Thermodynamic imaging calculation model on COVID-19 transmission and epidemic cities risk level assessment-data from Hubei in China.

Novel coronavirus pneumonia in 17 city (Hubei) provinces was analyzed by using the principle of thermodynamics. A thermodynamic imaging model of infectious diseases was established to calculate the cumulative superimposed density of epidemic in 17 cities (prefectures). An evaluation rule of urban risk grade is established and evaluates the COVID-19 risk of 17 cities. The results show that (1) the higher the superimposed density of urban epidemic, the more infected people. (2) In the incubation stage, the thermodynamic imaging shows a point distribution, random walk, and outward diffusion trend. In the initial stage, the color of thermodynamic imaging gradually deepened and the range gradually expanded. During the burst stage, the thermodynamic imaging color deepens rapidly and the scope expands rapidly. In the stable stage, the thermodynamic imaging color becomes darkest and the range is extended to the pole. (3) According to the situation of COVID-19 transmission in Hubei Province, the cumulative superimposed density of Wuhan epidemic is far more than 10,000, ranking as "highest-risk." Xiaogan and other 10 cities have a cumulative superimposed density within the range of [1000, 10,000], ranking as "high-risk." Shiyan and other 5 cities have accumulated superimposed density values within the range of [100, 1000], ranking as "medium-risk." Shennongjia cumulative superimposed density value is less than 100, and the level is "low-risk."

The early warning research on nursing care of stroke patients with intelligent wearable devices under COVID-19.

Stroke patients under the background of the new crown epidemic need to be home-based care. However, traditional nursing methods cannot take care of the patients' lives in all aspects. Based on this, based on machine learning algorithms, our work combines regression models and SVM to build a smart wearable device system and builds a system prediction module to predict patient care needs. The node is used to collect human body motion and physiological parameter information and transmit data wirelessly. The software is used to quickly process and analyze the various motion and physiological parameters of the patient and save the analysis and processing structure in the database. By comparing the results of nursing intervention experiments, we can see that the smart wearable device designed in this paper has a certain effect in stroke care.

Development of Effective PEDV Vaccine Candidates Based on Viral Culture and Protease Activity.

Porcine epidemic diarrhea (PED) is a highly contagious disease that has been reported annually in several Asian countries, causing significant economic losses to the swine livestock industry. Although vaccines against the porcine epidemic diarrhea virus (PEDV) are available, their efficacy remains questionable due to limitations such as viral genome mutation and insufficient intestinal mucosal immunity. Therefore, the development of a safe and effective vaccine is necessary. In this study, a virulent Korean strain of PEDV, CKT-7, was isolated from a piglet with severe diarrhea, and six different conditions were employed for serial passage of the strain in a cell culture system to generate effective live attenuated vaccine (LAV) candidates. The characteristics of these strains were analyzed in vitro and in vivo, and the CKT-7 N strain was identified as the most effective vaccine candidate, with a viral titer peak of 8.67 ± 0.29 log10TCID50/mL, and no mortality or diarrhea symptoms were observed in five-day-old piglets. These results indicate that LAV candidates can be generated through serial passage with different culture conditions and provide valuable insights into the development of a highly effective LAV against PEDV.

Time delay of the appearance of a new strain can affect vaccination behavior and disease dynamics: An evolutionary explanation.

The emergence of a novel strain during a pandemic, like the current COVID-19, is a major concern to the healthcare system. The most effective strategy to control this type of pandemic is vaccination. Many previous studies suggest that the existing vaccine may not be fully effective against the new strain. Additionally, the new strain's late arrival has a significant impact on the disease dynamics and vaccine coverage. Focusing on these issues, this study presents a two-strain epidemic model in which the new strain appears with a time delay. We considered two vaccination provisions, namely preinfection and postinfection vaccinations, which are governed by human behavioral dynamics. In such a framework, individuals have the option to commit vaccination before being infected with the first strain. Additionally, people who forgo vaccination and become infected with the first train have the chance to be vaccinated (after recovery) in an attempt to avoid infection from the second strain. However, a second strain can infect vaccinated and unvaccinated individuals. People may have additional opportunities to be vaccinated and to protect themselves from the second strain due to the time delay. Considering the cost of the vaccine, the severity of the new strain, and the vaccine's effectiveness, our results indicated that delaying the second strain decreases the peak size of the infected individuals. Finally, by estimating the social efficiency deficit, we discovered that the social dilemma for receiving immunization decreases with the delay in the arrival of the second strain.

Threshold conditions for curbing COVID-19 with a dynamic zero-case policy derived from 101 outbreaks in China.

