Descriptive norms predicted all drinking behavior better than injunctive norms and all five motives for all age groups. The effects of each of the five motives differed with age. The enhancement motive was the strongest predictor of the motives for drinking frequency, binge drinking, and high-risk drinking across all age groups. Social and conformity motives predicted only binge drinking. Conclusions: These results suggest that descriptive norms, injunctive norms, and enhancement motives predict drinking behaviors across all age groups, although the relative predictive strength of those variables differed by age.Background: Drinking norms and motives accumulate with drinking experience; thus, it is likely that related drinking behaviors will differ with age. This study aimed to predict drinking behaviors by age based on drinking norms and motives in a sample of Korean women. Methods: This exploratory study used a nationwide demographically stratified sample including 1057 women aged 19–59 years. Self-report questionnaires assessed participants’ general drinking frequency and quantity, two drinking norms, and five dimensional motives. The data were analyzed using Spss 26. Results: Descriptive and injunctive norms were the predictors that accounted for the greatest variance in drinking frequency, quantity, binge drinking, and high-risk drinking across all age groups ( According to a recent Korea National Health and Nutrition Examination Survey (KNHNES) by the Ministry of Health and Welfare, the amount of alcohol consumed annually by Koreans is decreasing, but the rates of risky and binge drinking among young adults, especially women, is increasing . In 2020Drinking, especially binge drinking or high-risk drinking, is largely influenced by sociocultural factors, including social drinking norms and motives, traditional drinking patterns, and a country’s alcohol policies . Norms aAccording to Riley’s age stratification theory , each agKorea has one of the most rapidly changing societies worldwide, and the gender roles and social responsibilities of women have changed dramatically in the past forty years. While social expectations and life experiences differ for each age cohort, analyses of drinking patterns among women by age have not received sufficient attention in Korea .hoesik, meaning “staff dining” or “company dining”, is very common in Korea. Ko and Sohn [Research has contended that the main reason for drinking alcohol in Korea is to reduce work-related stress, as rapid economic growth leads Koreans to work long hours ,8. Compaand Sohn ,8 have sand Sohn . Enhanceand Sohn . HoweverMany studies of women’s alcohol use in Korea have focused on differences between men and women; therefore, there has been less research on other individual factors, such as social norms and motives at different ages ,8,14. SiSD = 11.2). To compare age groups for the purposes of the analysis, the respondents were divided into four age groups—those 20–29 , 30–39 , 40–49 , and 50–59 . Fifty-one percent of participants were married or living with a partner, 22.8% were high school graduates or less, 12.0% had a low monthly income (up to KRW 1999), 68.9% had a middle income (KRW 2000–6999), and 19.1% had a high income (KRW 7000 or more).Demographically proportioned stratified sampling was conducted using a panel of participants enrolled in June 2021 by the domestic company “M” to recruit the study participants. Respondents were screened for eligibility using questions regarding their age and region. The allocated female sample size of 1100 was stratified by age and region to obtain a nationally representative sample. A cleaning process was performed for the derived data and subsequently, 1067 cases were analyzed. Their mean age was 40.5 years . Informed consent was obtained from all participants. The survey was conducted from June to July 2021 using an online survey. Drinking frequency and quantity. In this study, the data available before the onset of the COVID-19 pandemic were used. Participants were asked how often they had consumed alcohol over the past year  and how much they usually drank on each occasion. For the regression analyses, these variables were converted to the number of standard drinks. Binge drinking and high-risk drinking. Binge drinking is considered risky because it can increase blood alcohol concentration dramatically within a short period [t period . The deft period . One stat period . High-rit period . Descriptive norms refer to the perceptions of the drinking frequency and quantity of others. Injunctive norms refer to the perceived approval of drinking and represent perceived moral rules ,19. InjuDescriptive norms and injunctive norms. Descriptive norms  were measured by assessing how frequently respondents thought their friends drank alcohol. Injunctive norms included positive perceptions in nine different situations  [r alone) . In thisDrinking motives. Drinking motives were measured using 15 self-reported items on five subscales with three items each. The 5 subscales were enhancement , coping , social , conformity , and environmental context  motives for drinking. The participants were asked to rate how often each statement reflected their reasons for drinking over the last 12 months on a five-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree).Except for lifetime abstainers who had never consumed alcoholic beverages, 991 respondents answered the drinking motive items to obtain the exact drinking motives. Higher scores indicated greater agreement with the enhancement, coping, social, conformity, and environmental drinking motives. Cronbach’s coefficients for the enhancement, coping, social, conformity, and environmental (accessible) drinking motives scales were 0.70, 0.73, 0.86, 0.79, and 0.82, respectively.Sociodemographic variables were categorized in detail; however, they were analyzed as dichotomous variables for further analyses. Sociodemographic variables consisted of the age group , marital status , education (<2-year college degree vs. ≥2-year college degree), job status , monthly household income (low—up to 1999 k KRW vs. middle—2000 k–6999 k KRW and high—7000 k KRW or more).SPSS statistics software package version 26.0  was used for the statistical analyses. The characteristics of the different age groups were analyzed using descriptive statistics . Drinking behaviors, norms, and motives variables were analyzed using ANOVAs and chi-square tests by age group.Multiple and logistic regression analyses assessed differences and influences of demographic variables, norms, and motives on the frequency of drinking occasions and quantity of drinks consumed by age group. The numbers of participants who reported binge and high-risk drinking were insufficient to conduct analyses by age group. Before the multiple and logistic regression, significant variables were identified using correlation analysis. SD = 4.54) standard drinks. p < 0.001).Drinking behaviors were significantly different in the frequency and quantity of drinking occasions with age. Abstention rates differed by age group and were 19.2%, 16.0%, 18.6%, and 28.8% for those in their 20s, 30s, 40s, and 50s, respectively. The prevalence of drinking was the lowest among adults in their 50s. The mean drinking quantity was significantly higher in younger versus older age groups (p < 0.001)—19.4% of those in their 50s reported binge drinking compared to 51.3% of those in their 20s. High-risk drinking was significantly more frequent in younger age groups than older (p < 0.001), with the percentage of high-risk drinkers peaking in their 20s (15.9%), followed by those in their 30s (12.4%).The proportion of participants reporting binge drinking significantly decreased by age (p < 0.001). Friends’ drinking frequency of two to four times per month differed by age group, being the highest for participants in their 20s (38.9%), followed by those in their 30s (34.2%), those in their 50s (33.5%), and those in their 40s (28.6%).As shown in p < 0.001).Among the drinking behaviors considered acceptable by those in their 20s vs. those in their 50s, the highest reported percentage was for “drinking alone” (79.1% vs. 40.6%), followed by “getting drunk” (59.4% vs. 15.3%), “drinking during the day” (58.6% vs. 8.3%), and “drinking in a convenience store” (31.4% vs. 13.4%). For all statements, except “Crimes committed while drunk can be forgiven” and “It is discourteous to refuse a drink offered by someone else”, respondents in their 20s and 30s were more likely to agree significantly than those in their 40s and 50s (p < 0.001). As seen in The drinking motives of each age group are presented in M = 3.18) ranked the highest among the five motives, followed by enhancement (M = 2.85), coping (M = 2.54), conformity (M = 2.18), and environmental (M = 1.92). The five motives ranked in the order of social > enhancement > coping > conformity > environmental in all age groups. Different levels were shown by age group, and the highest level of social motive was found among those in their 20s. The enhancement motive had the highest score among those in their 30s, the coping motive among those in their 40s, and the conformity and environmental motives among those in their 50s.The social motive . The quantity of alcohol consumption accounted for 36%, 37%, 31%, and 21% of the variance by age group—20s, 30s, 40s, and 50s .A multiple regression analysis was conducted to determine the factors associated with the frequency of drinking and quantity of alcohol across age groups . The socThe regression analyses showed that descriptive norms  were the most important factors and positively related to the drinking frequency and quantity for all age groups. Injunctive norms were significantly and positively related to drinking frequency and quantity for most age groups.Regarding the five motives, the enhancement motive was the most important motive and positively related to drinking frequency and quantity for most age groups. The coping motive was not significantly correlated with the frequency and quantity of drinking among all age groups. The social motive was significantly and positively associated with drinking quantity for women in their 20s. The conformity motive was significantly negatively correlated with drinking frequency and quantity in most age groups. Overall, these findings suggest that those with a high level of conformity were more likely to drink less in terms of frequency and amount. The environmental motive was significantly positively correlated with drinking frequency for women in their 40s. Of the sociodemographic variables, the regression analysis revealed that only household income had a significant positive association with drinking frequency only for those in their 30s. Additionally, smoking was significantly associated with the quantity of drinking for those in their 20s, 30s, and 40s.R2 = 0.35, 37). Binge drinking rates were significantly associated with age (p < 0.001), education (p < 0.001), smoking status (p < 0.001), descriptive norms (p < 0.001), injunctive norms (p < 0.001), enhancement motive (p < 0.001), social motive (p < 0.05), and conformity motive (p < 0.05). Those who were younger, high school graduates, smokers, and had a high level of descriptive norms (those who thought their friends drank frequently) and injunctive norms , enhancement motives, social motives, and low levels of conformity were more likely to be binge drinkers.As shown in p < 0.05), descriptive norms (p < 0.001), injunctive norms (p < 0.001), and the enhancement motive (p < 0.001). High-risk drinkers were more likely to be divorced or separated, have high levels of descriptive norms, injunctive norms, and the enhancement motive. Descriptive norms, injunctive norms, and the enhancement motive were significant for both binge drinking and high-risk drinking. Age, education, household