The experience and inspiration on the prevention and control of coronavirus disease 2019 in the department of radiotherapy

Coronavirus disease 2019 (COVID-19), as a public health emergency, is a serious threat to human health. Cancer patients have a high risk of being infected with COVID-19. As one of important means of cancer treatment, radiotherapy has become an important alternative to surgery during the epidemic of COVID-19. The radiotherapy department of Peking Union Medical College Hospital ensured the smooth development of radiotherapy work on the setup of prevention and control systems for COVID-19 by establishing admission strategies for cancer patients, disinfection, isolation, daily management measures, scientific exploration, and clinical practice. In this paper, the associated strategies are summarized and analyzed, which can provide experience and reference for radiotherapy treatment under public health emergencies.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

MWG-Net: Multi-scale Wavelet Guidance Network for COVID-19 Lung Infection Segmentation from CT Images

Recently, accurate segmentation of COVID-19 infection from computed tomography (CT) scans is critical for the diagnosis and treatment of COVID-19. However, infection segmentation is a challenging task due to various textures, sizes and locations of infections, low contrast, and blurred boundaries. To address these problems, we propose a novel Multi-scale Wavelet Guidance Network (MWG-Net) for COVID-19 lung infection by integrating the multi-scale information of wavelet domain into the encoder and decoder of the convolutional neural network (CNN). In particular, we propose the Wavelet Guidance Module (WGM) and Wavelet &Edge Guidance Module (WEGM). Among them, the WGM guides the encoder to extract infection details through the multi-scale spatial and frequency features in the wavelet domain, while the WEGM guides the decoder to recover infection details through the multi-scale wavelet representations and multi-scale infection edge information. Besides, a Progressive Fusion Module (PFM) is further developed to aggregate and explore multi-scale features of the encoder and decoder. Notably, we establish a COVID-19 segmentation dataset (named COVID-Seg-100) containing 5800+ annotated slices for performance evaluation. Furthermore, we conduct extensive experiments to compare our method with other state-of-the-art approaches on our COVID-19-Seg-100 and two publicly available datasets, i.e., MosMedData and COVID-SemiSeg. The results show that our MWG-Net outperforms state-of-the-art methods on different datasets and can achieve more accurate and promising COVID-19 lung infection segmentation. IEEE

Polymer formulated self-amplifying RNA vaccine is partially protective against influenza virus infection in ferrets.

COVID-19 has demonstrated the power of RNA vaccines as part of a pandemic response toolkit. Another virus with pandemic potential is influenza. Further development of RNA vaccines in advance of a future influenza pandemic will save time and lives. As RNA vaccines require formulation to enter cells and induce antigen expression, the aim of this study was to investigate the impact of a recently developed bioreducible cationic polymer, pABOL for the delivery of a self-amplifying RNA (saRNA) vaccine for seasonal influenza virus in mice and ferrets. Mice and ferrets were immunized with pABOL formulated saRNA vaccines expressing either haemagglutinin (HA) from H1N1 or H3N2 influenza virus in a prime boost regime. Antibody responses, both binding and functional were measured in serum after immunization. Animals were then challenged with a matched influenza virus either directly by intranasal inoculation or in a contact transmission model. While highly immunogenic in mice, pABOL-formulated saRNA led to variable responses in ferrets. Animals that responded to the vaccine with higher levels of influenza virus-specific neutralizing antibodies were more protected against influenza virus infection. pABOL-formulated saRNA is immunogenic in ferrets, but further optimization of RNA vaccine formulation and constructs is required to increase the quality and quantity of the antibody response to the vaccine.

A review of COVID-19: A summary of the epidemic in Wuhan and other local areas in China

COVID-19 is a new kind of coronavirus that was found in 2019 and it has swept the world until now. Reviewing it and discovering the problem is what we must do. In this scenario, the influence of COVID-19 on the world, and especially in China since it is the country where COVID-19 first outbreak, has been thoroughly reviewed. The main point ofthis paper is to identify the epidemiological information ofCOVID-19 and to review typical cities that are most influenced by COVID-19, such as Wuhan, Dalian, and Shijiazhuang. Moreover, discovering and comparing the characteristics and regulations according to different periods have also been carefully performed. With the understanding of the infection of COVID-19, the bright future in which prevention and control measures of nosocomial infection are improved is surely within reach. Furthermore, the psychological construction and management in fundamental systems require more attention. © The Authors, published by EDP Sciences.

