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Introduction Adherence to digital proximity tracing apps and preventive measures leading up to and following widespread SARS-CoV-2 vaccine rollout remains unclear. Our study aims to evaluate the relative effect of digital proximity tracing app use, SARS-CoV-2 vaccine uptake and adherence to additional preventive measures in a localized context of the pandemic. Methods We report findings from two population-based longitudinal cohorts in Switzerland, the Corona Immunitas Digital Follow-up eCohort (CI-DFU) and the COVID-19 Social Monitor (CSM) studies in 2021. Failure time analyses were conducted for each study cohort, stratified by age group. Cox proportional hazards regression models with time-varying covariates were used to estimate adjusted hazard ratios (aHR). The analyses assessed vaccine uptake and SwissCovid app uninstalling outcomes, with the outcomes interchanging as the exposures in two separate substudies. Results We observed a dichotomy of individuals who did not use the app during the study period and did not get vaccinated, and who used the SwissCovid app during the study period and got vaccinated during the study period. We found an increased uptake of the vaccine associated with SwissCovid app use (aHR, 1.51; 95% CI: 1.40–1.62 [CI-DFU]; aHR, 1.79; 95% CI: 1.62–1.99 [CSM]) or adherence to preventive measures (aHR, 1.44; 95% CI: 1.28–1.62 [CI-DFU]; aHR, 1.82; 95% CI: 1.52–2.18 [CSM]). Decreased SwissCovid uninstallation risk was observed for participants who received their first vaccine dose throughout the study period (aHR, 0.55; 95% CI: 0.38–0.81 [CI-DFU]; aHR, 0.45; 95% CI: 0.27–0.78 [CSM]). Conclusion In evolving pandemic contexts, these findings can assist public health authorities in designing evidence-based communication strategies to enable adoption of preventive measures and novel health technologies across all population groups.

PURPOSE Excessive duration of antibiotic treatment is a major factor for inappropriate antibiotic consumption. Although in some instances shorter antibiotic courses are as efficient as longer ones, no specific recommendations as to the duration of antimicrobial treatment for bloodstream infections currently exist. In the present study, we investigated the effect of antibiotic treatment duration on in-hospital mortality using retrospective data from two cohorts that included patients with bacteremia at two Swiss tertiary Intensive Care Units (ICUs). MATERIALS AND METHODS Overall 8227 consecutive patients requiring ICU admission were screened for bacteremia between 01/2012-12/2013 in Lausanne and between 07/2016-05/2017 in Bern. Patients with an infection known to require prolonged treatment or having single positive blood culture with common contaminant pathogens were excluded. The primary outcome of interest was the time from start of antimicrobial treatment to in-hospital death or hospital discharge, whichever comes first. The predictor of interest was adequate antimicrobial treatment duration, further divided into shorter (≤10 days) and longer (>10 days) durations. A time-dependent Cox model and a cloning approach were used to address immortality bias. The secondary outcomes were the median duration of antimicrobial treatment for patients with bacteremia overall and stratified by underlying infectious syndrome and pathogens in the case of secondary bacteremia. RESULTS Out of the 707 patients with positive blood cultures, 382 were included into the primary analysis. Median duration of antibiotic therapy was 14 days (IQR, 7-20). Most bacteremia (84%) were monomicrobial; 18% of all episodes were primary bacteremia. Respiratory (28%), intra-abdominal (23%) and catheter infections (17%) were the most common sources of secondary bacteremia. Using methods to mitigate the risk of confounding associated with antibiotic treatment durations, shorter versus longer treatment groups showed no differences in in-hospital survival (time-dependent Cox-model: HR 1.5, 95% CI (0.8, 2.7), p = 0.20; Cloning approach: HR 1.0, 95% CI (0.7,1.5) p = 0.83). Sensitivity analyses showed that the interpretation did not change when using a 7 days cut-off. CONCLUSIONS In this restrospective study, we found no evidence for a survival benefit of longer (>10 days) versus shorter treatment course in ICU patients with bacteremia. TRIAL REGISTRATION The study was retrospectively registered on clinicatrials.gov (NCT05236283), 11 February 2022. The respective cantonal ethics commission (KEK Bern # 2021-02302) has approved the study.