income, smoking status, and social, conformity, coping, and environmental motives were not significantly related to high-risk drinking; however, some of those variables  approached a significant level for binge drinking.In the full sample, the probabilities showed a significant association between a high-risk drinking rate and marital status , two norms , and five drinking motives by age group. Factors affecting the frequency, quantity, binge drinking, and high-risk drinking were identified. Drinking frequency and quantity significantly differed by age, with the highest rates among those in their 30s, 20s, 40s, and 50s, in that order. Binge drinking and high-risk drinking peaked among those in their 20s, with much larger differences in the rate of binge drinking among those in their 20s and 50s.Our findings are similar to those of the KNHNES, which found that binge or high-risk drinking was more frequent in younger age groups compared to older age groups, while monthly drinking, binge drinking, and high-risk drinking in men did not significantly differ by age . In the This study found that descriptive and injunctive norms regarding drinking differed by age group. Descriptive norms were the strongest predictor across all age groups, especially younger age groups. The respondents believed that their friends and colleagues drank more frequently than they did. Respondents who believed that their friends drank frequently were more likely to drink frequently themselves. They also drank more and were significantly more likely to be binge drinkers or high-risk drinkers. Among the respondents, norms served as a standard for judging the appropriateness of their actions by observing others’ drinking behavior ,8,13. CoInjunctive norms are perceptions regarding which specific drinking behaviors are socially acceptable . The regDrinking alone was perceived more favorably by younger women than older women in this study. Recently, the popularity of solitary drinking has grown in Korea ,21 due tIn this study, there were large differences in drinking motives between the younger and older respondents, although the ranking of the motives was the same. The five dimensional motives ranked in the order of social > enhancement > coping > conformity > environmental for all age groups. However, in terms of the type of drinking motive, the age group rating for the highest-level motive differed, with those in their 20s having the highest social motive rating, those in their 30s having the highest enhancement motive rating, those in their 40s having the highest coping motive rating, and those in their 50s having the highest ratings for the conformity and environmental motives. Younger women had a higher motivation for drinking to enhance positive emotions and cope with negative ones compared to older women, while older women had a higher motivation to drink due to social pressure and environmental stimuli or temptation. These findings suggest that the drinking culture of enjoyment represents a leisure activity for younger adults in Korea. In terms of drinking frequency and quantity, those with a high level of enhancement and low level of conformity were likely to drink more. Although the social motive was rated the highest, it did not predict drinking frequency and quantity. Since all Korean women, regardless of age, had high social motive levels, there was less variation, which did not predict their drinking behaviors.In particular, the enhancement motive of the five motives significantly predicted both binge and high-risk drinking. These findings are consistent with research reporting that enhancement motives are the frequent drinking motivation reported among adolescents , with yoIn addition, respondents who were divorced or separated were more likely to engage in high-risk drinking; therefore, special attention should be paid to these populations. Many studies regarding health behaviors such as smoking, alcohol consumption, and physical activities have found large gaps across age, income, education, and occupation groups ,28. DistThis study had several limitations. The data reflected the drinking frequency and quantity that were assessed before the onset of the COVID-19 pandemic, so they were likely to have a recall bias. The COVID-19 pandemic has led to considerable changes in drinking patterns worldwide, including in South Korea. Drinking frequency and quantity in most groups has decreased owing to social distancing measures in South Korea .The drinking motives scale used in this study had some limitations related to its psychometric validation. In Sohn’s study , there wThe study findings indicate that young women tend to consume more alcohol and drink more frequently than older women. The increased alcohol consumption by young women has led to a greater proportion of binge drinking and high-risk drinking among young women compared to older women. Since women who engage in high-risk drinking are more vulnerable to alcohol dependence or alcoholism than men ,18, earlThe study findings indicated that the descriptive and injunctive norms played an important role in influencing the frequency and quantity of drinking for all age groups. Respondents who reported high levels of injunctive norms  reported more drinking behaviors. These norms could be changed by public campaigns to reduce risky drinking behaviors. A government-led campaign is needed to address descriptive norms and decrease excessive drinking. In addition, people should be informed of the criteria for low-risk drinking.


Conducting a ward round in a structured and goal-oriented manner is one of the central competencies of a physician's work. Despite its relevance, ward round competence was only addressed in an unstructured way in the Medical Curriculum Munich (MeCuM) prior to 2011. Therefore, the project’s aim was to implement an evidence-based course on medical ward round competence. This project report provides a guideline for developing such a training course. Project planning and development was guided by the steps of the “Kern cycle”, beginning with needs assessment, learning objectives definition, and selection of appropriate teaching methods, and ending with implementation and evaluation. Medical ward rounds are a central and complex part of the medical routine of any specialization and usually have to be performed independently from the first day of clinical activity. Conducting a ward round is an entrustable professional activity (EPA) , which iAlready on the first day of a work, it is expected that physicians carry out a ward round competently . HoweverThe reason for a lack of ward round competence is, on the one hand, the complexity of the ward round since various goals are pursued here and numerous domains of competences are required , 10]. O. O10]. OIn Germany, young residents are likely insufficiently prepared for ward rounds during their studies. Although ward rounds are partly used to teach practical and theoretical content, they are rarely used to reflect on the ward rounds themselves. http://www.nklm.de] in Germany, ward rounds are listed as a competence and at the end of the final clinical year a competence level 3a (“perform and demonstrate under supervision”) is demanded. The teaching method for achieving this competence is left to the individual medical faculties, as is the case for all other content of the NKLM. In the National Competence-Based Learning Objectives Catalogue for Undergraduate Medical Education (NKLM)  to to17] toa tool for feedback and self-reflection as a prerequisite for self-directed, lifelong learning in the area of ward rounds skills anda structured hands-on training of the professional activity “conducting a ward round” with a focus on error management, self-management, leadership and organizational skills.To improve ward round competency on the first day of practice as a physician, a course should be implemented in MeCuM with the overall learning objective:MeCuM graduates will be able to conduct and demonstrate a ward round under supervision.To meet the above needs, a training course for the clinical semesters was planned. This course should bring together previously acquired knowledge, skills, and learned behaviors of the domains of competence to perform a specific activity “conducting a ward round”. The course furthermore should supplement these competencies with specific professional knowledge, and create the ability and willingness for continuous development in the remainder of the medical studies and post-graduate training. The learning objectives are shown in table 2 th and 7th semester; approx. 550 students per academic year). The new ward round course should be established in the compulsory curriculum and linked to the existing internal medicine clerkship (“Blockpraktikum Innere Medizin”). The structure of the clerkship in internal medicine with integration of the ward round training course is shown in figure 1 The planned training course should take place in the basic interdisciplinary clinical year of MeCuM  and then to implement the unstructured acquired knowledge in the SiLVi course in a structured manner through a simulated experience. In addition to the focus on ward rounds, students pursue self-defined learning objectives on the days they are present on the ward in the internal medicine clerkship in order to meet their individual learning needs (self-directed learning ). StudenFifteen students per group take part in the SiLVi course after the clerkship in internal medicine. The ward round courses are led by a team of ten trained medical teachers. The course duration is 120 min. In the course, the EPA checklist is used, which was developed on the basis of the interview studies , 19] in in19] inThe timing and content of the SiLVi course, together with the assigned learning objectives and teaching methods, are shown in table 3 the medical complexity of the patient cases should be standardized as well as adapted to the prior knowledge of the students, in the clerkship in internal medicine, the students already participate in real ward rounds and can bring this experience into the simulation, the course in the form of a simulation offers the students a protected setting – the student takes on a role that they can discard after the scenario. Mistakes should be allowed and serve as a learning opportunity, after observing the ward round in the clerkship and experiencing a ward round in the simulated role play, the students should then in the practical year conduct real ward rounds under supervision in the spirit of the learning spiral. The course was implemented in the teaching clinic . Here, realistic patient rooms with video transmission to the neighboring seminar room and with Venetian mirror are available. In the training course, students have the opportunity to experience different perspectives of the ward round in role plays and to apply what they have learned. At the beginning of each scenario, all students are presented with the framework of the patient case (briefing). In addition, separate role scripts are handed out to the participants of the ward round as well as to the patients. In order to make the role play as realistic as possible, the participants wear appropriate professional clothing  and patient charts  are available to the team. The observing students follow the ward rounds and evaluate them using the EPA checklist. The ward round scenarios were developed by medical experts and tested with medical personnel. In terms of content, the scenarios are based on ward round cases with a low level of medical complexity mainly because of the partly heterogeneous prior knowledge of the students. Frequently, ward round teams are focused on medical aspects of a patient case – in the course and accordingly to the developed ward round scenarios – however, the students were to focus primarily on further