Attitudes towards vaccination are associated with vaccination behaviour among university students : Jannis Trümmler

Introduction Vaccination behaviour is influenced by various determinants. Evidence indicates a higher COVID-19 vaccine hesitancy among university students due to their age and a lower risk of complications compared to the general population in Germany. However, little is known about other COVID-19-related determinants for the population of German university students. This study aimed to investigate determinants of vaccination behaviour among German university students. Methods The cross-sectional COVID-19 German Student Well-being Study was conducted at five German universities at the end of 2021 via an online survey (n = 7.267). Multiple logistic regressions were calculated to examine associations of vaccination behaviour (not vaccinated vs. fully vaccinated) and attitudes towards vaccination (5Cs: confidence in the safety of the vaccine, complacency - not perceiving diseases as high risk, constraints - structural and psychological barriers, calculation - engagement in information seeking, collective responsibility - willingness to protect others), health literacy in a pandemic (CHL-P), and additional determinants. Results All 5Cs were associated with the vaccination status ‘fully vaccinated’, except for complacency. Regarding CHL-P, we found that students who felt that the current scientific knowledge about COVID-19 in terms of the policy decisions on pandemic measures was very complex had a higher odds for being vaccinated (OR = 3.02;95% CI: 2.26-4.04). Regarding additional determinants, the analysis revealed that students who had been previously infected had in all regressions a lower odds for being vaccinated compared to students with no previous infection. Conclusions Due to the strong association of the attitudes towards vaccination and vaccination behaviour among university students, we recommend that the different components of the 5Cs should be considered in future COVID-19 vaccination campaigns in the university context. Key messages Attitudes towards vaccinations impact on vaccination behaviour among university students. Perceiving the current scientific knowledge on COVID-19 as very complex increased the odds for vaccination.

Anxiety among students during the pandemic - Results from the C-19 German Student Well-being Study : Eileen Heumann

Background Anxiety is widespread among university students. The COVID-19 pandemic af-fected students’ mental health negatively. Given the long duration of the pandemic monitoring mental health remains important. This study aims to determine to which extent anxiety is preva-lent among students (1), what factors are associated with it (2) and which student groups are mostly affected (3). Methods The cross-sectional COVID-19 German Student Well-being Study (C19 GSWS) sur-veyed mental health and well-being of students at five universities in Germany from 27.10.-14.11.21. Anxiety was assessed using the GAD-2. Associations between anxiety and sociodem-ographic, socioeconomic/social support factors as well as health- and COVID-19-related factors were determined using multiple binary logistic regression models. Results The mean age of students was 24.1 years (SD = 4.9), 67% were women and 31% men. The prevalence of anxiety was 32% and diverse gender (OR = 3.98, 95% CI: 1.71-9.23), a com-plicated relationship status (OR = 1.66, 95% CI: 1.06-2.60), the lack of a confidant (OR = 2.50, 95% CI: 1.80-3.46), and financial difficulties (e.g., being able to cover monthly expenses;OR = 1.76, 95% CI: 1.36-2.29) were associated with anxiety. Participants who were worried about (re)infection with COVID-19 had a 1.28-times higher chance (OR, 95% CI: 1.03-1.59) for anxie-ty. Students who were (rather) not worried that a relative would become severely ill with COVID-19 had a lower chance to experience anxiety (OR = 0.72, 95% CI: 0.53-0.98) as well as those who were confident receiving medical care in case of an infection with COVID-19 (OR = 0.80, 95% CI: 0.65-0.98). Conclusions Concepts for prevention and counselling in terms of mental health problems in students should be developed considering specific stressors due to the pandemic. Key messages • This study shows that anxiety is widespread among university students and associated with a variety of stressors. • The findings can help to develop specific concepts for prevention and counselling.

Minimum irradiance required to inhibit microbial growth to prevent ventilatorassociated pneumonia by an endotracheal tube equipped with blue LEDs

Artificial respiration is saving lives especially in the COVID-19 pandemic, but it also carries the risk to cause ventilator-Associated pneumonia (VAP). VAP is one of the most common and severe nosocomial infections, often leading to death and adding a major economic burden to the healthcare system. To prevent a proliferation of microbial pathogens that cause VAP, an endotracheal tube (ETT) equipped with blue LEDs (LED-ETT) was developed. This blue wavelength exhibits antimicrobial properties but may also harm human tracheal cells at higher irradiances. Therefore, the aim of this study was to find the minimal required irradiance for microbial reduction of 1 log level in 24 h by applying LED-ETTs. A LED-ETT with 48 blue LEDs (450 nm) was fixed in a glass tube, which served as a trachea model. The investigation was carried out with irradiations of 4.2, 6.6 and 13.4 mW/cm² at 37 °C for 24 h. The experiments were performed with Acinetobacter kookii as a surrogate of Acinetobacter baumannii, which is classified as critical by the WHO. Samples of A. kookii suspensions were taken every 4 h during irradiation from the trachea model. Bacteria concentrations were quantified by determining colony forming units (CFU)/ml. A homogeneous irradiance of only 4.2 mW/cm² generated by the blue LEDs, at a LED forward current of 3.125 mA, is sufficient to achieve a 1 log reduction of A. kookii within 24 h. The total irradiation dose within this period was 360 J/cm2. Human cells survive this dose without cellular damage. Previous studies revealed that the pathogen A. baumannii is even more sensitive to blue light than A. kookii. Therefore, blue LED-ETTs are expected to reduce A. baumannii without harming human tracheal cells. © 2021 by Walter de Gruyter Berlin/Boston.

