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As COVID-19 poses a major threat to people's health and economy, there is an urgent need for forecasting methodologies that can anticipate its trajectory efficiently. In non-stationary time series forecasting jobs, there is frequently a hysteresis in the anticipated values relative to the real values. The multilayer deep-time convolutional network and a feature fusion network are combined in this paper's proposal of an enhanced Multilayer Deep Time Convolutional Neural Network (MDTCNet) for COVID-19 prediction to address this problem. In particular, it is possible to record the deep features and temporal dependencies in uncertain time series, and the features may then be combined using a feature fusion network and a multilayer perceptron. Last but not least, the experimental verification is conducted on the prediction task of COVID-19 real daily confirmed cases in the world and the United States with uncertainty, realizing the short-term and long-term prediction of COVID-19 daily confirmed cases, and verifying the effectiveness and accuracy of the suggested prediction method, as well as reducing the hysteresis of the prediction results.
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Geographic information systems (GIS) and choropleth maps for COVID-19 cases as well as COVID-19 test and vaccination rates proved very valuable to informing decision-making on the local and regional levels of government in Shelby County, Tennessee, USA. The authors have all served on the City of Memphis and Shelby County COVID Joint Task Force and share here their observations about the challenges and promises related to these techniques in the context of a fast-changing environment. As the pandemic unfolded, new virus variants emerged and the population became increasingly vaccinated. Consequently, the use of GIS changed, and maps needed to be continually adapted to the shifting needs of decision makers. The authors describe their approaches to leveraging GIS techniques to monitor the spread of the disease, draw conclusions about the effect of policy measures, and address health disparities. They outline the strengths and weaknesses of choropleth maps, reflect on how best to facilitate interorganizational communication of the derived information, and suggest desirable aspects of educational courses for GIS as well as skill sets in personnel that they came to appreciate as essential. © 2023 Taylor and Francis Group, LLC.
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Accurately estimating land-use demand is essential for urban models to predict the evolution of urban spatial morphology. Due to the uncertainties inherent in socioeconomic development, the accurate forecasting of urban land-use demand remains a daunting challenge. The present study proposes a modeling framework to determine the scaling relationship between the population and urban area and simulates the spatiotemporal dynamics of land use and land cover (LULC). An allometric scaling (AS) law and a Markov (MK) chain are used to predict variations in LULC. Random forest (RF) and cellular automata (CA) serve to calibrate the transition rules of change in LULC and realize its micro-spatial allocation (MKCA(RF-AS)). Furthermore, this research uses several shared socioeconomic pathways (SSPs) as scenario storylines. The MKCA(RF-AS) model is used to predict changes in LULC under various SSP scenarios in Jinjiang City, China, from 2020 to 2065. The results show that the figure of merit (FoM) and the urban FoM of the MKCA(RF-AS) model improve by 3.72% and 4.06%, respectively, compared with the MKCA(ANN) model during the 2005-2010 simulation period. For a 6.28% discrepancy between the predicted urban land-use demand and the actual urban land-use demand over the period 2005-2010, the urban FoM degrades by 21.42%. The growth of the permanent urban population and urban area in Jinjiang City follows an allometric scaling law with an exponent of 0.933 for the period 2005-2020, and the relative residual and R-2 are 0.0076 and 0.9994, respectively. From 2020 to 2065, the urban land demand estimated by the Markov model is 19.4% greater than the urban area predicted under scenario SSP5. At the township scale, the different SSP scenarios produce significantly different spatial distributions of urban expansion rates. By coupling random forest and allometric scaling, the MKCA(RF-AS) model substantially improves the simulation of urban land use.