By 31 May 2022, original/Alpha, Delta and Omicron strains induced 101 outbreaks of COVID-19 in mainland China. Most outbreaks were cleared by combining non-pharmaceutical interventions (NPIs) with vaccines, but continuous virus variations challenged the dynamic zero-case policy (DZCP), posing questions of what are the prerequisites and threshold levels for success? And what are the independent effects of vaccination in each outbreak? Using a modified classic infectious disease dynamic model and an iterative relationship for new infections per day, the effectiveness of vaccines and NPIs was deduced, from which the independent effectiveness of vaccines was derived. There was a negative correlation between vaccination coverage rates and virus transmission. For the Delta strain, a 61.8% increase in the vaccination rate (VR) reduced the control reproduction number (CRN) by about 27%. For the Omicron strain, a 20.43% increase in VR, including booster shots, reduced the CRN by 42.16%. The implementation speed of NPIs against the original/Alpha strain was faster than the virus's transmission speed, and vaccines significantly accelerated the DZCP against the Delta strain. The CRN ([Formula: see text]) during the exponential growth phase and the peak time and intensity of NPIs were key factors affecting a comprehensive theoretical threshold condition for DZCP success, illustrated by contour diagrams for the CRN under different conditions. The DZCP maintained the [Formula: see text] of 101 outbreaks below the safe threshold level, but the strength of NPIs was close to saturation especially for Omicron, and there was little room for improvement. Only by curbing the rise in the early stage and shortening the exponential growth period could clearing be achieved quickly. Strengthening China's vaccine immune barrier can improve China's ability to prevent and control epidemics and provide greater scope for the selection and adjustment of NPIs. Otherwise, there will be rapid rises in infection rates and an extremely high peak and huge pressure on the healthcare system, and a potential increase in excess mortality.

Clinical Profile and Outcomes of Epidemic Dropsy Patients Attending a Tertiary Care Centre in Assam, India.

Background The clinical condition of epidemic dropsy is caused by the consumption of edible oils contaminated with Argemone mexicana oil. Two of the most toxic alkaloids found in argemone oil are sanguinarine and dehydrosanguinarine, which cause capillary dilation, proliferation, and increased permeability. Extreme cardiac decompensation leading to congestive heart failure and glaucoma resulting in blindness are the most serious consequences of epidemic dropsy.  Materials and methods All patients attending the medicine department of Tezpur Medical College and Hospital with clinical features of epidemic dropsy were included in the study after obtaining informed consent. All patients, after a complete history, underwent a thorough clinical examination, and findings were recorded using a pre-formed proforma. Along with routine blood examination, patients were also evaluated with echocardiography, ECG, and chest X-ray. Cooking oil samples obtained from patients were investigated for the presence of sanguinarine in a standardized laboratory with the help of the district authority. The statistical analysis was done using MS Excel 2017. Results Out of 38 patients, 36 were male (94.7%), and only two were female (5.2%). Male to female ratio was 18:1. This difference in sex ratio may be due to the fact that only severely ill patients attended our tertiary care hospital. In contrast, moderate and mildly ill patients were treated in local hospitals. The mean age of patients was 28.1 years, and the mean length of hospital stay was eight days. Bilateral pitting type of ankle edema was the most common clinical manifestation, and all 38 patients (100%) exhibited edema. A total of 76% of patients had dermatological manifestations. Sixty-two percent of patients had gastrointestinal manifestations. In cardiovascular manifestation, persistent tachycardia was seen in 52% of patients, pansystolic murmur was best heard in the apical area in 42% of patients, and 21 percent had evidence of a raised jugular venous pressure (JVP). Five percent of patients had pleural effusion. Sixteen percent of patients had ophthalmological manifestations. Eight patients (21%) required ICU care. The in-hospital fatality rate was 10.53% (n=4). Of the expired patients, 100% were male. The most common cause of death was cardiogenic shock (75%), followed by septic shock (25%). Conclusion From our study, it was found that most of the patients were male, with an age group of 25-45 years. The most common clinical manifestation was dependent edema, along with signs of heart failure. Other common manifestations were dermatological and gastrointestinal. The severity and outcome were directly related to the delay in seeking medical consultation and diagnosis.

Analysis and Prediction of COVID-19 Multivariate Data Using Deep Ensemble Learning Methods.

