants were invited to complete the general demographic questionnaire, Pittsburgh Sleep Quality Index (PSQI) and Simplified Coping Style Questionnaire (SCSQ). Multiple linear regression analysis was used to explore the influencing factors of sleep quality among nurse managers. RESULTS: In this study, 43.7% of nurse managers suffered from sleep disorders. Active coping style and frequent exercise were positive factors that could influence nurse managers' sleep quality, while passive coping style and age over 41 years old were negative predictors, collectively accounting for 52.0% of the variance of sleep quality. CONCLUSIONS: The issue of sleep disorders among nurse managers during regular epidemic prevention and control period is underscored. Coping style and demographic factors including age and frequency of exercise can significantly affect nurse managers' sleep quality. Healthcare administrators should pay more attention to nurse managers' sleep disorders and implement targeted strategies based on influencing factors to ensure their sleep quality.

Nurses' experience of work stress related to COVID-19 regular prevention and control in China: A qualitative study.

AIM: To explore the experiences of nurses' work stress related to COVID-19 regular epidemic prevention and control in China. BACKGROUND: The global COVID-19 epidemic is still severe, and China's ongoing regular epidemic prevention and control still cannot be relaxed, which places demands on nurses. METHODS: Thirty nurses and eight nurse managers were interviewed using semistructured in-depth interviews, and the data were analysed by the Colaizzi seven-step analysis method. RESULTS: Four themes were extracted as follows: environmental factors, organizational factors, personal factors and positive factors in coping with stress. CONCLUSIONS: Nursing managers should pay attention to construction of the first-line departments of regular epidemic prevention and control. The shortage of nurses' human resources and the increase of nurse-patient conflicts are problems that need to be solved urgently. In addition, this research also emphasizes the importance of promoting nurses' stress-related growth and thinking about the possibility of reform. IMPLICATIONS FOR NURSING MANAGEMENT: The construction of the hospital environment and increasing the resilience of nursing teams require attention. We should attach importance to the training of nurses' communication skills and provide sufficient organizational support and economic guarantees for nurses. Finally, perhaps we should also consider whether it is necessary to reform the relevant hospital systems and how to reform them.

The Role of Forensic Medicine in Responding to Emergencies and New Major Epidemics.

In recent years, human beings are constantly facing the threat of emerging infectious diseases. Forensic technology plays a unique role in responding to the emergencies and new epidemics. In epidemic prevention and control, forensic partitioners can provide important clues for the identification of vector animal species and the traceability of pathogen regions based on non-human DNA testing technology. In epidemic-related judicial practice, forensic partitioners bear more and more evidence responsibilities in dealing with biosafety laws-related issues, such as improper handling of epidemics and vaccine safety issues, which require forensic evidence. In terms of pathogen tracing, forensic physical evidence examinations identify species and individuals through biological materials extracted from the scene of death and autopsy of infectious diseases, are expected to provide informative clues for epidemiological investigations and point out the direction for pathogen tracing. In addition, forensic pathological examination can provide an important pathophysiological basis for determining the cause of death and the mechanism of death through autopsy, also offer necessary scientific evidence for clarifying the epidemiological characteristics of the epidemic and predicting the development trend of the epidemic.

Clustering Cases of Chlamydia psittaci Pneumonia in Coronavirus Disease 2019 Screening Ward Staff.

We describe 4 cases of Chlamydia psittaci pneumonia among medical staff in a coronavirus disease 2019 (COVID-19) screening ward, as well as the experience of dealing with this nosocomial infection event. Atypical pneumonia, in addition to COVID-19, should be considered when clustering cases occur, even during a COVID-19 pneumonia pandemic.

Effect of the "Normalized Epidemic Prevention and Control Requirements" on hospital-acquired and community-acquired infections in China.