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Objective: To explore the guidance value of "treatment of disease in accordance with three conditions" theory in the prevention and treatment of corona virus disease 2019 (COVID-19) based on the differences of syndromes and traditional Chinese medicine (TCM) treatments in COVID-19 patients from Xingtai Hospital of Chinese Medicine of Hebei province and Ruili Hospital of Chinese Medicine and Dai Medicine of Yunnan province and discuss its significance in the prevention and treatment of the unexpected acute infectious diseases. Method(s): Demographics data and clinical characteristics of COVID-19 patients from the two hospitals were collected retrospectively and analyzed by SPSS 18.0. The information on formulas was obtained from the hospital information system (HIS) of the two hospitals and analyzed by the big data intelligent processing and knowledge service system of Guangdong Hospital of Chinese Medicine for frequency statistics and association rules analysis. Heat map-hierarchical clustering analysis was used to explore the correlation between clinical characteristics and formulas. Result(s): A total of 175 patients with COVID-19 were included in this study. The 70 patients in Xingtai, dominated by young and middle-aged males, had clinical symptoms of fever, abnormal sweating, and fatigue. The main pathogenesis is stagnant cold-dampness in the exterior and impaired yin by depressed heat, with manifest cold, dampness, and deficiency syndromes. The therapeutic methods highlight relieving exterior syndrome and resolving dampness, accompanied by draining depressed heat. The core Chinese medicines used are Poria, Armeniacae Semen Amarum, Gypsum Fibrosum, Citri Reticulatae Pericarpium, and Pogostemonis Herba. By contrast, the 105 patients in Ruili, dominated by young females, had atypical clinical symptoms, and most of them were asymptomatic patients or mild cases. The main pathogenesis is dampness obstructing the lung and the stomach, with obvious dampness and heat syndromes. The therapeutic methods are mainly invigorating the spleen, resolving dampness, and dispersing Qi with light drugs. The core Chinese medicines used are Poria, Atractylodis Macrocephalae Rhizoma, Glycyrrhizae Radix et Rhizoma, Coicis Semen, Platycodonis Radix, Lonicerae Japonicae Flos, and Pogostemonis Herba. Conclusion(s): The differences in clinical characteristics, TCM syndromes, and medication of COVID-19 patients from the two places may result from different regions, population characteristics, and the time point of the COVID-19 outbreak. The "treatment of disease in accordance with three conditions" theory can help to understand the internal correlation and guide the treatments.Copyright © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.
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Objective: To compare the efficacy of the combination of abidol, lopinavir/ritonavir plus recombinant interferon alpha-2b (rIFNalpha-2b) and the combination of lopinavir/ritonavir plus rIFNalpha-2b for patients with COVID-19 in Zhejiang province. Method(s): A multicenter prospective study was carried out to compare the efficacy of triple combination antiviral therapy and dual combination antiviral therapy in 15 medical institutions of Zhejiang province during January 22 to February 16, 2020. All patients were treated with rIFNalpha-2b (5 million U, 2 times/d) aerosol inhalation, in addition 196 patients were treated with abidol (200 mg, 3 times/d) + lopinavir/ritonavir (2 tablets, 1 time/12 h) (triple combination group) and 41 patients were treated with lopinavir/ritonavir (2 tablets, 1 time/12 h) (dual combination group). The patients who received triple combination antiviral therapy were further divided into three subgroups: <48 h, 3-5 d and >5 d according the time from the symptom onset to medication starting. The therapeutic efficacy was compared between triple combination group and dual combination group, and compared among 3 subgroups of patients receiving triple combination antiviral therapy. SPSS 17.0 software was used to analyze the data. Result(s): The virus nucleic acid-negative conversion time in respiratory tract specimens was (12.2+/-4.7) d in the triple combination group, which was shorter than that in the dual combination group [(15.0+/-5.0) d] (t=6.159, P<0.01). The length of hospital stay in the triple combination group [12.0 (9.0, 17.0) d] was also shorter than that in the dual combination group [15.0 (10.0, 18.0) d] (H=2.073, P<0.05). Compared with the antiviral treatment which was started within after the symptom onset of in the triple combination group, the time from the symptom onset to the viral negative conversion was 13.0 (10.0, 17.0), 17.0 (13.0, 22.0) and 21.0 (18.0, 24.0) d in subgroups of 48 h, 3-5 d and >5 d, respectively (Z=32.983, P<0.01), while the time from antiviral therapy to viral negative conversion was (11.8+/-3.9), (13.5+/-5.1) and (11.2+/-4.3) d, respectively(Z=6.722, P<0.05). Conclusion(s): The triple combination antiviral therapy of abidol, lopinavir/litonavir and rIFNalpha-2b shows shorter viral shedding time and shorter hospitalization time, compared with the dual combination antiviral therapy;and the earlier starting triple combination antiviral therapy will result in better antiviral efficacy.Copyright © 2020 by the Chinese Medical Association.