The global economy has suffered losses as a result of the COVID-19 epidemic. Accurate and effective predictive models are necessary for the governance and readiness of the healthcare system and its resources and, ultimately, for the prevention of the spread of illness. The primary objective of the project is to build a robust, universal method for predicting COVID-19-positive cases. Collaborators will benefit from this while developing and revising their pandemic response plans. For accurate prediction of the spread of COVID-19, the research recommends an adaptive gradient LSTM model (AGLSTM) using multivariate time series data. RNN, LSTM, LASSO regression, Ada-Boost, Light Gradient Boosting and KNN models are also used in the research, which accurately and reliably predict the course of this unpleasant disease. The proposed technique is evaluated under two different experimental conditions. The former uses case studies from India to validate the methodology, while the latter uses data fusion and transfer-learning techniques to reuse data and models to predict the onset of COVID-19. The model extracts important advanced features that influence the COVID-19 cases using a convolutional neural network and predicts the cases using adaptive LSTM after CNN processes the data. The experiment results show that the output of AGLSTM outperforms with an accuracy of 99.81% and requires only a short time for training and prediction.

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends.

Introduction: Large-scale diagnostic testing has been proven insufficient to promptly monitor the spread of the Coronavirus disease 2019. Electronic resources may provide better insight into the early detection of epidemics. We aimed to retrospectively explore whether the Google search volume has been useful in detecting Severe Acute Respiratory Syndrome Coronavirus outbreaks early compared to the swab-based surveillance system. Methods: The Google Trends website was used by applying the research to three Italian regions (Lombardy, Marche, and Sicily), covering 16 million Italian citizens. An autoregressive-moving-average model was fitted, and residual charts were plotted to detect outliers in weekly searches of five keywords. Signals that occurred during periods labelled as free from epidemics were used to measure Positive Predictive Values and False Negative Rates in anticipating the epidemic wave occurrence. Results: Signals from "fever," "cough," and "sore throat" showed better performance than those from "loss of smell" and "loss of taste." More than 80% of true epidemic waves were detected early by the occurrence of at least an outlier signal in Lombardy, although this implies a 20% false alarm signals. Performance was poorer for Sicily and Marche. Conclusion: Monitoring the volume of Google searches can be a valuable tool for early detection of respiratory infectious disease outbreaks, particularly in areas with high access to home internet. The inclusion of web-based syndromic keywords is promising as it could facilitate the containment of COVID-19 and perhaps other unknown infectious diseases in the future.

Investigation of variants in genetics and virulence of Porcine Epidemic Diarrhea Virus after serial passage on Vero cells.

Porcine epidemic diarrhea virus (PEDV) is a highly contagious intestinal virus. However, the current PEDV vaccine, which is produced from classical strain G1, offers low protection against recently emerged strain G2. This study aims to develop a better vaccine strain by propagating the PS6 strain, a G2b subgroup originating from Vietnam, on Vero cells until the 100th passage. As the virus was propagated, its titer increased, and its harvest time decreased. Analysis of the nucleotide and amino acid variation of the PS6 strain showed that the P100PS6 had 11, 4, and 2 amino acid variations in the 0 domain, B domain, and ORF3 protein, respectively, compared to the P7PS6 strain. Notably, the ORF3 gene was truncated due to a 16-nucleotide deletion mutation, resulting in a stop codon. The PS6 strain's virulence was evaluated in 5-day-old piglets, with P7PS6 and P100PS6 chosen for comparison. The results showed that P100PS6-inoculated piglets exhibited mild clinical symptoms and histopathological lesions, with a 100% survival rate. In contrast, P7PS6-inoculated piglets showed rapid and typical clinical symptoms of PEDV infection, and the survival rate was 0%. Additionally, the antibodies (IgG and IgA) produced from inoculated piglets with P100PS6 bound to both the P7PS6 and P100PS6 antigens. This finding suggested that the P100PS6 strain was attenuated and could be used to develop a live-attenuated vaccine against highly pathogenic and prevalent G2b-PEDV strains.

Opioid prescriptions and patients' health services utilization and cost before and during the COVID-19 pandemic: an exploratory population-based administrative data analysis.

The objective was to explore percentages of the population treated with prescribed opioids and costs of opioid-related hospitalizations and emergency department (ED) visits among individuals treated with prescription opioids and costs of all opioid-related hospitalizations and ED visits in the province (i.e., provincial costs) before and during the coronavirus disease 2019 (COVID-19) pandemic in Alberta, Canada. In administrative data, we identified individuals treated with prescription opioids and opioid-related hospitalizations and ED visits among those individuals and among all individuals in the province between 2015/16 and 2021/22 fiscal years. Services used were counted on an item-by-item basis and costed using case-mix approaches. Annually, from 9.98% (2020/21-2021/22) to 14.52% (2017/18) of the provincial population was treated with prescription opioids. Between 2015/16 and 2021/22, annual costs of opioid-related hospitalizations and ED visits among individuals treated with prescription opioids were ∼$5 and ∼$2 million, respectively. In 2020/21-2021/22, the provincial costs of opioid-related hospitalizations (∼$14 million) and ED visits (∼$7.0 million) were almost twice the costs observed in 2015/16 and immediately before the pandemic (2019/20). Our findings suggest that increases in the opioid-related utilization of inpatient and ED services between 2015/16 and 2021/22, including the drastic increases observed during the COVID-19 pandemic, were likely driven by unregulated substances.