BACKGROUND: No studies have yet reported the effect of prevention and control measures, which were implemented to combat COVID-19, on the prevention and control of common HAIs. We aimed to examine the effect of the "Normalized Epidemic Prevention and Control Requirements" (implemented in May 2020) by comparison of hospital-acquired infections (HAIs) and community-acquired infections (CAIs) in China during 2018, 2019, and 2020. METHODS: Data of inpatients before and after implementation of new requirements were retrospectively analyzed, including infection rate, use of alcohol-based hand cleaner, anatomical sites of infections, pathogen species, infection by multi-drug resistant species, and use of different antibiotics. RESULTS: The HAI rate was significantly higher in 2020 than in 2018 and 2019 (P < 0.05), and the CAI rate was significantly higher in 2019 and 2020 than in 2018 (P < 0.001). Lower respiratory tract infections were the most common HAI during all years, with no significant changes over time. Lower respiratory tract infections were also the most common CAI, but were significantly more common in 2018 and 2019 than 2020 (P < 0.001). There were no changes in upper respiratory tract infections among HAIs or CAIs. Most HAIs and CAIs were from Gram-negative bacteria, and the percentages of fungal infections were greater in 2019 and 2020 than 2018. MRSA infections were more common in 2020 than in 2018 and 2019 (P < 0.05). The utilization rate and usage days of antibiotics decreased over time (P < 0.001) and the culture rate of microbial specimens before antibiotic usage increased over time (P < 0.001). CONCLUSIONS: The new prevention and control requirements provided important benefits during the COVID-19 pandemic. However, their effects on HAIs were not obvious.

Population migration, spread of COVID-19, and epidemic prevention and control: empirical evidence from China.

BACKGROUND: This study applied the susceptible-exposed-infectious-removed (SEIR) model to analyze and simulate the transmission mechanisms of the coronavirus disease 2019 (COVID-19) in China. METHODS: The population migration was embedded in the SEIR model to simulate and analyze the effects of the amount of population inflow on the number of confirmed cases. Based on numerical simulations, this study used statistical data for the empirical validation of its theoretical deductions and discussed how to improve the effectiveness of epidemic prevention and control considering population migration variables. Statistics regarding the numbers of infected people in various provinces were obtained from the epidemic-related data reported by China's National Health Commission. RESULTS: This study explored how the epidemic should be prevented and controlled from the perspective of population migration variables. It found that the combination of a susceptible population, an infected population, and transmission media were important routes affecting the number of infections and that the migration of a Hubei-related infected population played a key role in promoting epidemic spread. Epidemic prevention and control should focus on regions with better economic conditions than the epidemic region. Prevention and control efforts should focus on the more populated neighboring provinces having convenient transportation links with the epidemic region. To prevent and control epidemic spread, priority should be given to elucidating the destinations and directions of population migration from the domestic origin of infections, and then controlling population migration or human-to-human contact after such migration. CONCLUSIONS: This study enriched and expanded on simulations of the effects of population migration on the COVID-19 epidemic and China-based empirical studies while offering an epidemic evaluation and warning mechanism to prevent and control similar public health emergencies in the future.

Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China.

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly and affected most of the world since its outbreak in Wuhan, China, which presents a major challenge to the emergency response mechanism for sudden public health events and epidemic prevention and control in all countries. In the face of the severe situation of epidemic prevention and control and the arduous task of social management, the tremendous power of science and technology in prevention and control has emerged. The new generation of information technology, represented by big data and artificial intelligence (AI) technology, has been widely used in the prevention, diagnosis, treatment and management of COVID-19 as an important basic support. Although the technology has developed, there are still challenges with respect to epidemic surveillance, accurate prevention and control, effective diagnosis and treatment, and timely judgement. The prevention and control of sudden infectious diseases usually depend on the control of infection sources, interruption of transmission channels and vaccine development. Big data and AI are effective technologies to identify the source of infection and have an irreplaceable role in distinguishing close contacts and suspicious populations. Advanced computational analysis is beneficial to accelerate the speed of vaccine research and development and to improve the quality of vaccines. AI provides support in automatically processing relevant data from medical images and clinical features, tests and examination findings; predicting disease progression and prognosis; and even recommending treatment plans and strategies. This paper reviews the application of big data and AI in the COVID-19 prevention, diagnosis, treatment and management decisions in China to explain how to apply big data and AI technology to address the common problems in the COVID-19 pandemic. Although the findings regarding the application of big data and AI technologies in sudden public health events lack validation of repeatability and universality, current studies in China have shown that the application of big data and AI is feasible in response to the COVID-19 pandemic. These studies concluded that the application of big data and AI technology can contribute to prevention, diagnosis, treatment and management decision making regarding sudden public health events in the future.

Characterizing the patterns of China's policies against COVID-19: A bibliometric study.