Omicron BA.2 Prediction Research Based on SEIR-ARIMA Mixed Model

Omicron BA.2, a new variant of severe acute respiratory syndrome coronavirus (SARS-CoV-2), has attracted worldwide attention due to its high infectivity and vaccine escape mutation. Based on the SEIR model being susceptible to changes in external factors and having specific errors, the ARIMA model is data-dependent and can only capture linear relationships. In this paper, based on the traditional infectious disease dynamic model SEIR and the differential integrated mean autoregressive model ARIMA, an SEIR-ARIMA mixed model is proposed to predict and evaluate the virus outbreak in March in Jilin Province, China. The data from SEIR and ARIMA models were processed using SPSS to obtain the predicted values f and e, respectively. Linear regression modeling was performed on the predicted values f and e to establish the SEIR-ARIMA model. MATLAB is used to complete the best linear fitting line. Furthermore, The results show that the model's predicted value is in good agreement with the actual value. It shows that the SEIR-ARIMA mixed model based on the SEIR-ARIMA model has a good prediction effect, which is beneficial for the country to make the right decision when facing the epidemic. It is of great value for preventing other types of infectious diseases in China in the future. © 2022 IEEE.

Polymer formulated self-amplifying RNA vaccine is partially protective against influenza virus infection in ferrets

COVID-19 has demonstrated the power of RNA vaccines as part of a pandemic response toolkit. Another virus with pandemic potential is influenza. Further development of RNA vaccines in advance of a future influenza pandemic will save time and lives. As RNA vaccines require formulation to enter cells and induce antigen expression, the aim of this study was to investigate the impact of a recently developed bioreducible cationic polymer, pABOL for the delivery of a self-amplifying RNA (saRNA) vaccine for seasonal influenza virus in mice and ferrets. Mice and ferrets were immunized with pABOL formulated saRNA vaccines expressing either haemagglutinin (HA) from H1N1 or H3N2 influenza virus in a prime boost regime. Antibody responses, both binding and functional were measured in serum after immunization. Animals were then challenged with a matched influenza virus either directly by intranasal inoculation or in a contact transmission model. While highly immunogenic in mice, pABOL-formulated saRNA led to variable responses in ferrets. Animals that responded to the vaccine with higher levels of influenza virus-specific neutralizing antibodies were more protected against influenza virus infection. pABOL-formulated saRNA is immunogenic in ferrets, but further optimization of RNA vaccine formulation and constructs is required to increase the quality and quantity of the antibody response to the vaccine.

[Analysis of common viral infection in surveillance cases of febrile respiratory syndrome in 9 provinces of China from 2009 to 2021].

Objective: To understand the common viral infection among the surveillance cases of fever respiratory syndrome (FRS) in nine provinces in China. Methods: The research data were obtained from nine provinces (Anhui, Beijing, Guangdong, Hebei, Hunan, Jilin, Shandong, Shaanxi and Xinjiang) in the "Infectious Disease Surveillance Technology Platform Information Management System" of the Chinese Center for Disease Control and Prevention from January 2009 to June 2021. Finally, 8 243 FRS cases with nucleic acid detection results of eight viruses [human influenza virus (HIFV), human respiratory syncytial virus (HRSV), human adenovirus (HAdV), human parainfluenza virus (HPIV), human rhinovirus (HRV), human metapneumovirus (HMPV), human coronavirus (HCoV) and human Boca virus (HBoV)] were included in the study. The χ2 test/Fisher exact probability method was used to analyze the difference of virus detection rate in different age groups, regions and seasons. Results The M (Q1, Q3) age of 8 243 FRS cases was 4 (1, 18) years old, and 56.56% (4 662 cases) were children under 5 years old. Males accounted for 58.1% (4 792 cases) of all cases. All cases were from outpatient/emergency department (2 043 cases) and inpatient department (6 200 cases). The virus detection rates of FRS cases from high to low were HRSV, HIFV, HPIV, HRV, HAdV, HMPV, HCoV and HBoV. Two or more viruses were detected simultaneously in 524 cases, accounting for 15.66% of virus-positive cases. The difference of the virus detection rate in different age groups was statistically significant (all P values<0.05), and the virus detection rate in children<5 years old was higher (49.96%). The positive rate of any virus in south China was higher than that in north China (P<0.001). The virus-positive FRS cases were detected throughout the year. The detection rate of HRSV was higher in autumn and winter. The detection rate of HIFV was higher in winter. The detection rate of HMPV was higher in winter and spring. The detection rates of HPIV, HRV, HCoV and HBoV were higher in summer and autumn, while there was no significant difference in the detection rate of HAdV in different seasons. Compared with 2009-2019, the detection rate of any virus in 2020-2021 decreased from 41.37% to 37.86%. The detection rate of HIFV decreased sharply from 10.62% to 1.37%. The detection rate of HPIV decreased from 8.24% to 5.88%. The detection rate of HRV and HBoV increased from 5.43% and 1.79% to 9.67% and 3.19%, respectively. Conclusion: HRSV and HIFV infections are more common among FRS cases in nine provinces in China from 2009 to 2021, and the epidemiological characteristics of eight common respiratory viruses vary in different age groups, regions and seasons.