The Effect of Fangcang Shelter Hospitals under Resource Constraints on the Spread of Epidemics.

Since the outbreak of the COVID-19 pandemic, Fangcang shelter hospitals have been built and operated in several cities, and have played a huge role in epidemic prevention and control. How to use medical resources effectively in order to maximize epidemic prevention and control is a big challenge that the government should address. In this paper, a two-stage infectious disease model was developed to analyze the role of Fangcang shelter hospitals in epidemic prevention and control, and examine the impact of medical resources allocation on epidemic prevention and control. Our model suggested that the Fangcang shelter hospital could effectively control the rapid spread of the epidemic, and for a very large city with a population of about 10 million and a relative shortage of medical resources, the model predicted that the final number of confirmed cases could be only 3.4% of the total population in the best case scenario. The paper further discusses the optimal solutions regarding medical resource allocation when medical resources are either limited or abundant. The results show that the optimal allocation ratio of resources between designated hospitals and Fangcang shelter hospitals varies with the amount of additional resources. When resources are relatively sufficient, the upper limit of the proportion of makeshift hospitals is about 91%, while the lower limit decreases with the increase in resources. Meanwhile, there is a negative correlation between the intensity of medical work and the proportion of distribution. Our work deepens our understanding of the role of Fangcang shelter hospitals in the pandemic and provides a reference for feasible strategies by which to contain the pandemic.

The effect of the social support on PTSD and PTG about university student volunteers in the prevention and controlling of coronavirus: with coping style as the intermediary.

To investigate the relationship among post-traumatic stress disorder (PTSD), posttraumatic growth (PTG), social support, and coping style of university student volunteers in the prevention and control of the coronavirus in 2020, a total of 2,990 university student volunteers (students who are enrolled in a university and involved in volunteer activities) from 20 universities in Sichuan Province participated in the prevention and control of the epidemic were investigated when March 20-31, 2020 when the coronavirus first occurred using the post-traumatic stress disorder questionnaire, posttraumatic growth questionnaire, university student social support questionnaire and coping style questionnaire. The results showed that (1) 7.06% of university student volunteers had some degree of PTSD symptoms (the total PCL-C score was 38-49), and 2.88% had obvious PTSD symptoms, (2) PTSD level of university student volunteers was significantly positively correlated with negative coping style, and significantly negatively correlated with social support and positive coping style; on the contrary, the PTG level is significantly positively correlated with social support and positive coping styles, and (3) Positive coping style plays a partial mediating role in the influence of social support on PTG; in the influence of social support on PTSD, the mediating effect of positive or negative coping style was not significant. These results show that in the prevention and control of the coronavirus, the positive coping style and social support of university student volunteers can positively predict the PTG level of them, while the negative coping style can positively predict the severity of their PTSD symptoms. Among them, a positive coping style plays a partial mediating role in the influence of social support on the PTG level.

A survey of epidemic management data models.

The COVID-19 epidemic has demonstrated the important role that data plays in the response to and management of public health emergencies. It has also heightened awareness of the role that ontologies play in the design of semantically precise data models that improve data interoperability among stakeholders. This paper surveys vocabularies and ontologies relevant to the task of achieving epidemic-related data interoperability. The paper first reviews 16 vocabularies and ontologies with respect to the use cases. Next it identifies patterns of knowledge that are common across multiple vocabularies and ontologies, followed by an analysis of patterns that are missing, based on the use cases. Conclusions show that existing vocabularies and ontologies provide significant coverage of the concepts underlying epidemic use cases, but there remain gaps in the coverage. More work is required to cover missing but significant concepts.

V for vaccines and variants.

In the context of the Covid-19 pandemic, we evaluate the effects of vaccines and virus variants on epidemiological and macroeconomic outcomes by means of Monte Carlo simulations of a macroeconomic-epidemiological agent-based model calibrated using data from the Lombardy region of Italy. From simulations we infer that vaccination plays the role of a mitigating factor, reducing the frequency and the amplitude of contagion waves and significantly improving macroeconomic performance with respect to a scenario without vaccination. The emergence of a variant, on the other hand, plays the role of an accelerating factor, leading to a deterioration of both epidemiological and macroeconomic outcomes and partly negating the beneficial impacts of the vaccine. A new and improved vaccine in turn can redress the situation. Vaccinations and variants, therefore, can be conceived of as drivers of an intertwined cycle impacting both epidemiological and macroeconomic developments.