Since the beginning of 2020, the Chinese government has implemented substantial policies to prevent and control the COVID-19 epidemic. This research attempts to reveal and characterize the patterns of China's policy against COVID-19. Bibliometric methods are applied for studying policy evolution, with the aim of discovering the transitions of the policies over time, the collaborations among policy makers, and the effects of the policies. A total of 366 policies of epidemic prevention are collected. Policy topic shifting, the cooperation of policy-issuing agencies, and the policy content of agencies are analyzed. According to the results, China's policies are implemented in four stages. Moreover, the policy's foci against COVID-19 shifted from medical support in the early stage to economic development in the late stage. Agencies involved in the policymaking can be categorized into three types: leading agencies, key agencies, and auxiliary agencies, with their corresponding administrative influence ranked in this order. Especially, the Chinese government adopted a multi-agency, joint epidemic prevention and control mechanism to ensure the efficiency of the policymaking cooperation. Furthermore, aside from ensuring cooperation among the policy-issuing agencies, they each had their own primary focus of policies in the early stage, but their foci were gradually shared as the epidemic situation changed. This research reveals how China responded to the public health emergency of COVID-19 from the perspective of policy making.

Exploring early prevention and control of COVID-19 outbreak based on system dynamics model analysis.

To explore early prevention and control of coronavirus disease 2019 （COVID-19） outbreak based on system dynamics model analysis. The data of early outbreak of COVID-19 were collected from the World Health Organization，covering countries of the China，United States，United Kingdom，Australia，Serbia and Italy. The susceptible-exposed-infected-recovered （SEIR） model was generalized and then its parameters were optimized. According to the parameters in the basic infection number expression，the sensitivity in the system dynamics model was used to quantitatively analyze the influence of the protection rate，infection rate and average quarantine time on the early spread of the outbreak. Based on the analysis results，targeted prevention and control measures for the early outbreak of COVID-19 were proposed. The generalized SEIR model had a good fit for the early prediction and evaluation of COVID-19 outbreaks in six countries. The spread of COVID-19 was mainly affected by the protection rate，infection rate and average quarantine time. The improvement of the protection rate in the first ays was the most important:the greater the protection rate，the fewer the number of confirmed cases. The infection rate in the first 5 days was the most critical:the smaller the infection rate，the fewer the number of confirmed cases. The average quarantine time in the first 5 days was very important:the shorter the average quarantine time，the fewer the number of confirmed cases. Through the comparison of key parameters of six countries，Australia and China had implemented strict epidemic prevention policies，which had resulted in good epidemic prevention effects. In the early stage of the outbreak，it is necessary to improve the protection rate，shorten the average quarantine time，and implement strict isolation policies to curb the spread of COVID-19.

[Routine Epidemic Prevention and Control and Treatment Process Reengineering of Outpatient Dental Care].

The coronavirus disease 2019 (COVID-19) pandemic is the most severe global public health emergency in over a hundred years. We have collected and organized prevention and control information from China and other counties and used it as an important reference for designing routine epidemic prevention and control measures and treatment process reengineering of outpatient dental services. Suggestions are made in the following aspects: standard precaution is adopted for all patients based on situational risk assessment conducted by the medical staffs; transmission-based precautions are adopted in addition while caring for patients who are suspected of or have been confirmed of having infectious diseases, in which scenario, standard precautions may not be enough; regarding clinical services, the triage process should be further improved, clinical service delivery areas should be redesigned to maximize safe distances, minimally invasive dentistry procedures should be prioritized for treatment, and postponement of treatment should be recommended appropriately; infection prevention and control guidelines should be regularly updated and relevant trainings provided to the medical staffs accordingly; COVID-19 incidents associated with delivery of dental care should be documented and evaluated; it is also important to communicate with Chinese and international colleagues and stress research and professional training.

Prevention and control mechanism for coronavirus disease 2019 epidemic at the primary level: perspective from China.

After the 2003 SARS epidemic, China started constructing a primary-level emergency response system and focused on strengthening and implementation of policies, resource allocation. After 17 years of restructuring, China's primary-level response capabilities towards public health emergencies have greatly improved. During the coronavirus disease 2019 epidemic, primary-level administrative and medical personnel, social organisations, volunteers, etc. have played a significant role in providing professional services utilising the primary-level emergency response system of 17 years. However, China's organisations did not learn their lesson from the SARS epidemic, and certain problems are exposed in the system. By analysing the experience and shortcomings of China's disease prevention and control system at the primary level, we can focus on the development of disease control systems for major epidemics in the future.