Purpose Intensive care patients have increased risk of death and their care is expensive. We investigated whether risk-adjusted mortality and resources used to achieve survivors change over time and if their variation is associated with variables related to intensive care unit (ICU) organization and structure. Methods Data of 207,131 patients treated in 2008–2017 in 21 ICUs in Finland, Estonia and Switzerland were extracted from a benchmarking database. Resource use was measured using ICU length of stay, daily Therapeutic Intervention Scoring System Scores (TISS) and purchasing power parity-adjusted direct costs (2015–2017; 17 ICUs). The ratio of observed to severity-adjusted expected resource use (standardized resource use ratio; SRUR) was calculated. The number of expected survivors and the ratio of observed to expected mortality (standardized mortality ratio; SMR) was based on a mortality prediction model covering 2015–2017. Fourteen a priori variables reflecting structure and organization were used as explanatory variables for SRURs in multivariable models. Results SMR decreased over time, whereas SRUR remained unchanged, except for decreased TISS-based SRUR. Direct costs of one ICU day, TISS score and ICU admission varied between ICUs 2.5–5-fold. Differences between individual ICUs in both SRUR and SMR were up to > 3-fold, and their evolution was highly variable, without clear association between SRUR and SMR. High patient turnover was consistently associated with low SRUR but not with SMR. Conclusion The wide and independent variation in both SMR and SRUR suggests that they should be used together to compare the performance of different ICUs or an individual ICU over time. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-021-06546-4.

BACKGROUND Digital proximity tracing apps have been deployed in multiple countries to assist with SARS-CoV-2 pandemic mitigation efforts. However, it is unclear how their performance and effectiveness were affected by changing pandemic contexts and new viral variants of concern. OBJECTIVE The aim of this study is to bridge these knowledge gaps through a country-wide digital proximity tracing app effectiveness assessment as guided by the WHO/ECDC framework. Specifically, we performed a descriptive analysis of the digital proximity tracing app in Switzerland for three different time periods where different SARS-CoV-2 variants of concern (i.e., Alpha, Delta, and Omicron, respectively) were most prevalent. METHODS In our study, we refer to the indicator framework for the evaluation of public health effectiveness of digital proximity tracing apps of the World Health Organization / European Center for Disease Control (WHO/ECDC). We applied this framework to compare performance and effectiveness indicators of the SwissCovid app in Switzerland across three time periods that were characterized by the dominance of the Alpha, Delta, and Omicron variants of concern. RESULTS Average daily registered SARS-CoV-2 case rates during our assessment period from January 25, 2021 to March 19, 2022 were 20 (Alpha), 54 (Delta), and 350 (Omicron) per 100’000 inhabitants. The percentages of overall entered authentication codes from positive tests in the SwissCovid app were 10%, 4%, and 5% during the Alpha, Delta, and Omicron variant phases, respectively. Following receipt of an exposure notification from the SwissCovid app, 58% (Alpha), 44% (Delta), and 73% (Omicron) of app users sought testing or performed self-tests. Test positivity among these exposure-notified individuals was 19% in the Alpha (compared with 6% in the general population), 29% (11%) in the Delta, and 41% (43%) in the Omicron variant phases. In addition, 34% (Alpha), 19% (Delta), and 30% (Omicron) of exposure-notified app users reported receiving mandatory quarantine orders by manual contact tracing or through a recommendation by a health care professional. CONCLUSIONS In constantly evolving pandemic contexts, the effectiveness of digital proximity tracing apps in contributing to mitigating pandemic spread should be reviewed regularly and adapted based on changing requirements. The WHO/ECDC framework allowed us to assess relevant domains of digital proximity tracing in a holistic and systematic approach. Future implementation of digital proximity tracing apps should place more emphasis on the social, psychological and organizational aspects to reduce bottlenecks and facilitate their use in pandemic situations.

BACKGROUND/OBJECTIVES To assess the course and prediction of basic activities of daily living (ADL) function in patients after transcatheter aortic valve implantation (TAVI). DESIGN This was a prospective cohort study. SETTING The setting was a single academic center in Switzerland. PARTICIPANTS Participants included individuals aged ≥70 years (n = 330) undergoing TAVI. MEASUREMENTS A frailty index (based on geriatric assessment) and cardiac risk scores (EuroSCORE, Society of Thoracic Surgeons [STS] score) were determined in patients before TAVI. Basic ADL function was measured with patient or proxy interviews at baseline and 1-year follow up. We used logistic regression models to investigate the association between baseline factors and functional decline. RESULTS At 1-year follow up, 229 (69.4%) of the 330 patients had stable or improved basic ADL function, 49 (14.8%) experienced a decline in basic ADL function, and 52 (15.8%) died. The frailty index, but not cardiac risk scores, significantly predicted decline in basic ADL function. Among the 34 surviving very frail patients, 12 (35.3%) experienced a functional status decline, and the remaining 22 (64.7%) had stable or improved functional status at 1-year follow up. CONCLUSION This study confirms that a frailty index, and not cardiac risk scores, identifies patients at an increased risk of functional status decline after TAVI. Identifying patients with a high frailty index before TAVI is clinically relevant as these patients might benefit from targeted geriatric management and rehabilitation after TAVI. However, based on current data, it is not justified to use information on frailty status as the criterion for identifying patients in whom TAVI might be futile. Although the probability of poor outcome is high, very frail patients also have a high probability of favorable long-term functional outcome.