A NOVEL CONVOLUTIONAL NEURAL NETWORK BASED ON ADAPTIVE MULTI-SCALE AGGREGATION AND BOUNDARY-AWARE FOR LATERAL VENTRICLE SEGMENTATION ON MR IMAGES

In this paper, we propose a novel convolutional neural network based on adaptive multi-scale feature aggregation and boundary-aware for lateral ventricle segmentation (MB-Net), which mainly includes three parts, i.e., an adaptive multi-scale feature aggregation module (AMSFM), an embedded boundary refinement module (EBRM), and a local feature extraction module (LFM). Specifically, the AMSFM is used to extract multi-scale features through the different receptive fields to effectively solve the problem of distinct target regions on magnetic resonance (MR) images. The EBRM is intended to extract boundary information to effectively solve blurred boundary problems. The LFM can make the extraction of local information based on spatial and channel attention mechanisms to solve the problem of irregular shapes. Finally, extensive experiments are conducted from different perspectives to evaluate the performance of the proposed MB-Net. Furthermore, we also verify the robustness of the model on other public datasets, i.e., COVID-SemiSeg and CHASE DB1. The results show that our MB-Net can achieve competitive results when compared with state-of-the-art methods. © 2022 IEEE

Analytics applications, limitations, and opportunities in restaurant supply chains

Technology, market, and competitive dynamics are requiring firms in restaurant/food service supply chains to improve their analytics capabilities, which have tended to lag behind other comparable industries. The global COVID-19 pandemic has further encouraged industrial leaders to evaluate new challenges and opportunities. Our research provides insights into current applications of analytics technologies and organizationally integrates these insights for decision-makers in restaurant supply chains. The study applies decision theory as a framing perspective to this phenomenon, thereby advancing the academic literature on the interface between data management, analytical techniques, and computing. We combine data drawn from interviews of leading players in U.S. and Chinese-based restaurant chains with insights from trade publications and social media posts to identify best practices for analytics usage and supporting organizational changes. Our analysis provides examples of ways in which business leaders are applying analytics technologies to structured and unstructured data to address targeted objectives for demand/supply processes and to foster higher order organizational learning. In keeping with the stated objectives of this special issue of Production and Operations Management, this study provides an overview of both current state-of-the-art and next-generation capabilities for analytics in the restaurant industry. We further identify specific limitations of current processes, opportunities for development and theory-based research, and challenges to implementation.

Estimation of epidemiological parameters of COVID-19 epidemic caused by Delta variant strain in Guangzhou

Objective An epidemic of COVID-19 caused by an imported Delta variant strain in Guangzhou was investigated, and the transmission chain, transmission characteristics and infection of each case were analyzed, so as to provide a theoretical basis for predicting disease development and epidemic prevention and control. Methods By collecting the information released by Guangzhou government, the confirmed cases with a clear transmission chain were selected, and the infectious disease indicators such as serial interval (SI), basic reproduction number (Rq) and time-dependent reproduction number (Rt) were calculated to analyze the epidemiological characteristics. Results From May 21 to June 20, 2021, a total of 144 cases of indigenous COVID-19 were confirmed in Guangzhou, among which 67 pairs of cases with a clear transmission chain were selected. SI was calculated to follow the Gamma distribution, with a mean of 4. 27 d and a standard deviation of 2.65 d. Rq = 3. 18 (95% CI: 2. 1974.428), and Rt showed an obvious decreasing trend over time. On June 10, Rt = 0.97 (95% CI: 0. 751 -1. 214), which was lower than 1. Since then Rt had been less than 1, and it got smaller and smaller over time. Conclusion In this COVID-19 epidemic, the SI was shorter and the Rq was larger, which indicated that the Delta variant strain had a faster transmission rate and stronger transmissibility than the COVID-19 infected in Wuhan in 2020.