ward round competencies and less on medical expertise. The goal was to minimize problems caused by students’ lack of medical knowledge in the ward round simulation. The duration is approximately 5-10 minutes per ward round scenario. According to our research, this is a realistic time frame (4-12 minutes/patient case) , whereasPotential conflicts are inserted in each of the ward round scenarios, so the ward round team has to respond accordingly. Examples of the conflicts in the scenarios are: pending test results ward round participation of relatives newly emerged symptoms of the patient  Following each ward round scenario, the actors reflect on their performance and the observers provide feedback with the help of the EPA checklist. Moderation and debriefing are done by the instructor.In 2011, a curriculum reform of the clinical years of study at LMU took place with the implementation of a basic clinical year (“module 23”). In the process, the disciplines of internal medicine (previously “module 2”) and surgery (previously “module 3”), which had previously been taught separately, were restructured into a total of eight organ-based modules and now taught on an interdisciplinary basis. Each of these organ-based modules  comprises four weeks, which are concluded with a final exam.As part of the reform, structure and content of the clerkship in internal medicine were also adapted and further developed. The conceptualization and implementation of the ward round training course as part of the clerkship was done by persons who were also part of the central organization team of “module 23” . Thus, the curriculum reform of the clinical years of study section facilitated the implementation of the SiLVi course. After presentation of the state analysis as well as the need for a ward round training course, the project received broad support from the Dean of Studies, “module 23” spokespersons at the time as well as the students involved in the curriculum reform. Personnel costs were incurred primarily during the development phase of the project. No real costs were incurred by the project team due to the teaching commitments and medical didactic research activities of the curriculum planners. The costs for student assistants were covered by a teaching innovation funding instrument of the LMU Medical Faculty (Hildegard-Hampp-Humanitas Trust). There were no technical or construction costs, as simulation rooms for new teaching formats were available with the establishment of the teaching clinic (2011). The teaching clinic enabled the ward round course in its current form with simulation in a realistic patient room. The first concept for the training course was piloted with students in their practical year and residents. Their feedback helped to refine the content of the course. The lecturers were intensively trained and actively involved in the course development. This also enabled content-related and organizational problems to be identified prior to implementation. After optimizing the course schedule and adding further ward round scenarios, the first SiLVi courses were held in the summer term of 2012. In following courses, the concept was adapted by means of regular evaluations (by students and lecturers). When designing the training course, the possibility of using actors who play standardized patients was discussed. This could have made the ward round situations more controllable and the process more predictable. However, role-playing offered students the change to take on the patient-role – an experience that was likely new to most students. In the opinion of the course developers, the advantage of role-playing outweighed that of standardized patients, which would also have involved additional financial and personnel costs. The active experience of the patient role was also supported by the students and evaluated as very positive in the course evaluations. Regarding the course content, there was concern prior to implementation that students would not volunteer to participate in the role plays. Therefore, it was mandated that each student must actively participate in a scenario at least once. This was ultimately well accepted by the students. For individual cases, the option of a written reflection paper as a substitute performance was kept open. In the briefing it is emphasized that the course takes place in a protected setting and that mistakes can be made and that a duty of confidentiality applies. Students are taught that this is precisely how a lasting learning effect can be achieved. Physicians who were judged by the course developers to have sufficient experience in ward rounds were requested individually to be instructors of the course. Medical teachers were either specialist for internal medicine or were internal medicine residents. The residents had to have sufficient ward round experience . In addition, they should also have the educational competence to adequately lead the course and moderate the discussion/feedback rounds. Initially, each course was conducted by two teachers: one physician took over the content-related course leadership, and one psychologist or pedagogue managed moderation and debriefing. Students reported back that it was especially important for them to be accompanied by a physician trainer during the facilitation and debriefing process. The physician could guide them in transferring this somewhat ideal world of simulation to the real world of medical ward rounds. Subsequently, the course was only led by physicians.In order to ensure a high quality of teaching, the instructors were briefed in advance by the course developers in form of structured individual training sessions. In addition to teaching the theoretical basics of ward round competence, instruction on the course procedure  was provided in the teaching clinic. In addition, medical teachers were trained in the basics of feedback and debriefing. New instructors participated as observers in at least one course. This was followed by a meeting to discuss possible challenges in the course and possible ways of dealing with these situations. At least the first course unit was accompanied by an experienced supervisor. In addition to the professional and content-related qualifications of the instructors, personal contact was also important to us in order to be able to assess the instructors' self-motivation and interest in the topic of ward rounds. Despite the complexity of the course, a homogeneous teaching quality was to be maintained. It was therefore decided to recruit teachers exclusively from our own internal medicine clinic and from the Department of Medical Education. This ultimately proved more challenging in recruiting new instructors, but still ensures short lines of communication and honest feedback loops.The SiLVi course has been offered since the summer term of 2012 and has been completed by 3466 students to date (as of 04/2020). The course was offered as a voluntary course after a trial period of two semesters. Thereafter, it was implemented as a mandatory course as part of the clerkship in internal medicine and has continued to date. Now that the course is mandatory, almost 100% of students have participated in the course. On average, 235 students have participated in the course per semester since the winter term 2014/2015. Even though the overall learning objectives and general course structure have not changed over the years, the SiLVi course has been adapted based on the research findings of the working group , 15], ,  to meet The SiLVi course in its current form  was evaluated by both instructors and students:students evaluated the simulation in terms of authenticity and were able to rate the course at the end using a scale.instructors evaluated the course in terms of its authenticity. The questions and their evaluation results are shown in figure 2 Overall, it was found that the students experienced the simulation as mostly authentic, which is an important evaluation parameter of a simulation environment. For the most part, they engaged with the simulation. Students did not feel overwhelmed by the course and felt well prepared for ward rounds. The course was rated an average of 2.2 on a scale of 1-5 (M=2.2±1.1). The instructors also felt that the course was authentic. In addition, they stated that the students benefited from the course and would have liked to have this course during their studies as preparation for later medical practice as well. In the course of the project development and the further scientific work of the research group, it became apparent that ward rounds - although its relevance is undisputed - have so far been addressed little or not at all, not only in the medical curriculum but also in residency training. Our course is a partial component on the long-term path to creating a ward round curriculum that should ideally extend into residency training. In addition to a ward round curriculum for medical school, a structured implementation in the clinical internship year would be useful. Furthermore, we would advocate the inclusion of ward round competence as a training objective in residency training. Since ward round competence is an EPA, a workplace-based assessment would be valuable to complete the important steps from a simulated ward round (students), to a ward round conducted under supervision (young residents), to the independent and autonomous conduction of ward rounds . In view of the current evaluation of the project, a pre/post measurement was introduced as a new form of evaluation to further confirm the teaching concept. For this, students had to state the objectives of a ward round in an online survey both before and after the course. In the future, for long-term monitoring of learning success and for testing practical competence, external assessment should ideally take place, for example in the form of an OSCE .The medium-term goal must remain to create corresponding projects for other training levels in the sense of a learning spiral. Finally, there is the additional possibility of promoting the teaching competence of clinical teachers through a train-the-trainer course. Further follow-up projects should focus on interdisciplinary collaboration  and collaborative clinical reasoning projects (fewer wrong decisions with competently managed ward rounds).In summary, after a corresponding needs analysis, the SiLVi course was successfully and sustainably implemented into the existing curriculum. The simulation was experienced by the students – as well as by the teachers – as an authentic situation and has already been completed by 3466 students (as of 04/2020). Since the ward round is a central part of daily work, a corresponding curriculum should be developed to optimally prepare students for their future work situation. Because of the many domains of competence, a longitudinal curriculum would be useful in which the individual competencies are first taught and then combined in a simulation course. This could be followed by transfer of practice with a teach-the-teacher course for clinical instructors and, in the long term, an EPA examination during residency training.Special thanks go to Dr. Stephanie Keil and Dr. Sophie Niedermaier-Patramani, who helped conceptualize the course and were crucial in its initial implementation. Furthermore, we would like to thank all participants of our research projects on ward round competence - the research results provided the opportunity to further develop the course in an evidence-based manner.We thank all the instructors of the SiLVi course for their commitment and constant feedback. We also thank the students for their course participation and feedback on the course. Furthermore, we would like to thank for the financial support of the project initiation by the Hildegard-Hampp-Humanitas Trust.The authors declare that they have no competing interests.