Modeling COVID-19 infection in a confined space.

In this paper, we construct a stochastic model of the 2019-nCoV transmission in a confined space, which gives a detailed account of the interaction between the spreading virus and mobile individuals. Different aspects of the interaction at mesoscopic level, such as the human motion, the shedding and spreading of the virus, its contamination and invasion of the human body and the response of the human immune system, are touched upon in the model, their relative importance during the course of infection being evaluated. The model provides a bridge linking the epidemic statistics to the physiological parameters of individuals and may serve a theoretical guidance for epidemic prevention and control.

[Application of artificial intelligence in prevention and control of COVID-19 in Guangzhou city].

Since the outbreak of COVID-19, it has spread rapidly throughout the country and even in the world. As a first tier city, Guangzhou is also the South Gate of China, with large population mobility and severe and complex prevention and control situation. Guangzhou CDC, together with Tencent and Alibaba Cloud, has made full use of its artificial intelligence technology to carry out a series of practices in case transmission chain analysis, close contact and other key personnel management, front-line staff prevention and control skills training and convenience services. Through the application of artificial intelligence in different scenarios, the difficulties and challenges in the prevention and control are solved, and the speed of epidemic prevention and control is increased.

[Epidemiology, Treatment, and Epidemic Prevention and Control of the Coronavirus Disease 2019: a Review].

This review summarizes the ongoing researches regarding etiology, epidemiology, transmission dynamics, treatment, and prevention and control strategies of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with comparison to severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and pandemic H1N1 virus. SARS-CoV-2 may be originated from bats, and the patients and asymptomatic carriers are the source of epidemic infection. The virus can be transmitted human-to-human through droplets and close contact, and people at all ages are susceptible to this virus. The main clinical symptoms of the patients are fever and cough, accompanied with leukocytopenia and lymphocytopenia. Effective drugs have been not yet available thus far. In terms of the prevention and control strategies, vaccine development as the primary prevention should be accelerated. Regarding the secondary prevention, ongoing efforts of the infected patients and close contacts quarantine, mask wearing promotion, regular disinfection in public places should be continued. Meanwhile, rapid detection kit for serological monitoring of the virus in general population is expected so as to achieve early detection, early diagnosis, early isolation and early treatment. In addition, public health education on this disease and prevention should be enhanced so as to mitigate panic and mobilize the public to jointly combat the epidemic.

[Research on coronavirus disease 2019 field disinfection technology for prevention and control].

The coronavirus disease 2019 (COVID-19) epidemic has had a serious impact in the world. In the absence of vaccines and therapeutic drugs, disinfection has become an important technical means to block the spread of the virus. By analyzing the characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we studied a series of disinfection technologies for COVID-19. During the outbreak of COVID-19, Jinan Second Center for Disease Control and Prevention disinfected the houses of the cases to be investigated in a community. The effectiveness of the disinfection technology was verified through the process of disinfection preparation, sampling before disinfection, field disinfection, sampling after disinfection and evaluation of disinfection effect. Compared the data before and after disinfection, the killing rate of the total bacterial colonies in the air and on the surface of the object was more than or equal to 90%, and no SARS-CoV-2 was detected after disinfection. The results show that the disinfection effect of the disinfection technology meets the standard. Finally, through the analysis of the wrong way of disinfection and the harm of over disinfection, the importance of scientific disinfection and precise disinfection are emphasized, and the research has a good guiding value for prevention and control of the epidemic.

Systematic Research and Application of a 5G Medical Unmanned Aerial Vehicle to Deliver COVID-19 Nucleic Acid Samples.