Irrigated agriculture potential of Australia's northern territory inferred from spatial assessment of groundwater availability and crop evapotranspiration

Agricultural expansion has been a hot topic in the Northern Territory (NT) of Australia in recent years. However, insufficient information on available water resources and crop evapotranspiration is a bottleneck to this expansion. Towards closing this gap, this study employs the newest Global Land Data Assimilation System (GLDAS;version 2.2) catchment products assimilated from the Gravity Recovery and Climate Experiment (GRACE;hereafter called GLDAS-DA) and the Food and Agriculture Organization (FAO) Penman-Monteith equation to spatially evaluate the Balance between water availability (i.e., groundwater and effective rainfall) and melons, maize and citrus crop evapotranspiration (water demand) of three representative (short-, medium-season and perennial) crop types over the NT for the 2010–2019 period. Specifically, this Balance is the estimated ratio of water availability and crop evapotranspiration, representing the crop area that can be planted in each GLDAS-DA grid cell. The larger the Balance , the greater the irrigated agriculture potential. Under the average 2010–2019 conditions, our results show that the northern part of the NT has the highest irrigated agriculture potentials with the average Balance of 9430 ha (15.7%), 5490 ha (9.1%) and 3520 ha (5.8%) for melons, maize and citrus, respectively, excluding non-agriculture areas. Irrigated agriculture in the central part of the NT shows less potential compared to the northern part of the NT, with the average Balance of 2780 ha (4.6%), 2000 ha (3.3%) and 970 ha (1.6%) for melons, maize and citrus, respectively (excluding non-agriculture areas). The southern part of the NT shows an average Balance below 1% of grid cell for all three crops, suggesting that only small-scale irrigated agriculture could be possible. In addition, the Balance across most of the northern and central parts of the NT decreased by 50% or more during 2019 dry period. Drought risk management should therefore be a serious consideration when exploring further expansion of irrigated agriculture in the NT. • Irrigated-agriculture potential in NT is assessed through groundwater and ETc. • The northern NT has highest potential for irrigated agriculture. • The shoreline of central NT shows potential for intensive irrigated-farming. • The southern NT has limited potential for irrigated agriculture. • Agriculture potential reduces 50% or more in the NT during the dry climate of 2019. [ FROM AUTHOR];Copyright of Agricultural Water Management is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Clinical features of COVID‑19 in patients with prominent digestive symptoms

Objective: To analyze the clinical characteristics of COVID‑19 in the patients with predominant digestive symptoms and to discuss related clinical issues. Methods: A retrospective clinical analysis was performed on 638 discharged patients with confirmed COVID‑19 from January 30, 2020 to March 10, 2020, to collect their basic information, first symptoms, laboratory results, nucleic acid test, disease severity, and outcomes. Results: Of the 638 patients with COVID‑19, fever was the most common first symptom. There were 87 cases (13.6%) with obvious digestive symptoms and 551 cases (86.4%) without digestive symptoms, of which, diarrhea was the most common (67.8%) one. As compared with those without predominant digestive symptoms, these COVID cases were younger in age, had higher rate of cough (65.5%), higher maximum body temperature, and higher proportion of WBC counts <4.0×109/L. However, patients without gastrointestinal symptoms had a higher level of ultra‑troponin I. There was no significant difference between the two groups in terms of gender composition, fever, sputum, chest pain, chest tightness, dyspnea, and basic diseases. Meanwhile, no statistical difference was found between the two groups in most laboratory results, duration of viral shedding, the production of specific antibodies, characteristics of chest CT imaging, disease severity, and death rate. Conclusion: The diarrhea‑mainly digestive symptoms were the first‑episode symptoms in some patients with COVID‑19, their clinical characteristics and the courses were generally similar to those without obvious digestive symptoms. In view of the fact that some patients have positive nucleic acid test on anal swab and there is a risk of gastrointestinal transmission, the clinical care requirements and difficulties have increased for such patients. © 2022, Editorial Board of Medical Journal of Wuhan University. All right reserved.

Caring for an Aging Population in a Post-Pandemic World: Emerging Trends in the US Older Adult Care Industry

This paper examines older adult care services during the outbreak of the COVID-19 global pandemic. Specifically, it investigates emerging developments initiated or augmented by the pandemic and discusses their permanency in a postpandemic world. Primary survey data are collected from both older adult care-providing organizations (supply) and individuals receiving or considering care (demand) in the United States. Qualitative support from various sources supplements the surveys. The results indicate a movement toward deinstitutional care options, which began prepandemic but intensified during the outbreak. Care organizations confirm this development, reporting more occupancy-related concerns. Findings also suggest that telehealth and digital communication tools have substantially expanded. Benefits, issues, and future projections of these trends are discussed, and some suggestions for industry reform are proposed. These results illuminate many actionable ideas for various stakeholders, including older adults, industry practitioners, and policymakers.