The interval between the physician consultations was 6.2 ± 3.0 months, during which cases lost 5.3 ± 2.3 kg of body weight and controls gained 0.2 ± 2.3 kg (p < 0.001). Cases and controls did not differ in demographics, disease duration, disease phenotype or medical history. Independent IBD-related malnutrition risk factors were: 18.5 ≤ BMI ≤ 22 kg/m2 , high annual healthcare utility  and endoscopic disease activity . The IBD-MR was positively associated with malnutrition development independently of the MUST score . Among patients with low MUST scores determined during the index visit, identification of ≥2 IBD-MR factors was strongly associated with malnutrition development . (4) Conclusions: We identified IBD-related risk factors for malnutrition, highlighting the need for a disease-specific malnutrition screening tool, which may increase malnutrition risk detection.(1) Background: Malnutrition is a highly prevalent complication in patients with inflammatory bowel diseases (IBD). It is strongly associated with poor clinical outcomes and quality of life. Screening for malnutrition risk is recommended routinely; however, current malnutrition screening tools do not incorporate IBD specific characteristics and may be less adequate for screening these patients. Therefore, we aimed to identify IBD-related risk factors for development of malnutrition. (2) Methods: A retrospective case-control study among IBD patients attending the IBD clinic of the Tel-Aviv Medical Center for ≥2 consecutive physician consultations per year during 2017–2020. Cases who had normal nutritional status and developed malnutrition between visits were compared to matched controls who maintained normal nutritional status. Detailed information was gathered from medical files, including: demographics, disease phenotype, characteristics and activity, diet altering symptoms and comorbidities, medical and surgical history, annual healthcare utility, nutritional intake and the Malnutrition Universal Screening Tool (MUST) score. Univariate and multivariate analyses were used to identify malnutrition risk factors. The independent risk factors identified were summed up to calculate the IBD malnutrition risk score (IBD-MR). (3) Results: Data of 1596 IBD patients met the initial criteria for the study. Of these, 59 patients developed malnutrition and were defined as cases ( The prevalence of malnutrition in inflammatory bowel diseases (IBD) is estimated to be between 6.1% and 69.7% depending on the definition used, the type of IBD, the clinical setting and disease activity . MalnutrA retrospective matched case-control study. All data were collected from medical files. The study was approved by the local ethics committee of the Tel Aviv Medical Center (TLVMC).2 ≤ BMI ≤ 27 kg/m2, and did not answer malnutrition criteria of weight loss (as follows). At the following consecutive clinic visit (diagnostic visit), control participants maintained normal nutritional status, whereas cases developed malnutrition, defined according to the European Society for Clinical Nutrition and Metabolism (ESPEN) criteria [2; (2) a combination of weight loss >5% during 3 months or weight loss >10% indefinite of time with BMI < 20 kg/m2 for patients <70 years or BMI < 22 kg/m2 for patients >70 years [The study population included IBD patients treated at the IBD unit of the Department of Gastroenterology and Hepatology of the TLVMC in Israel. During their routine clinical visits, patients are thoroughly evaluated for their clinical disease manifestations and their nutritional status. Weight, weight change, nutritional intake and the MUST score are documented. Both cases and controls were identified using a systematic search protocol of all IBD patients >18 years of age, arriving at the clinic for ≥2 consecutive physician consultations per year, between 2017 and 2020. Cases and controls had normal nutritional status during their first visits to the clinic (index visit), defined as 18.5 kg/mcriteria  as one oExclusion criteria for both cases and controls included: lack of information regarding medical or nutritional status evaluation in either consecutive clinical visit; patients with a stoma, pregnancy or malnutrition diagnosed during the index visit. Controls were also excluded if they had developed malnutrition within 2 months post-diagnostic visit.Controls and cases were matched in a 1:1 ratio, based on age (±5 years), gender, disease (CD/UC/Pouch) and time of diagnostic clinic visit.Detailed information was gathered from medical files  for both the diagnostic clinic visit and the prior index visit. Information included details of demographics; disease phenotype at visit; and medical history—including chronic general diseases , chronic gastrointestinal (GI) disease  and psychological comorbidities ; surgical history; disease characteristics; endoscopic results (documented as simple endoscopic score (SES-CD) for CD, MAYO score for UC and pouch disease activity index (PDAI) for pouchitis); ±12 months from the index visit; physician global assessment (PGA); clinical disease activity; disease symptoms and manifestations (during the index visit); biochemical disease activity and blood test results (within 6 months of clinic visit); and medical treatment (at visit). Nutritional intake related symptoms ; annual healthcare utility ; reported nutritional intake from diet and supplementation, weight and weight loss; and the MUST score, were documented. Inadequate nutritional intake was determined if decreased or restricted eating was documented for any reason by any healthcare giver.The etiology for inadequate nutritional intake was categorized as one of the following: dental problems, oral aphtha, vomiting, constipation, nausea, dysphagia, diarrhea, pain on eating, loss of appetite, early satiety/fullness. If ≥2 etiologies were documented, the patient was categorized as suffering from multiple etiologies.2, generating two categories: 18.5 ≤ BMI ≤ 22 kg/m2 and BMI > 22 kg/m2) and annual healthcare utility (≥5 or <5 physician/multidisciplinary clinic visits per year).Continuous variables were categorized into dichotomous variables according to the study sample median: BMI at baseline . Continuous variables are presented as means ± SDs, and nominal variables as proportions.t-test or Mann–Whitney U tests for parametric and non-parametric continuous variables, respectively, and the Chi-square test for categorized data, were used to compare demographic and disease-related characteristics between cases and controls.Serum hemoglobin (HB) level; percentage of weight change; and the differences in BMI, HB, white blood cell (WBC) count and simple colitis clinical activity index (SCCAI) between the two visits were distributed normally. All the other continuous variables were not distributed normally according to Kolmogorov–Smirnov normality test. Cases and controls were compared during the index visit using univariate analysis: the independent samples 2. HBI and PGA scores differed between the groups in univariate analysis but were not included in multivariate analysis, since HBI is CD specific, and the PGA may be physician subjective. All parameters which were significantly associated with malnutrition development in multivariate analysis were entered together into a single model with automated parameter elimination. In the final multivariate logistic regression model, risk factors for malnutrition development were adjusted for potential confounders and for one another. Of all significantly associated risk factors which represent disease activity , endoscopic disease activity was chosen to be included as the most IBD specific parameter of disease activity.Multivariate logistic regression analysis was used to identify independent IBD-related risk factors for malnutrition development, after adjustments for potential confounders and the MUST score. Parameters which were examined by multivariate analysis were those which significantly differed between cases and controls in univariate analysis. These included steroid therapy, elevated CRP, elevated calprotectin, following an elimination diet, high annual healthcare utility, endoscopic disease activity, high stool frequency, moderate–severe abdominal pain and 18.5 ≤ BMI ≤ 22 kg/mThe number of IBD-related malnutrition risk factors was summed, and the malnutrition development risk (IBD-MR score) was accordingly categorized as: low risk (0 factors), medium risk (1 factor) and high risk (2 or 3 factors).n = 59) were selected from the remaining 1466 patients who had normal nutritional status throughout the two consecutive clinic visits, and who were individually matched to cases. A flowchart of study population selection incorporating a timeline of physician consultation visits, from which data were collected, is depicted in Of the 1596 patients who were treated at the IBD unit of the TLVMC between the years 2017 and 2020, 130 patients were defined as having malnutrition. Of these, 59 patients met the inclusion criteria as cases and had normal nutritional status during the index visit. Matched control patients , and levels of serum albumin and blood hemoglobin. Nonetheless, cases had a significantly lower mean BMI, and had higher proportions of reported weight loss during the 6 months prior to the index visit.During the index visit, both cases and controls had normal mean BMI . Changes in mean hemoglobin level, clinical and biochemical disease activity markers differed significantly between cases and controls during the follow-up period, whereas other nutritional and clinical characteristics did not differ between visits in both cases and controls , CRP > 0.5  and steroid therapy  were all positively associated with malnutrition development after adjustment for disease duration, age of diagnosis and MUST score , high annual healthcare utility , abdominal pain , 18.5 ≤ BMI ≤ 22 kg/mST score .2 and the number of these risk factors . Identification of ≥2 IBD-MR factors during the index visit was strongly associated with the odds of malnutrition development .When assessing these risk factors among a subpopulation of patients with a MUST score of 0 during the index visit, the number of IBD-MR factors was positively associated with malnutrition development, after adjustment for disease duration and age of diagnosis , which is used to assess current malnutrition and not to predict future risk of malnutrition . The SakImportantly, the associations shown in this study might be underestimations of the true associations with malnutrition development, as cases showed higher rates of malnutrition preventive interventions, such as referral to a dietician, use of partial enteral nutrition and therapy upgrading. As seen, these measures were not able to prevent malnutrition development among cases.The limitations of this study include the potential information bias of a case-control study. This bias was probably small due to a meticulous and standardized data collection protocol, with systematic data validation, so potential data handling bias was minimized. Data were extracted from all hospital visits—including visits with nurses and dieticians, and visits to the emergency room and other supporting clinics of the IBD unit—so that the missing data bias would be minimal. Data were gathered by one observer, in the same manner in consecutive cases and controls, to prevent differential information bias. Still, differential misclassification of dietary measures among cases is possible and could not be ruled out. A non-differential misclassification bias of nutritional status may have existed, since it was determined based on BMI and weight loss alone, without information regarding body composition, which has recently been at the center of nutritional evaluation recommendations, such as the Global Leadership Initiative on Malnutrition (GLIM) Criteria . AdditioOn the other hand, strengths of our study included recruitment of cases and controls from the same population, with comparable demographic and medical history characteristics, thereby minimizing potential selection bias and residual confounding. In terms of external validity, this study population was selected from the adult population of patients treated in a tertiary hospital; thus, our findings cannot be generalized to the entire IBD population, due to potential referral filter bias. However, the IBD-related characteristics which were found here to be strongly and independently associated with malnutrition development are universal, and not necessarily associated with the tertiary nature of our clinic. Parameters of the IBD-MR score reflect disease activity and management, and may therefore be relevant for all IBD patients. Additional advantages included our extensive and meticulous data collection, and the direct measuring of malnutrition as the study outcome, enabling predictive criterion validity for the IBD-MR score.In conclusion, our study elaborated on IBD-related risk factors for malnutrition, highlighting the need for a disease-specific screening tool, which takes into account the unique clinical manifestations, dietary habits and chronic inflammatory nature of this population. These findings should be further validated in a larger, prospective study, which might enable formulating a prediction model for malnutrition among IBD patients.