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Objective: To analyze the clinical features of patients with COVID-19 in Chongqing Municipality. Method(s): The clinical data, laboratory tests and chest imaging findings of 153 patients COVID-19 admitted in Chongqing Public Health Medical Center from January 26 to February 5, 2020 were retrospectively reviewed. According to the relevant diagnostic criteria, patients were divided into non-severe group (n=132) and severe group (n=21). The correlation between serum index changes and disease severity was analyzed. Result(s): The proportion of patients with underlying diabetes or chronic respiratory diseases in severe group was significantly higher than that in non-severe group (chi2=11.04 and 6.94, P<0.05). The proportion of symptom-free patients in non-severe group was significantly higher than that in severe group (chi2=4.09, P<0.05). The symptoms of fever, fatigue and muscle soreness in the severe group were more common than those in the non-severe group (chi2=4.40, 14.42 and 22.67, P<0.05). Among the concomitant symptoms, the proportion of cough and shortness of breath in the severe group was higher than that in the non-severe group (chi2=8.46 and 4.80, P<0.05). C-reactive protein and D-Dimer levels were higher in the severe group than those in the non-severe group (Z=-4.39 and -1.96, P<0.05), and the number of CD3+ T lymphocyte cells, CD4+ T lymphocyte cells and CD8+ T lymphocyte cells in the severe group was lower than that in the non-severe group (Z=27.25, 20.60 and 17.36, P<0.05). Compared with the non-severe group, both lungs and the right lung lower lobe were more susceptible to be involved(chi2=9.7123.61, P<0.05). Conclusion(s): There are significant differences in underlying diseases, clinical symptoms, imaging manifestations and laboratory findings between severe and non-severe patients with COVID-19.Copyright © 2020 by the Chinese Medical Association.
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With the growing importance of preventing the COVID-19 virus in cyber-manufacturing security, face images obtained in most video surveillance scenarios are usually low resolution together with mask occlusion. However, most of the previous face super-resolution solutions can not efficiently handle both tasks in one model. In this work, we consider both tasks simultaneously and construct an efficient joint learning network, called JDSR-GAN, for masked face super-resolution tasks. Given a low-quality face image with mask as input, the role of the generator composed of a denoising module and super-resolution module is to acquire a high-quality high-resolution face image. The discriminator utilizes some carefully designed loss functions to ensure the quality of the recovered face images. Moreover, we incorporate the identity information and attention mechanism into our network for feasible correlated feature expression and informative feature learning. By jointly performing denoising and face super-resolution, the two tasks can complement each other and attain promising performance. Extensive qualitative and quantitative results show the superiority of our proposed JDSR-GAN over some competitive methods. IEEE
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Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
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Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
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Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
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Objective: To compare the efficacy of the combination of abidol, lopinavir/ritonavir plus recombinant interferon alpha-2b (rIFNalpha-2b) and the combination of lopinavir/ritonavir plus rIFNalpha-2b for patients with COVID-19 in Zhejiang province. Method(s): A multicenter prospective study was carried out to compare the efficacy of triple combination antiviral therapy and dual combination antiviral therapy in 15 medical institutions of Zhejiang province during January 22 to February 16, 2020. All patients were treated with rIFNalpha-2b (5 million U, 2 times/d) aerosol inhalation, in addition 196 patients were treated with abidol (200 mg, 3 times/d) + lopinavir/ritonavir (2 tablets, 1 time/12 h) (triple combination group) and 41 patients were treated with lopinavir/ritonavir (2 tablets, 1 time/12 h) (dual combination group). The patients who received triple combination antiviral therapy were further divided into three subgroups: <48 h, 3-5 d and >5 d according the time from the symptom onset to medication starting. The therapeutic efficacy was compared between triple combination group and dual combination group, and compared among 3 subgroups of patients receiving triple combination antiviral therapy. SPSS 17.0 software was used to analyze the data. Result(s): The virus nucleic acid-negative conversion time in respiratory tract specimens was (12.2+/-4.7) d in the triple combination group, which was shorter than that in the dual combination group [(15.0+/-5.0) d] (t=6.159, P<0.01). The length of hospital stay in the triple combination group [12.0 (9.0, 17.0) d] was also shorter than that in the dual combination group [15.0 (10.0, 18.0) d] (H=2.073, P<0.05). Compared with the antiviral treatment which was started within after the symptom onset of in the triple combination group, the time from the symptom onset to the viral negative conversion was 13.0 (10.0, 17.0), 17.0 (13.0, 22.0) and 21.0 (18.0, 24.0) d in subgroups of 48 h, 3-5 d and >5 d, respectively (Z=32.983, P<0.01), while the time from antiviral therapy to viral negative conversion was (11.8+/-3.9), (13.5+/-5.1) and (11.2+/-4.3) d, respectively(Z=6.722, P<0.05). Conclusion(s): The triple combination antiviral therapy of abidol, lopinavir/litonavir and rIFNalpha-2b shows shorter viral shedding time and shorter hospitalization time, compared with the dual combination antiviral therapy;and the earlier starting triple combination antiviral therapy will result in better antiviral efficacy.Copyright © 2020 by the Chinese Medical Association.