The experience and inspiration on the prevention and control of coronavirus disease 2019 in the department of radiotherapy

Coronavirus disease 2019 (COVID-19), as a public health emergency, is a serious threat to human health. Cancer patients have a high risk of being infected with COVID-19. As one of important means of cancer treatment, radiotherapy has become an important alternative to surgery during the epidemic of COVID-19. The radiotherapy department of Peking Union Medical College Hospital ensured the smooth development of radiotherapy work on the setup of prevention and control systems for COVID-19 by establishing admission strategies for cancer patients, disinfection, isolation, daily management measures, scientific exploration, and clinical practice. In this paper, the associated strategies are summarized and analyzed, which can provide experience and reference for radiotherapy treatment under public health emergencies. © 2021, Peking Union Medical College Hospital. All rights reserved.

Sleep health traits and COVID-19: Mortality risk from the UK biobank

Introduction: While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods: We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3;range 50.2-84.6). Selfreported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/“intermediate”/“evening”), daytime dozing (often/ rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results: The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (>9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%);OR 2.09, 95% 1.19-3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04-2.72, p=0.03), and nappers (OR 1.52, 95% 1.04-2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25-3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion: Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19.

Multi-dimensional Visualization and Simulation Analysis of COVID-19 Outbreak

The progression of the global COVID-19 epidemic situation is the main focus of attention of all countries in the world. Due to characteristics, such as multi-origins, huge amount, and inaccessibility, of the existing data, an all-round analyzation of the epidemic situation, which is in dire need, is impeded. The aim of the following study is to provide a multi-dimensional analysis of COVID-19 through visualization and dynamic simulation of data. In order to achieve this goal, the study collected related data though multiple platforms and used tools such as Echarts and Java Swing to visualize the data, and then dynamically simulated the transmission model. Moreover, the data of Wuhan has been applied to the SEIR model to study the effect of quarantine on the transmission of COVID-19. Ultimately, the study hopes to demonstrate an effective method of data analyzation that can be applied to prevent and contain similar outbreak in the future. © 2021, Springer Nature Switzerland AG.

Value of D-dimer, C-reactive protein, procalcitonin, and blood routine test in assessing the prognosis of severe coronavirus disease 2019

Objective: To investigate the value of D-dimer, C-reactive protein (CRP), Procalcitonin (PCT) and blood routine test in evaluating the prognosis of patients with severe coronavirus disease 2019 (COVID-19). Methods: A total of 54 severe COVID-19 patients were retrospectively studied, and were divided into death group (n=54) and survival group (n=31) according to the outcomes. The plasma D-dimer, CRP, PCT, and blood routine test of the two groups were analyzed and compared in order to clarify their relationship to the prognosis of severe COVID-19. Results: The time to initiation of disease days, age and proportion of comorbidity in death group were significantly longer or higher than in survival group (all P<0.05). The white blood cell counts and neutrophil counts levels in death group were significantly higher than in survival group (both P<0.05), while the lymphocyte counts levels in dead group were significantly lower than in survival group (P<0.05). D-dimer, CRP and PCT in death group were significantly higher than in survival group (all P<0.05). D-dimer was positively correlated to CRP (r=0.426, P<0.05), and negatively correlated with PCT (r=-0.217, P>0.05). Conclusion: D-dimer, CRP, white blood cell counts, and lymphocyte counts are valuable for prognosis evaluation of patients with severe COVID-19, and PCT also has certain prognostic value. © 2021, Editorial Board of Medical Journal of Wuhan University. All right reserved.

Formative assessment as an online instruction intervention: Student engagement, outcomes, and perceptions

Online education has long been suffering from high dropout rate and low achievement. However, both asynchronous and synchronous online instructions have to become effective to serve as a quick response to maintain undisrupted learning during the COVID-19 outbreak. The purpose of the present study was to examine student engagement, learning outcome, and students' perceptions of an online course featured with frequent tasks, quizzes, and tests as formative assessment. Data were collected from the first five weeks of a course that was temporarily converted from blended learning to be fully online in time of school closure. Analysis of students' learning records and scores indicated that students engaged themselves actively in all of the online learning activities and had gained high scores in all tasks, quizzes, and tests. In addition, students held positive perceptions towards the formative assessment. © This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and production in any medium, provided the author of the original work and original publication source are properly credited.