This paper describes a model for estimating COVID-19 related excess deaths that are a direct consequence of insufficient hospital ward bed and intensive care unit (ICU) capacity.Compartmental models were used to estimate deaths under different combinations of ICU and ward care required and received in England up to late April 2021. Model parameters were sourced from publicly available government information and organisations collating COVID-19 data. A sub-model was used to estimate the mortality scalars that represent increased mortality due to insufficient ICU or general ward bed capacity. Three illustrative scenarios for admissions numbers, ‘Optimistic’, ‘Middling’ and ‘Pessimistic’, were modelled and compared with the subsequent observations to the 3rd February.The key output was the demand and capacity model described. There were no excess deaths from a lack of capacity in the ‘Optimistic’ scenario. Several of the ‘Middling’ scenario applications resulted in excess deaths—up to 597 deaths (0.6% increase) with a 20% reduction compared to best estimate ICU capacity. All the ‘Pessimistic’ scenario applications resulted in excess deaths, ranging from 49,178 (17.0% increase) for a 20% increase in ward bed availability, to 103,735 (35.8% increase) for a 20% shortfall in ward bed availability. These scenarios took no account of the emergence of the new, more transmissible, variant of concern (b.1.1.7).Mortality is increased when hospital demand exceeds available capacity. No excess deaths from breaching capacity would be expected under the ‘Optimistic’ scenario. The ‘Middling’ scenario could result in some excess deaths—up to a 0.7% increase relative to the total number of deaths. The ‘Pessimistic’ scenario would have resulted in significant excess deaths. Our sensitivity analysis indicated a range between 49,178 (17% increase) and 103,735 (35.8% increase). Given the new variant, the pessimistic scenario appeared increasingly likely and could have resulted in a substantial increase in the number of COVID-19 deaths. In the event, it would appear that capacity was not breached at any stage at a national level with no excess deaths. it will remain unclear if minor local capacity breaches resulted in any small number of excess deaths.The online version contains supplementary material available at 10.1186/s12911-021-01504-y. The number of COVID-19 deaths in the UK was 74,125 deaths and the number of known cases was 2,542,069 as of the 2nd January 2021 representing a case fatality rate (CFR) of 2.9%. The Office for National Statistics (ONS) Coronavirus (COVID-19) Infection Survey estimated that 8.7% of people in England still had antibodies at detectable levels based upon serological testing [IFR estimates are typically made in the context of adequate capacity of health care services including hospital beds and ICU beds. Should the demand for ICU beds exceed the supply, then the IFR would be expected to rise. In this paper we describe a demand and capacity model designed to estimate the number of COVID-19 deaths that would directly arise from a lack of ICU and ward beds. Such a model currently does not exist for the UK in the public domain.In November 2020 we began development of a model to estimate what increases in deaths could be expected as a direct consequence of a lack of hospital bed capacity, and in particular ICU beds. Due to availability of data, the model was restricted to England.Estimating the ICU capacity in England is complicated, as the actual capacity at a given point of time varies between usual bedbase and the maximum surge capacity created to handle increasing demand during a pandemic. There were estimated to be 4114 ICU beds in England pre-pandemic . HoweverAt the start of the pandemic a series of field hospitals were constructed at eight sites across England. The capacity provided by these field hospitals is flexible according to circumstance, but it is estimated that this would potentially provide an additional 8000 general ward beds and 500 ICU beds though there may be staffing constraints that limit this number .In this paper we describe a model for estimating the number of additional deaths that occur from a lack of capacity under different scenarios. These are illustrative scenarios and not forecasts. Parameterization of the model can be modified according to available information and updated over time.https://github.com/Crystallize/COVID19_ExceedingCapacityModel .Once COVID-19 mortality rates for ward and ICU patients both within and outside of capacity were calibrated, the number of deaths occurring ‘within capacity’ and the number that occur directly as a result of being out of capacity could be calculated. The number of ‘out of capacity’ deaths does not include the number of deaths that would have been expected to occur if normal care had been received, and so represent ‘excess’ deaths occurring because the capacity limit was breached.Description of each step in the modelling.We will now describe the purpose and workings of the model in more detail.The pre-pandemic  spare bed availability in the general wards in England is estimated at 9,769 and the ICU spare bed capacity as 817 beds from a study of hospital capacity in the COVID-19 pandemic by the Medical Research Council, Public Health England, The National Institute of Health Research and Imperial College . AltogetThe age distribution of admissions was required in 5-year age bands up to the age of 80 years with one category for those of age 80-years and over (if this data is available it can be applied directly in the model removing the need for this estimation step). The age distribution in ICUs is lower than on the wards with an average age of 62 years and with only a small proportion of those over 80-years being fit enough for invasive ventilation . These wIn this step, we applied the distribution of admissions by age to the weekly admission demand from the scenarios to calculate the percentage of admissions accounted for by each year of age.th December 2020, and the total number of COVID-19 hospital admissions up to the 18th December 2020 from the Gov.UK COVID-19 data dashboard [Next, we calculated the proportion of admissions that require intensive care and ward care by age for each 5-year age band, with one age band for those aged 80 years or over. This is done using data on the age breakdown of admissions and total admission numbers to ICU from the ICNARC report of the 18In this step, we separated the weekly demand for general ward care by age into two tables; one for those cared for within the expected hospital capacity, and a second for those who fail to receive any hospital care when required because of lack of capacity.In this step we separated the weekly demand for ICU care by age into three tables; one for those cared for within the expected ICU capacity, a second for those who receive only ward care when ICU care is required because of no capacity, and a third for those who fail to receive any hospital care when required.This is a critical step in the modelling as it is here that the estimate of the increase in COVID-19 mortality in the absence of a ward or ITU bed is determined. It would be very challenging to directly make a meaningful estimate of the increase in mortality overall, given the diverse range of severity of COVID-19 and the distribution of people with COVID-19 across the different pathways that unfold. In order to reduce uncertainty, it is necessary to map the flow of individuals through treatment pathways and consider the impact on mortality that would arise from depriving any individual requiring that element of care. The uncertainty in estimating the impact of lack of capacity is greatly reduced by considering each element of care in the pathway separately than when considering the impact across the pathway as a whole. Consequently, we have taken the approach of compartmentalizing the care-pathway for COVID-19, identifying the most critical element of the pathway for different individuals and the volume of people in those compartments from observed data. For example, for people who never need more than high-flow oxygen on a general ward > 35% O2), they are allocated to this compartment and their risk is not related to lower-risk care compartments like ‘general ward care’. Similarly, for individuals who pass through general ward care and high flow oxygen to ITU admission, continuous positive airways pressure’ support (CPAP) and eventually invasive mechanical ventilation (IMV), then they are allocated to riskiest of these compartments—the IMV. In the latter case, we can observe the survival from data in this group and also make a reasonably reliable judgment that if the option of IMV is removed, then the survival will be close to zero. There will be greater uncertainty in the estimation of the impact of removing lower levels of care, but structure can be applied to estimating the impact of depriving this care by considering the fatal events that are averted by the care and their risk in the absence of that care. The evidence and assumptions used in setting the mortality rates in each compartment can be found in Table , they arWe estimated the multiplier of COVID-19 mortality risk for ward and ICU care COVID-19 patients when there is (1) no ICU capacity and (2) when there is neither ward nor ICU capacity in comparison to the in-capacity mortality. The output from this sub-model is only dependent on the ‘hospitalised’ compartment and the modelling is not age dependent.The proportion of patients requiring intensive care was taken from the results of the modelling step “Splitting Admissions into ICU and Ward” (8%). Those receiving general ward care or ICU care were segmented into the categories shown in Table The expected numbers of deaths in each category calculated using the assumed mortality rate and weighted by the proportions in the categories using the formulae below.From the Excess Mortality Sub-model, we estimated a hazard ratio of 1.99 for COVID-19 mortality in those needing ICU care when no ICU bed was available but there was a ward bed, and 9.02 when there was neither an ICU nor ward bed available. For those needing ward care only, the hazard ratio