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Objective: To analyze the clinical features of patients with COVID-19 in Chongqing Municipality. Method(s): The clinical data, laboratory tests and chest imaging findings of 153 patients COVID-19 admitted in Chongqing Public Health Medical Center from January 26 to February 5, 2020 were retrospectively reviewed. According to the relevant diagnostic criteria, patients were divided into non-severe group (n=132) and severe group (n=21). The correlation between serum index changes and disease severity was analyzed. Result(s): The proportion of patients with underlying diabetes or chronic respiratory diseases in severe group was significantly higher than that in non-severe group (chi2=11.04 and 6.94, P<0.05). The proportion of symptom-free patients in non-severe group was significantly higher than that in severe group (chi2=4.09, P<0.05). The symptoms of fever, fatigue and muscle soreness in the severe group were more common than those in the non-severe group (chi2=4.40, 14.42 and 22.67, P<0.05). Among the concomitant symptoms, the proportion of cough and shortness of breath in the severe group was higher than that in the non-severe group (chi2=8.46 and 4.80, P<0.05). C-reactive protein and D-Dimer levels were higher in the severe group than those in the non-severe group (Z=-4.39 and -1.96, P<0.05), and the number of CD3+ T lymphocyte cells, CD4+ T lymphocyte cells and CD8+ T lymphocyte cells in the severe group was lower than that in the non-severe group (Z=27.25, 20.60 and 17.36, P<0.05). Compared with the non-severe group, both lungs and the right lung lower lobe were more susceptible to be involved(chi2=9.7123.61, P<0.05). Conclusion(s): There are significant differences in underlying diseases, clinical symptoms, imaging manifestations and laboratory findings between severe and non-severe patients with COVID-19.Copyright © 2020 by the Chinese Medical Association.
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CT is an important imaging tool for the diagnosis of novel coronavirus pneumonia (COVID-19), therefore, it's necessary to strictly control the disinfection of CT workplace and equipment and biosafety to avoid the place from becoming a potential infection source and to reduce the risk of infection of patients and radiological staff. It is also necessary to reduce the CT scan dose to minimize the radiation hazards on patients under the premise of ensuring the CT image quality and diagnostic efficiency. Based on the survey that novel coronavirus residues after disinfection at some CT workplace in domestic and overseas and the application of low-dose CT scan in diagnosis of COVID-19, as well as the current situation of radiological protection management in emergency hospital, this paper summarizes and proposes suggestions on infection control and radiological protection for CT workplace to strengthen the defense line of COVID-19 prevention and control.Copyright © 2021 by the Chinese Medical Association.