The purpose of this study was to investigate the feasibility and effectiveness of COVID-19 throat swab samples delivered by medical drones in epidemic prevention and control. This study was carried out in both southern and northern hospital districts of the Affiliated Hospital of Jiangnan University from May to October 2022. The main participants were the Affiliated Hospital of Jiangnan University and Zhejiang Antwork Technology Co., Ltd. We first constructed an urban medical unmanned aerial vehicle (UAV) delivery system and developed a UAV-specific storage box for COVID-19 samples. The UAV system was used to transport COVID-19 throat swab samples from the northern hospital district to the southern hospital district, and the following indexes were obtained: (1) flight time of COVID-19 samples delivered by UAV, (2) real-time temperature of COVID-19 nucleic acid samples during transportation, and (3) the time of distribution of COVID-19 nucleic acid samples by road traffic as measured using the Baidu Maps application, compared with the flight time of UAV. The COVID-19 sample delivery system for urban medical UAV mainly consists of intelligent logistics UAV, low-temperature COVID-19 throat swab sample storage box, unmanned logistics hub, and cloud operation control platform. The flight distance between the northern and southern districts of the Affiliated Hospital of Jiangnan University was 10 km, and the ground distance was 24 km. From May 11 to October 28, 2022, a total of 1,190 UAV flights occurred. The average flight time was 13 minutes, which was 40 to 70 minutes faster than the average road travel time required for manual delivery of COVID-19 throat swab samples. At different time points in the day, UAV delivery efficiency increased by 67.5% to 82%. The use of 5G with the Internet of Things and UAV technology to deliver nucleic acid samples has the characteristics of fast speed, being unaffected by ground traffic conditions, and the ability to ensure the safety of nucleic acid samples in the transportation process, which is worthy of further study.

Coordination and modularization: the experience of the joint prevention and control mechanism to COVID emergencies in China.

Background: The integration of disparate emergency resources and the improvement of emergency response teamwork are the underlying trends and shared requirements for building resilience in an era of multiple global public health crises. Objective: This study investigated the emergency response with emergency collaboration networks of each functional module and the overall Joint Epidemic Prevention and Control Mechanism (JPCM) network in China's COVID outbreak prevention and control. Methods: The study employed a scholarly framework of "the integration of JPCM coordination and emergency collaborative modularization" to explore the attributes of JPCM using social network analysis. The data were obtained from administrative records from JPCM's official website, spanning January 2020 to December 2022. Results: The study examined the JPCM coordination and found several functional working modules of JPCM, such as Interrupt Spread, Manage Supply, Medical Rescue, Restore Work and Production, and Implement Responsibility modules. The network structure indicators showed that the Manage Supply module had the most extensive network connectivity, the shortest communication distance, and the most consistent collaboration. The E-I index of the overall JPCM network and the Manage Supply network were - 0.192 and - 0.452, respectively (at p < 0.001 and p < 0.05), indicating more internal relationships than external relationships. The E-I index of the Medical Rescue and Implement Responsibility collaboration networks were 0.122 and 0.147, respectively (at p < 0.001 and p < 0.05), indicating more external relationships than internal relationships. The QAP regression analysis showed that the most vital driver on the overall JPCM network was the Interrupt Spread module, followed by the Implement Responsibility and Medical Rescue modules. Discussion: The Interrupt Spread module initiated emergency coordination with most departments and agencies. The Manage Supply module ensured the flow of medical supplies and survival essentials, while the Medical Rescue module addressed the core aspects of the health emergency response. The Restore Work and Production module repaired the halt in production and livelihoods caused by the outbreak, strengthening and developing emergency coordination and roles across emergency organizations. The Implement Responsibility module provided more heterogeneous emergency response resources for the overall JPCM coordination, complementing the COVID cross-organizational emergency response coordination. Conclusion: The study on the JPCM case in China improves public health emergency management and aids informed decision-making.

Modeling and analysis of a tourism supply chain considering service level and advertising in the context of regular epidemic prevention and control under COVID-19.

In the context of regular epidemic prevention and control, this paper considers a two-stage tourism supply chain consisting of a scenic spot that attracts tourists through advertising and a travel agency that invests in service improvement and epidemic prevention. By establishing theoretical game models of a tourism supply chain, we investigate how the service level and advertising level can affect the retail price, product service level, and profits of the supply chain. The results show that the service level of travel agencies could improve consumers' preferences, expand the market demand for tourism products, and improve the efficiency of the supply chain to achieve a win-win situation and increase the profits of the scenic spot and the travel agency. The retailer price, service level, promotion level, and supply chain profit all increase as the service coefficient and advertising coefficient increase, and the speed of the increase is higher for the centralized model than for other models. Some valuable information could be provided for supply chain enterprises to develop collaborative strategies and promote tourism supply chain management practices.