is 3.69 when no hospital bed is available. Sensitivity testing indicated that results were not especially sensitive to small changes in these hazard ratios (± 20%).In this step, we estimated the in-capacity COVID-19 mortality rate by age in 5-year age bands interpolating from data from the cumulative COVID-19 daily deaths report on the NHS England website and using the age distributions for admissions calculated in the modelling step “Estimating Admissions by Age” . Data wath November 2020 ICNARC report on COVID-19 in intensive care [In this step, we calculated the in-capacity COVID-19 mortality rates by 5-year age bands in ICU. Data was taken from the 6ive care . The morIn this step we took the COVID-19 mortality rates by age calculated in the previous two modelling steps and the hazard ratios from the ‘Excess Mortality Model’ step to calculate the mortality rates when no ICU beds and no ward beds are available respectively. The mortality rate under the scenario ‘s’ is calculated using the equation:entclass1pt{minimath December 2020, with ICU deaths calculated as 15% of the total number of deaths (as there are significant delays in reporting the deaths in the ICNARC data).In this step, we calculated the number of COVID-19 deaths each week from the corresponding number of admissions generated by the ‘Ward Demand’ and ‘ICU Demand’ steps and the in-capacity mortality rates from the previous ‘Mortality Rates’ step. Observed data is used up to the 9The number of deaths in ICU within capacity as the dot product of the vector of ICU demand within ICU capacity by age from step 'ICU Demand' and the vector of mortality rates from step ‘Mortality Rates’.The number of deaths in patients requiring ICU care where only ward care was available, as the dot product of the vector of ICU demand outside ICU by age from step 'ICU Demand' and the vector of mortality rates from step ‘Mortality Rates’.The number of deaths in patients requiring ICU care where neither ward nor ICU care was available as the dot product of the vector of ICU demand outside both ICU and ward by age from step 'ICU Demand' and the vector of mortality rates from step ‘Mortality Rates’.The number of deaths in patients requiring ward care only as the dot product of the vector of ward demand within ward capacity by age from step 'Ward Demand' and the vector of mortality rates from step ‘Mortality Rates’.The number of deaths in patients requiring ward care where ward care was not available as the dot product of the vector of ward demand outside ward capacity by age from step 'Ward Demand' and the vector of mortality rates from step ‘Mortality Rates’.The total number of deaths each week under the current scenario including both ICU and ward deaths as the sum of all results in steps 1–5.The total number of deaths in each calendar week in both the ICU and ward care groups calculated in the step ‘Deaths—In capacity’ was taken and subtracted from the capacity constrained total in step 6 to provide the number of deaths arising as a direct result of the lack of an ICU or ward bed.In this step, we calculated the numbers of deaths arising each week as a direct result of failing to get an ICU or ward bed. Observed data is used up to the 9th December 2020. A series of seven calculations were used:We applied three scenarios for admission demand from the week beginning 16th December 2020 through to the week beginning 28th April 2021  appears to be about 56% (95% CI 50%-74%) more transmissible than the existing variants and appears to have a higher case-fatality rate , 16. AltIn the longer term, there are now three vaccines approved for use in the UK, as of the 19th January 2021 . It is eThe estimate of bed availability is determined using the mean length of stay on the ward or in ICU. The distribution of occupants by length of stay will change over time which may result in a slow consumption of capacity that is not captured in this model. For example, a higher proportion of afflicted younger patients in hospital may lead to longer bed occupancy both in ward and critical care, as withdrawal of active treatment in view of futility is less likely to take place in this group.Mortality rates are affected by constraints other than just bed availability including staffing and equipment.The model will not capture the transition between low mortality with full capacity and the high mortality from lack of a bed that arises from stressing of the system before capacity is absent .Capacity estimates are fixed throughout the model when, in fact, new resources may be recruited over time, or capacity may fall in response to disruption of staffing and supplies.Age specific case fatality rates are assumed to be static, but in fact may change, either due to changes in virulence, improvement in care or dilution of standards of care during a surge scenario.The oxygen cut-off of 35% is based on clinical opinion, and there is no empirical study in support of this threshold for obvious reasons. However, often clinical practice may be to err on the side of caution in a ward setting and to keep a patient on a slightly higher fractionated oxygen than s/he needs and therefore a patient on a lower than 35% FiO2 may actually need even smaller amounts of oxygen, and therefore the assumption is that s/he would withstand the lack of medical oxygen with a degree of success.Here we list and discuss the limitations of the model:Intensive care resources are constrained not only by bed availability but also by equipment and staffing. A combination of all three is required for optimal care in ICU. In reality there is not a simple binary state of presence or absence of these factors and skills. A degradation of equipment maintenance, training around new equipment and distribution as well as reductions in the effectiveness of staff, either because staff-to-patient ratios fall as demand rises, or because of staff sickness due to COVID-19 or simply the physical and emotional fatigue as the pandemic continues is also seen. An analysis of within-capacity mortality rates in ICU by bed occupancy has found that there is an almost linear increase in mortality with no excess mortality at 0% bed occupancy to a 92% increase in mortality by 100% occupancy .The modelling by McCabe et al. suggests that ICU capacity is first constrained by bed availability, though lack of nurses and junior doctors is close behind . They inDecision making may change in the face of increasing demand either with formal revisions of treatment thresholds as resources become increasingly scarce or with the introduction of triaging. On a less formal level, the heuristics used by clinicians in their everyday management of patients may vary as competing pressures rise. For example, at times of abundant capacity, the thresholds for transferring patients into ICU for a trial to see if a patient with poor chance of survival recovers with a short stay, may be lower than when there is severe limitation on capacity.One of the most uncertain parts of the modelling is the determination of the multipliers of risk in the section ‘Excess Mortality Submodel’. We estimated that the multiplier for the scenario of no ICU bed when one was required was 1.99. A recent observational study of 4,032 ICU admissions across 114 hospital trusts found a rising mortality with bed occupancy . The estAn important but unrealistic assumption in the model is that there is perfect distribution of resources with respect to demand across the country and that no patient is refused care whilst there remains a bed anywhere in England. ICUs are organized into networks which facilitate the transfer of patients from one hospital to another when ICU beds in a hospital run out, but even a delay of a few hours in transferring a patient to an ICU bed can influence outcome. Furthermore, even in the case of bed availability in a different hospital, it cannot be assumed that the patient in the referring and at-capacity hospital may be fit enough to able to be transferred safely. All the ICUs in a network are likely to have correlated demand and may all run out of space at the same time. In these circumstances, transfers would need to be arranged between networks or regions and this would entail yet further delay and challenges with consequent impact on outcomes.It is notable that the sensitivity of the excess deaths to ICU capacity is much greater than it is to ward bed capacity at marginal breaches of capacity, but that large scale breaches of capacity are more sensitive to ward bed capacity. There are far more ward beds than ICU beds, and there is an assumption that ICU capacity would be exhausted long before ward bed capacity.Here we describe a demand and capacity model for general hospital and intensive care beds in the context of the COVID-19 pandemic in England. The model allows a user to understand the excess COVID-19 mortality impact arising as a direct consequence of capacity being breached under various scenarios or forecasts of hospital admissions. The scenarios described in this paper are illustrative and are not forecasts.We estimated the number of excess COVID-19 deaths up to the end of April 2021 that would arise from lack of ward and ICU capacity under different demand assumptions from December 16th, 2020. No excess deaths from excess capacity would be expected under the ‘Optimistic’ assumptions of demand but would reach between 49,178 and 103,735 under the ‘Pessimistic’ scenario. Without the new variant, exceeding capacity for hospital and ICU beds was not the most likely outcome but given the new variant it appeared more plausible and could have result in a substantial increase in the number of COVID-19 deaths. In the event, it would appear that capacity was not breached at a national level any stage, and, under an assumption of a perfectly even distribution of demand and capacity, there would be no excess deaths due to lack of capacity expected under this set of assumptions. However, distribution of demand and capacity is imperfect. It will remain unclear if minor local capacity breaches resulted in any small number of excess deaths.Additional file 1. https://github.com/Crystallize/COVID19_ExceedingCapacityModel. Link to model on GitHub.