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Objective: To survey and supervise the risk of infection control and radiation safety in the radiological diagnostic workplace for COVID-19, and provide data support for the safety protection of radiographers and related staff. Method(s): 4 emergency hospitals for COVID-19 including 2 makeshift hospitals, module hospital and brick pattern hospital in Hubei province were performed for testing and evaluation of imaging performance and radiological protection for the 8 new installed CT scanners and places according to the national standards of WS 519-2019 and GBZ 130-2013. The infection control safety factors such as the layout of the equipment room were monitored and investigated. Two COVID-19 designated hospitals including general hospital and infectious disease specialized hospital were selected to carry out field investigation and sampling of environmental biological samples for 4 CT rooms. Then the samples were detected for the nucleic acid of novel coronavirus. The results of radiodiagnostic workplace overall arrangement, infection prevention and the nucleic acid testing were analyzed, and the biological safety reliability and risk point were evaluated. Result(s): The indicators of imaging performance and radiation protection for 8 CT scanners in emergency hospitals could meet the requirements of national standards.Each of 2 makeshift hospitals had 3 CT rooms with the area of 38.8 m2 and 4 mm Pb equivalent thickness of protective shielding. The CT rooms in module hospital and brick pattern hospital were 20.0 m2, and 35.8 m2 in areas, with 4 mm Pb equivalent and 3 mm Pb equivalent thickness of protection shielding, respectively. The 8 radiological diagnostic workplaces of the emergency hospitals were designed and constructed based on " three zones with two passage ways". The result of the nucleic acid test indicated that the positive samples were found at the multiple sites such as scanning bed, internal of gantry and ground touched by patients in CT scanning room. The areas such as console panel and ground were risked of pollution by the virus infected hands and feet of radiographers. In addition, the similar positive samples were found in the areas in scanning room with no touch of patients, such as observation window and air outlet. Conclusion(s): 8 CT scanners and rooms in 4 emergency hospitals basically meet the requirements of imaging performance and radiation protection. The disinfection of COVID-19 radiodiagnostic workplace should be standardized.Copyright © 2020 by the Chinese Medical Association.
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Purpose: This study aims at the sudden outbreak of COVID-19, which had an unprecedented negative impact on the Chinese economy, with firms being affected most. Firms differ in terms of their specific internal environment, shaping their ability to respond to the outbreak, so the impact may also vary. Design/methodology/approach: In this paper Chinese listed firms are selected as samples to investigate the mediating effect of prior digital technology on the relationship between R&D (research and development) investment (funds and staff) and firm performance during the epidemic. Firm size and diversification are then introduced as moderating variables to explore the conditional mediating effect of digital technology. Findings: The results indicate that the higher the firm's prior R&D investment, the higher its digital technology level, and thus the stronger its resistance to the epidemic. Moreover, compared with large-scale firms, small-scale firms have the advantage of strategic flexibility to technological changes, which can help them accumulate experience from R&D activities for digital transformation, thus attenuating the negative impact of the COVID-19 on firm performance. Finally, the results also show that digital technology mediates more strongly between R&D investment and firm performance in diversified firms than in centralized firms. Originality/value: The study builds a mediation model to reveal the process mechanism through which R&D investment affects firm performance via digital technology. Firm size and diversification are then innovatively introduced as situational factors to build the moderated mediation model, which opens up a new perspective for understanding the effect of firm internal factors on the relationship between R&D investment, digital transformation and firm performance. © 2022, Emerald Publishing Limited.
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Today, the world is still suffering from Coronavirus disease 2019(COVID-19) and other disasters. Therefore, it is critical to improve medical emergency professional training, and ensuring the training effect has become the top priority. As a result, this paper builds a Particle Swarm Optimization Back Propagation(PSO-BP) neural network model using training data from the National Disaster Life Support(NDLS) course to predict NDLS training outcomes. The PSO algorithm is used to calculate the initial weights of the BP network, and the model is then trained using error back propagation to obtain the predicted value of the training effect. When compared to the standard BP neural network prediction results, experimental analysis shows that the prediction model's accuracy reaches 93.24 percentage, and the prediction accuracy is improved by 11.71 percentage. It is also better in terms of convergence speed, minimum error, global search ability, and learning smoothness. This approach is suitable for medical training effect prediction and additionally to assist the training providers in grasping trainees' learning effects in advance to improve training quality. © 2022 IEEE.