Minimum irradiance required to inhibit microbial growth to prevent ventilator-associated pneumonia by an endotracheal tube equipped with blue LEDs

Introduction Artificial respiration is saving lives especially in the COVID-19 pandemic, but it also contains the risk to cause ventilatorassociated pneumonia (VAP). VAP is one of the most common and severe nosocomial infections often leading to death and adding a major economic burden to the healthcare system. To prevent a proliferation of microbial pathogens that cause VAPs, an endotracheal tube equipped with blue LEDs (LED-ETT) was developed. This blue wavelength exhibits antimicrobial properties but may also harm human tracheal cells. Therefore, the aim of this paper was to find the minimal required irradiance for microbial reduction of 1 log level in 24 h by applying LED-ETTs. Methods A LED-ETT with 48 blue LEDs (450 nm) was fixated in a glass tube, which functions as a trachea model. The investigation was carried out with irradiations of 4.2, 6.6 and 13.4 mW/cm2 at 37 °C for 24 h. The experiments were performed with Acinetobacter kookii as a surrogate of Acinetobacter baumannii, which is classified as critical by the WHO. Samples of A. kookii suspensions were taken every 4h during irradiation from the trachea model. Bacteria were quantified by determining colony forming units cfu/ml. Results A homogeneous irradiance of only 4.2 mW/cm2 generated by the blue LEDs, at a current of 25 mA, is sufficient to achieve a 1 log reduction of A. kookii within 24 h. The total irradiation dose within this period was 360 J/cm2. Conclusion 360 J/cm2is a dose that human cells survive without cellular damage. Previous studies revealed that the pathogen A. baumannii is even more sensitive to blue light. Therefore, blue LED-ETTs are expected to reduce A. baumannii without harming human tracheal cells.

How a healthcare system leveraged ICU patient load balancing to manage the COVID-19 pandemic surge

INTRODUCTION: Beth Israel Lahey Health (BILH) formed in March 2019 incorporating 2 legacy systems and 3 independent hospitals. In March 2020, during the surge of COVID-19 in MA, BILH formed a Critical Care Group (CCG) to assist patient load balancing and equipment leveling across all 12 hospitals. METHODS: CCG members included ICU leaders from 3 tertiary hospitals and the BILH Chief Medical Officer. The team huddled twice daily, and developed ICU bed and ventilator surge plans, and pathways for balancing across the network. Requests for transfers from referring hospitals were redirected to BILH hospitals with capacity. CCG made strategic decisions to transfer patients within BILH so that no single hospital became overwhelmed. CCG invited 3 Safety Net Hospitals (SNHs) to the huddles;each SNH was in a COVID ?hotspot,? and the CCG accommodated their transfers. RESULTS: The CCG enabled BILH to flex to 238% of the system's baseline 224 licensed ICU beds. At peak, BILH's tertiary hospital ICUs had an occupancy at 157% of baseline, with 73% of ICU patients on ventilators. From 3/1-6/30, one of the tertiary BILH hospitals accepted 81 SNH ICU transfers;support for SNHs was critical for the overall State response to the surge. Unexpected benefits of the CCG included providing a platform for communication and knowledge sharing;discussions included standardization for tracheostomy procedures, management of ECMO resources, avoidance of pitfalls using anesthesia machines as ventilators, and protocols for proning. As a new system, these strengthened relationships between legacy hospital systems. In addition, MA developed a similar CCG, with the aim of the state's largest hospitals having awareness of how other hospitals' ICUs were managing the surge. CONCLUSIONS: CCG was essential to the BILH system as it facilitated a real-time adaptive response to the surge. Key elements included: 1) Creating a team of senior Critical Care leadership, all of whom were closely in tune with their respective ICU's current status and needs 2) CCG relied on a dashboard that provided daily data on ICU capacity at each hospital, allowing for real-time decision-making 3) Early planning prior to the influx of patients;the CCG formed when the COVID critical care census system-wide was 5, relative to a census of 190 at peak surge.