Based on the theory of trade added value, this paper discusses the potential actual trade scale and benefit damage degree of the two countries under the background of big country game by measuring the real trade scale of China and the USA, simulating the economic impact of tariffs imposed by China and the USA and utilizing Wang–Wei–Zhu (WWZ) method to decompose the potential changes in Sino-US trade. The results show that: firstly, the size of China-US trade in terms of total value is significantly overestimated and China's overall trade with the USA in 2001–2014 was overestimated by an average of 3.06 percent, of which goods trade was overestimated by 8.06 percent. Secondly, although tariff increases can reduce the degree of trade imbalance between China and the USA to some extent, the adverse effects are mutual and global, and the European Union, the Association of Southeast Asian Nations (ASEAN), Japan and Canada become the main transfer countries of Sino-US trade. Thirdly, the pattern of China's final exports and the US' intermediate exports determines that China's trade interests are more damaged than those of the USA. It is proved that there is a big gap between China and the USA in the depth and breadth of China's participation in the value chain division of labor and the trade scale measured by Gross Domestic Product is more instructive than the total value. The global value chain is undergoing profound changes, and its rapid development has become an important feature of globalization; meanwhile, the rising China has gradually become the backbone of the global value chain. As a producer and exporter of the world's major industrial products, China's gradual transition from the downstream value chain relying on foreign advanced technology and patents to the upper and middle reaches not only imperceptibly affects the adjustment of international industrial structure and the reconstruction of global value chain. It also broke the Sino-US industrial chain division of labor “balance.” The rise of China's economy has made the long-time "global hegemony" of the USA unilaterally considered threatened and provoked trade disputes. As a catalyst, the epidemic of novel coronavirus intensifies this competitive relationship, the geopolitical deterioration of China and the USA as well as the great power game results in the reconstruction of international rules , suggested that measuring trade value added could more truly reflect a country's trade level . On the basis of value added theory, Wang et al., , b gave In terms of the empirical point of view, on the basis of trade value added theory, dynamic panel model is used to quantitatively analyze the influence of each GVC index on bilateral trade value added difference through measuring GVC position, forward and backward participation index. The results show that integration GVC division of labor significantly improves China's trade interests and backward participation is the main way for China to profit. American countermeasures against China significantly inhibit China's total export correlation and distinguish intermediate from final value added , which can be used for calculation, has successfully established the quantitative relationship between the components of the economy. Compared to the input–output model, the CGE model links the sectors and industries involved in economic change. The potential economic impact of policy change is accurately simulated from macro perspective, such as trade balance, investment balance, GDP change, factor endowment, government, family, individual behavior Dixon, . Based oDivision of national departments According to the GTAP 9.0 database and research content, according to the ranking of the world's largest economies, this paper combines the original 140 countries and 57 sectors into seven countries and eight industries, including China, the USA, Japan, Canada, ASEAN (except Myanmar), the European Union and other countries; industries are divided into eight categories: agriculture, forestry, animal husbandry and fishery, mining, labor manufacturing, capital manufacturing, technology manufacturing, life service, knowledge service and public service.Benchmark scheme setting This paper assumes that all countries will adjust the current trade, investment, factor flow, government purchase, household consumption and other economic variables through the historical data in the Global Trade Analysis Project (GTAP) database according to the current policy before the Sino-US trade tariff is imposed.Scenario simulation settings On May 5, 2019, the US government has announced a 25% tariff on $250 billion in imports. It contains $50 billion of Chinese goods announced on September 18, 2018. China then announced an increase in tariffs to 5–25% on US goods worth $60 billion. This paper, based on the US new tariff imposed on the 200 billion list of goods and China's 60 billion list of goods, set tariff shock closure conditions for benchmark scenarios.This section presents the simulation results of the study based on the GTPA model which is considered as effective tool to quantify the trade issues.Table Secondly, China's economy is more damaged than the USA. China's real GDP decline is about ten times that of the USA, while China's decline is 3.03, but the USA is only 0.32; from a point of view of social welfare, China's welfare loss is 1.76 times that of the USA; and in terms of household income and private consumption indicators, China's decline is far above the USA. The reason is that China mainly exports final goods, and the trade pattern of the USA mainly exports intermediate goods determines that the American intermediate goods can quickly turn to other links in the global value chain to make up for the damage of exports.Thirdly, the impact of trade friction is global. From the point of view of trade balance, the trade imbalance between China and the USA increased by $14.684 billion, the USA increased by $69.551 billion, and other countries, such as Japan, Canada, ASEAN, the European Union and other countries, decreased to varying degrees, with the largest reduction in the European Union, followed by Japan, which shows that trade frictions in large economies will inevitably have a deep or shallow impact on third countries and have global characteristics.Table In general, Sino-US trade friction has the greatest impact on agriculture, forestry, animal husbandry, fishery and technology manufacturing in both countries. As a developed economy, Japan is dominated by trade transfer and market segmentation between China and the USA. Its high-tech industries quickly occupy the share of the world market, and the export range has increased by 7.28%, but the exports of other industries have been negatively affected to being different.Table This section will discuss the model and the decomposition of Sino-US trade friction based on WWZ method and other decomposition methods or theories.Koopman et al.,  further N sectors. Table This paper draws lessons from the WWZ method, and according to the realistic basis of Sino-US trade dispute, based on the world input–output model, the total trade accounting framework in Wang et al.  is extenIn the model,According to the origin and final absorption destination of trade products, the total value after the change is decomposed into 16 items by WWZ method and finally classified into ten items. Table From the simulation results of decomposition, China's trade structure mainly exports final goods and imports intermediate goods, while the US exports intermediate goods and imports final goods. But the global characteristics of trade friction make China and the US trade interests damaged, and China's negative impact is greater than the USA. Among them, trade between China and the USA measured on total export value overestimates trade losses, namely China's export DVA fell by $113.697 billion, accounting for 67.32 per cent of the decline in total exports, TE overvalued $55.191 billion, and US export DVA fell by $75.752 billion, TE overvalued $9.253 billion. The difference of overvalued scale depends on the difference of bilateral trade structure between China and the USA. As far as the trade balance is concerned, China's import and export trade balance has actually decreased by US $51.343 billion, which is 11.68% overestimated in terms of gross value. However, the change of US import and export trade balance has been underestimated by US $83.570 billion, which shows that under the influence of tariffs, in order to satisfy domestic needs, the US imports transfer faster than China.Affected by the trade structure, China's domestic value added exports to the USA fell by $156.735 billion, DVA exports to China fell by $42.281 billion. Although China's export DVA to the USA has decreased more, some of the RDV returned to China from the USA and were absorbed increased by $76.22 billion. This suggests that China indirectly exports more products to the USA through third countries which is consistent with Xiao Zhimin's (2019) study. Similarly, the Sino-US trade surplus fell by $138.15 billion under tariff pressure, DVA reduction of $114.454 billion, changes in trade imbalances were overestimated by 17.13 per cent  Index as an example, the average Normalized Revealed Comparative Advantage (NRCA) Index of the US knowledge-based services industry in 2001–2014 was 1.43; compared to 1.81 under the traditional caliber, it was overestimated by 0.38. Secondly, although tariffs can reduce the degree of trade imbalance between China and the USA to some extent, the adverse effects are mutual and global. Compared to the tariff increase, China's total exports fell 5.09, total imports fell 6.90, and total imports and exports of the USA fell 2.87 percent and 4.61 percent, respectively. And the European Union, ASEAN, Japan and Canada become the main transfer countries of Sino-US trade. Thirdly, the differences in bilateral trade structure between China and the USA determine that China's trade interests are more damaged than those of the USA. China mainly exports final products, and labor manufacturing industry participates in the division of labor in the global value chain, which has the advantage of production in “smile curve.” The USA mainly exports intermediate products, in the value chain R & D and sales at both ends, profitability is stronger. Under total value statistics, China's exports to the USA suffered an average of $27.602 billion which was overvalued by 29.02% compared with added value, while the US exports to China suffered an average of $10.339 billion, overvalued by 51.11%, with technology manufacturing among the top industries. However, as China gradually changes from a manufacturing power to a manufacturing power, the gap between China and the USA is gradually narrowing, whatever it is the scale of trade or GVC status. According to the results of the study, the following conclusions can be drawn. Firstly, the scale of Sino-US trade in terms of total value is overestimated, and the overall trade between China and the USA is overestimated by 3.06% on average in 2001–2014, of which the average trade in goods is overestimated by 8.06% on average.As the core competitiveness of a country, high-tech is not only the "powerful factor" for China to enhance its international competitiveness and enhance its international voice, but also the focus of the USA. Since the Sino-US trade war in 2018 to novel coronavirus epidemic now, the implementation of China's "powerful factor" technology long-arm jurisdiction, high-tech has been the core focus of the USA to suppress China. Facing the trade friction between China and the USA in the post-epidemic era, firstly, China needs to continue to develop high-tech manufacturing industry, tilt the policy of core technology manufacturing industry, increase R & D investment in scientific research institutes, universities and other related specialties, and encourage more outstanding talents to invest in industries such as chips and 5G. Secondly, enhancing regional cooperation and making full utilization of the 19 FTAs signed with 26 countries or regions, especially the newly signed RCEP, to integrate Asia–Pacific resources and promote regional cooperation can not only buffer the losses caused by Sino-US trade frictions, but also enhance regional partnerships. Lastly, China should speed up the FTA negotiations between China, Japan and South Korea, the China–EU investment agreement negotiations and the upgrading of existing FTA, expand China's trade circle in breadth and depth and combine the "Belt and Road" initiative to actively regulate the high-standard and high-level free trade area network system to enhance the international voice.