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Background/Aims A lack of knowledge exists as to how municipalities are meeting the rehabilitation needs of patients recovering from COVID-19. This poses a potential barrier when referring patients for rehabilitation. The aim of this study was to map and describe municipality-based rehabilitation services for patients recovering from COVID-19 in Denmark. Methods This was a cross-sectional, nation-wide survey. Key staff members from all 98 municipalities in Denmark were invited to participate. Participants had insight into the organisation and professional content of municipal rehabilitation. Structured telephone interviews were conducted by three interviewers between October and November 2020. The interview guide consisted of items that asked about the availability, content and organisation of municipality-based rehabilitation services. Results A total of 91 municipalities (93% response rate) participated in the study. Rehabilitation could be provided within pre-existing services in 98% of municipalities and 93% systematically assessed individual rehabilitation needs using a variety of measurement methods. All municipalities reported that they had services in place to provide functional rehabilitation (eg gait training) and over 90% provided physical, cognitive and lifestyle-related rehabilitation. In contrast, 70% could provide COVID-19 education and 64% psychological therapy. Overall, 32% of municipalities had not received referrals for COVID-19 rehabilitation. Of the 62 municipalities that had COVID-19 rehabilitation experience, 73% rated the degree to which they could deliver coherent and coordinated rehabilitation for patients with complex rehabilitation needs as high or very high. Conclusions Overall, Danish municipalities reported that pre-existing services are in place to provide relevant, individualised rehabilitation for patients recovering from COVID-19. Nonetheless, future efforts should ensure that patient education is established, in step with health care providers accumulating knowledge, as well as integrated referral pathways between sectors, to deliver rehabilitation to patients with complex needs. Further, implementation of a national data collection strategy would strengthen and inform future development of relevant services both nationally and internationally.
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Purpose: This study aims at the sudden outbreak of COVID-19, which had an unprecedented negative impact on the Chinese economy, with firms being affected most. Firms differ in terms of their specific internal environment, shaping their ability to respond to the outbreak, so the impact may also vary. Design/methodology/approach: In this paper Chinese listed firms are selected as samples to investigate the mediating effect of prior digital technology on the relationship between R&D (research and development) investment (funds and staff) and firm performance during the epidemic. Firm size and diversification are then introduced as moderating variables to explore the conditional mediating effect of digital technology. Findings: The results indicate that the higher the firm's prior R&D investment, the higher its digital technology level, and thus the stronger its resistance to the epidemic. Moreover, compared with large-scale firms, small-scale firms have the advantage of strategic flexibility to technological changes, which can help them accumulate experience from R&D activities for digital transformation, thus attenuating the negative impact of the COVID-19 on firm performance. Finally, the results also show that digital technology mediates more strongly between R&D investment and firm performance in diversified firms than in centralized firms. Originality/value: The study builds a mediation model to reveal the process mechanism through which R&D investment affects firm performance via digital technology. Firm size and diversification are then innovatively introduced as situational factors to build the moderated mediation model, which opens up a new perspective for understanding the effect of firm internal factors on the relationship between R&D investment, digital transformation and firm performance. © 2022, Emerald Publishing Limited.
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The latent and insidious nature of COVID-19 transmission poses a great challenge to epidemic prevention and control. In order to predict its transmission trend more accurately, optimal epidemic prevention and control strategies and measures can be formulated. In this paper, we propose a SEIR-C epidemic transmission trend prediction model, which improves the traditional SEIR infectious disease model and combines it with the GRU model, and experiments show that the model has better results in epidemic transmission prediction. The paper also analyses the situation of isolation measures and vaccines in epidemic prevention and control, providing some reference for the formulation of epidemic prevention and control policies. © 2022 ACM.
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The outbreak of the COVID-19 pandemic has greatly impacted patients with non-small cell lung cancer (NSCLC), making the fear of cancer recurrence (FCR) more pronounced. We explored the effects of FCR on immunotherapy efficacy and quality of life during the COVID-19 pandemic in China among the 124 NSCLC patients enrolled in this study. Quality of life and immunotherapy efficacy were compared between high- and low-FCR groups after completing 4-6 courses of treatment or cancer progression. Worse immunotherapy efficacy and quality of life were reported for the high-FCR group than for the low-FCR group. These findings emphasize the need to pay close attention to the level of FCR in NSCLC patients. Efforts should be taken to alleviate FCR levels among NSCLC patients. Moreover, research is needed to investigate the possible link between immunotherapy efficacy and FCR. Copyright © 2022 E-Century Publishing Corporation. All rights reserved.