Effects of safety attitude on factors related to burnout among nurses working at a dedicated infectious disease control hospital during the COVID-19 pandemic.

AIM: Repeated occupational exposure and increased stress and fatigue levels contribute to a high risk of coronavirus disease 2019 (COVID-19) infection among frontline nurses. This study aimed to explore the relationships among teamwork, work environment and resources, work-life balance, stress perception and burnout among nurses working at a dedicated infectious disease control hospital. METHODS: The participants were 389 nurses at a dedicated infectious disease control hospital in Taipei City, Taiwan. This study adopted survey design with a questionnaire using the Safety Attitude Questionnaire. RESULTS: The work-life balance among nurses at the dedicated hospital significantly mediated the effects of teamwork and work environment and resources on burnout. In addition, stress perception had interaction effects on work-life balance and burnout. CONCLUSION: This study's results provide important recommendations for managing teamwork, work environment and resources, work-life balance, stress perception and burnout prevention in nurses to help them better prepare and cope with emergencies. Findings can serve as a reference for developing relevant hospital management policies.

An adaptive testing strategy for efficient utilization of healthcare resources during an epidemic.

Lockdowns are found to be effective against rapidly spreading epidemics like COVID-19. Two downsides to strategies rooted in social distancing and lockdowns are that they adversely affect the economy and prolong the duration of the epidemic. The extended duration observed in these strategies is often due to the under-utilization of medical facilities. Even though an under-utilized health care system is preferred over an overwhelmed one, an alternate strategy could be to maintain medical facilities close to their capacity, with a factor of safety. We explore the practicality of this alternate mitigation strategy and show that it can be achieved by varying the testing rate. We present an algorithm to calculate the number of tests per day to maintain medical facilities close to their capacity. We illustrate the efficacy of our strategy by showing that it reduced the epidemic duration by 40% in comparison to lockdown-based strategies.

Supply Chain Risk Diffusion in Partially Mapping Double-Layer Hypernetworks.

The impact of COVID-19 is global, and uncertain information will affect product quality and worker efficiency in the complex supply chain network, thus bringing risks. Aiming at individual heterogeneity, a partial mapping double-layer hypernetwork model is constructed to study the supply chain risk diffusion under uncertain information. Here, we explore the risk diffusion dynamics, drawing on epidemiology, and establish an SPIR (Susceptible-Potential-Infected-Recovered) model to simulate the risk diffusion process. The node represents the enterprise, and hyperedge represents the cooperation among enterprises. The microscopic Markov chain approach (MMCA) is used to prove the theory. Network dynamic evolution includes two removal strategies: (i) removing aging nodes; (ii) removing key nodes. Using Matlab to simulate the model, we found that it is more conducive to market stability to eliminate outdated enterprises than to control key enterprises during risk diffusion. The risk diffusion scale is related to interlayer mapping. Increasing the upper layer mapping rate to strengthen the efforts of official media to issue authoritative information will reduce the infected enterprise number. Reducing the lower layer mapping rate will reduce the misled enterprise number, thereby weakening the efficiency of risk infection. The model is helpful for understanding the risk diffusion characteristics and the importance of online information, and it has guiding significance for supply chain management.

Management of centralized transition ward in a large general hospital in Shanghai during the epidemic caused by severe acute respiratory syndrome coronavirus 2 omicron variant infection.

The epidemic of coronavirus disease 2019 (COVID-19) has seriously affected people's normal work, life, and medical treatment. Since Mar. 2022, there has been a pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant in Shanghai. In order to meet the needs of hospitalization for patients, and at the same time for better control of epidemic and nosocomial infections, a large hospital in Shanghai innovatively set up a centralized transition ward in the hospital, and established scientific rules of medical work, regulations for prevention of nosocomial infections and efficient norms for patient admission. During the operation of the ward, a total of 211 patients were treated and one of the patients was confirmed of COVID-19 recurrence. All work was carried out methodically, and neither hospitalized patients nor medical staff had nosocomial infection of COVID-19. The preparation, operation and management of the central transition ward in our hospital are summarized here to provide guidance and reference for general hospitals to carry out similar work under the epidemic.Copyright © 2022, Second Military Medical University Press. All rights reserved.

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).

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.