With the recent development of video compression methods, video transmission on traditional devices and video distribution using networks has increased in various devices such as drones, IP cameras, and small IoT devices. As a result, the demand for encryption techniques such as MPEG-DASH for transmitting streams over networks is increasing. These video stream security methods guarantee stream confidentiality. However, they do not hide the fact that the encrypted stream is being transmitted over the network. Considering that sniffing attacks can analyze the entropy of the stream and scan huge amounts of traffic on the network, to solve this problem, the deception method is required, which appears unencrypted but a confidential stream. In this paper, we propose the new deception method that utilizes standard NAL unit rules of video codec, where the unpromised device shows the cover video and the promised device shows the secret video for deceptive security. This method allows a low encryption cost and the stream to dodge entropy-based sniffing scan attacks. The proposed stream shows that successful decoding using five standard decoders and processing performance was 61% faster than the conventional encryption method in the test signal conformance set. In addition, a network encrypted stream scan method the HEDGE showed classification results that our stream is similar to a compressed video. Currently, with the development of high-efficiency video codecs (HEVC), video traffic is used more often, accounting for approximately 80% of the total network traffic . TherefoDeception methods play an important role, especially within small networks, such as wireless LAN. This is because in a small network, it is easy to analyze the data of all the hosts to which they belong through the router to physically find the location of the monitoring assets hidden within a short distance. Given that the eavesdropping method through LAN sniffing uses the entropy analysis of the stream, it is possible to monitor all the huge traffic passing through the router . In a miStealth: The sender must use an unsuspecting method that can avoid entropy scanning to protect the physical monitoring device during the transmission process.Confidentiality: Even if a third party acquires a stream, it should not be able to decrypt hidden images and messages.Computational complexity: The encryption process must be sufficiently low for application to a small monitoring device.In summary, deception tactics are security techniques needed to protect themselves in a way that prevents an attacker from noticing information or presence. Today’s video stream encryption methods have made significant progress; however, when sending an encrypted stream, the eavesdropping technique makes it easy to expose the device’s presence. As with encryption, the strategy of not exposing the encrypted stream to the other is increasing; therefore, the requirements for the video security method satisfying this method are as follows:In this paper, our proposed method for compressed video streams satisfies all of the above conditions as follows: First, our algorithm does not use cryptographic encryption methods to satisfy stealthy and can avoid entropy scans. The method also uses deceptive cover video to be shown instead of secret video. Second, to achieve confidentiality, we analyze the header structure of video standard codecs to create a stream that is only accessed at promised devices without changing the encoder through header rules. Through this, the cover video is displayed to an unpromised device that does not know the rules of decoding a secret video.The contribution of our research is as follows: First, we propose a new deceptive security method with the cover video that our new framework is universally applicable to five codecs. Second, the secret message space is flexible and large that the video stream can be capable. Third, since there is no hardware encoder design that can be applied as a microcircuit for small monitoring surveillance. The remainder of this paper is organized as follows. The development of the Internet has enabled a vast amount of data transmission. Today, the network has huge traffic and its use is essential, but there is a problem that the data being transmitted are likely to be exposed through router. Because of this, network routers are always subject to wiretapping or malware infection. Therefore, as shown in Selective video syntax encryption has been proposed as an alternative to solve the video quality degradation of compressed video steganography methods. The initial selective video syntax encryption methods began with a full stream encryption method with a symmetric key that is sometimes referred to as the naïve encryption algorithm. When establishing the standard for moving picture experts group (MPEG) video codecs, the encryption method was not specified; therefore, a symmetric key encryption method for video streams was presented via MPEG-CENC (ISO/IEC 23001-7) . CENC ofAccordingly, given that the encoding process of the video stream is already promised in a complex manner close to encryption, this method focuses on the difficulty of decryption if the decoder side does not know the changed header rules. In , a way tWhen sniffers look at the selective encrypted stream, it looks like a transmission of continuously intentionally corrupted video. This will allow the sniffer to know that there is a deliberate change in the video header, meaning that there is a risk that they may try to correct the header through NALU frequency analysis.The purpose of steganography is to secretly convey messages that others do not notice on the cover stream. This deceptive method prevents a security system from noticing whether the stream is an important message ,17. The Compared to previous studies, steganography methods in the compressed domain have more small message space. In the compressed video, the stream has a variable length and high entropy. In , a methoThus, conventional steganography methods in compressed space cannot add many secret messages when the secret image size is high compared to the cover image. In addition, it is difficult to flexibly adjust the length of the secret message, and intervention in the encoding process is required, so there is a drawback that the standard encoder cannot be used as it is.Overall, there were several weaknesses in each related work. Selective encryption leaves encrypted evidence in the stream, or visual protection of secret video is not perfect. In the case of steganography, it has cover-video-quality distortion and small secret message space. Therefore, for information security, various methods should be applied simultaneously in a manner. In this paper, we propose a deception method that satisfies the requirements of conventional information security methods. Our method is faster than the selective encryption method due to header processing and has a larger secret message capacity than the steganography method.The proposed method utilizes standard header rules for video standards, such as the selective video syntax encryption method. We use cover videos for deception, such as the steganography method. This makes it possible to reduce the calculation cost while maintaining the confidentiality of messages and the chances of a secret message being discovered. The flow of the proposed method is the same as that in A. NALU Byte Stream Parsing and Split.A stream of video codecs consists of various types of NALU, each NALU starting with the start code. For example, for H.264 video codecs, NALU types include SPS, PPS, and IDR-pictures. When the stream is started, the front of the NALU starts with the start code 0 × 000001. The one byte that follows the start code can know what parameter information the stream has after it, via the NALU header. SPS and PPS contain the information needed to decode the slices displayed afterwards, such as video profile, number of video intensity bits, entropy coding mode, and resolution. IDR pictures include predictive mode and Huffman-coded block data. The 1-byte NALU header includes the following three bits. First, 1-bit size forbidden_zero_bit is used to provide a notification that there is a transmission error or header violation of NALU, and it is written as 0 if NALU is normal and 1 otherwise. Next, a size of 2 bits will inform the picture reference direction of the NALU corresponding to Nal_ref_idc. In the case of the I-frame, Nal_ref_idc set 11 and in other cases of P-frame then 10, and B-frames are set as 01. The next 5-bit length nal_unit_type indicates whether the corresponding NALU contains information for decoding or picture data. To interleave NALU, the nal_unit_type is important because a different type of processing is required. Let us express 5 bits in decimals: SPS is 7, PPS is 8, IDR-picture is 5, and other types that have picture data are 1, 2, 3, and 4. Overall, three bits of forbidden_zero_bit and Nal_ref_idc in NALU type are indifferent, and the subsequent five bits are phrased only for types 1–5. Thus, after the H.264 start code, the 1-byte test pattern is shown as follows: B. NALU Interleaving.S, while n is the number of cover NALUs and m is the number of secret NALUs:S isS refers to the entire interleaved video stream. If n is In this stage, the stream of the cover video and the secret video in the previous section are interleaved into one stream. Before the interleaving, there are several modulation methods of secret images for confidentiality. The modulation methods can use any invertible function, such as byte-order-reverse or encryption algorithms. However, we recommend using simple byte-order-reverse. This is because the inverse-arranged byte stream function does not increase the computational complexity and has little effect on statistical features such as entropy. Next, considering that the number of cover videos and secret NALU number are not the same, we repeat the cover NALU in the same way as the numbers of secret NALU or the trim option in interleaving. As shown in When interleaved with one stream, an emulation prevention process should be conducted. The secret stream space can be placed in an encrypted stream or characters, video, etc., but bytes such as start code can appear in the stream. If there is a start code in the secret video, the decoder emulates the next NALU decoding stage, meaning that an emulation prevention process must be removed. When the video encoder completes the picture in the entropy coding stage, a stream called the string of data bits (SODB) is completed, as shown in C. Secret NALU Extraction.S can be listed as follows.S begins by dividing them into the order of NALUs received based on the start code. For example, in H.264, whenever 0 × 000001 is received in the stream, the inverse function is performed again in the whole of the previous NALU. Finally, the following stream The secret video is returned to be decrypted at this stage for the receiver device. The secret message can be promised between transmitter and receiver in a variety of ways; if an invertible function is used for a secret message, the received stream For the experiment and evaluation of the proposed method, the proposed deception method was performed in the conformance specification for H.264 and H.265 sequences for video sequence evaluation in ITU-T ,33. The The proposed algorithm can be used in most codecs by utilizing the characteristics of NALU, but the detailed header name and byte code are slightly different for each codec, so the interleaving method used in the experiment is summarized as shown in Next, to evaluate the plausibility of the stream, we performed an evaluation of HEDGE , which ii and The following is the encryption speed evaluation of the proposed method with related encryption works. Next, the capacity compared with the related steganography is as follows. The proposed method can flexibly control the cover video to contain the secret video for which we used a 1:1 ratio for this capacity comparison. However, other steganography studies have generated a large amount of overhead such as that seen in The other comparison methods are only a few secret messages of 0.33% and 2.72% in the cover video. Therefore, assuming that the same secret message is required, the required overheads are close to 302 times and 36 times, respectively.Finally, Overall, a comparison of the other features from related works and the proposed method is presented as follows. Comparison of selective video syntax encryption method: Selective video encryption techniques typically output visually protected hard identification images or non-decodable image. This makes the sniffers aware that the stream is confidential. However, the proposed method decoded cover video first that was not classified as an encrypted stream, as shown in experiments. However, the proposed deception method utilizes the standard NALU structure such that our deception methods have the same tolerance as the standards video codec, even if the NALU is damaged. The data after excluding the damaged NAL can be decoded. Therefore, the proposed method is effective against data contamination. Comparison with the compressed video steganography method: Compressed video streams have very high entropy, so it is difficult to insert large secret messages in the compressed domain. For this reason, the conventional state-of-the-art compressed video steganography method has a very small secret message space. Considering that the cover video and secret message have an approximately 20:1 ratio, only a few secret messages can be transferred. Furthermore, the steganography method manipulates the symbol during the encoding process so that it is necessary to change the hardware design of the encoder. Therefore, there is a disadvantage that the hardware-implemented video encoder cannot be used as the original design. Furthermore, because the secret message manipulates the video symbol of the cover video such that it causes a unique pattern and suspicion in the cover video. On the other hand, the proposed method can freely adjust the ratio between the cover video and the secret video and can adjust the video quality of the secret video according to the purpose of flexibly dealing with it. Furthermore, there is an advantage that the hardware designed standard encoder can be used as the original, and the video quality of the cover video is not distorted in the proposed method. In this paper, we proposed a new compressed video stream deception method that can transmit a secret video in a cover video using the header structure of a video codec. The results show that the proposed deception method is almost the same as the original stream that avoided network scan eavesdropping for a network traffic analysis method HEDGE and reduced the computational complexity compared to encryption methods with partial NALU processing. Our deceptive method has a large secret space compared to other steganography methods, which was appropriate for video deception techniques. In addition, our proposed method uses an original video encoder design that can be applied to small monitoring devices in real-time with a standard. Therefore, compared to conventional encryption and steganography methods, it was confirmed that there are advantages in applying a small device. According to this study, it is expected that information security for deceptive methods will be diversified.