Objectives Interventions to increase fruit and vegetable intake among community-dwelling older people have shown mixed effects. We investigated whether an intervention based on an initial multidimensional health risk assessment and subsequent physician-lead nutrition counselling has favourable effects on dietary intake among community-dwelling older people. Design Randomised controlled trial comparing the intervention versus usual care. Setting and participants Non-disabled persons aged 65 years or older at an ambulatory geriatric clinic in Bucharest, Romania, allocated to intervention (n=100) and control (n=100) groups. Intervention Participants received a computer-generated health profile report based on answers to a health risk assessment questionnaire, followed by monthly individual counselling sessions with a geriatrician on topics related to health promotion and disease prevention, with a special focus on adequate fruit and vegetable consumption. Measurements Fruit and vegetable intake at baseline and at 6-month follow-up. Results At baseline, fruit and vegetable intake was below the recommended five portions per day in most study participants (85% in the intervention group, and 86% among controls, respectively). At six months, intake increased in the intervention group from a median of 3.8 to 4.6 portions per day, and decreased in the control group due to a seasonal effect from a median of 3.8 to 3.1 portions per day. At six months, fruit and vegetable consumption was significantly higher among persons in the intervention group as compared to controls (median difference 1.4 portions per day, 95% confidence interval 1.1–1.7, p Conclusion Personalised food-based dietary guidance, delivered as part of multidimensional preventive health counselling during geriatric clinic visits, results in relevant improvement of fruit and vegetable intake in community-dwelling older adults.

Publisher Copyright: © 2022 Purpose: The resource use of cardiac surgery and neurosurgery patients likely differ from other ICU patients. We evaluated the relevance of these patient groups on overall ICU resource use. Methods: Secondary analysis of 69,862 patients in 17 ICUs in Finland, Estonia, and Switzerland in 2015–2017. Direct costs of care were allocated to patients using daily Therapeutic Intervention Scoring System (TISS) scores and ICU length of stay (LOS). The ratios of observed to severity-adjusted expected resource use (standardized resource use ratios; SRURs), direct costs and outcomes were assessed before and after excluding cardiac surgery or cardiac and neurosurgery. Results: Cardiac surgery and neurosurgery, performed only in university hospitals, represented 22% of all ICU admissions and 15–19% of direct costs. Cardiac surgery and neurosurgery were excluded with no consistent effect on SRURs in the whole cohort, regardless of cost separation method. Excluding cardiac surgery or cardiac surgery plus neurosurgery had highly variable effects on SRURs of individual university ICUs, whereas the non-university ICU SRURs decreased. Conclusions: Cardiac and neurosurgery have major effects on the cost structure of multidisciplinary ICUs. Extending SRUR analysis to patient subpopulations facilitates comparison of resource use between ICUs and may help to optimize resource allocation.

OBJECTIVE Prognostic models are key for benchmarking intensive care units (ICUs). They require up-to-date predictors and should report transportability properties for reliable predictions. We developed and validated an in-hospital mortality risk prediction model to facilitate benchmarking, quality assurance, and health economics evaluation. STUDY DESIGN AND SETTING We retrieved data from the database of an international (Finland, Estonia, Switzerland) multicenter ICU cohort study from 2015-2017. We used a hierarchical logistic regression model that included age, a modified Simplified Acute Physiology Score-II, admission type, premorbid functional status, and diagnosis as grouping variable. We used pooled and meta-analytic cross-validation approaches to assess temporal and geographical transportability. RESULTS We included 61,224 patients treated in the ICU (hospital mortality 10.6%). The developed prediction model had an area under the receiver operating characteristic curve 0.886, 95% confidence interval (CI) 0.882-0.890; a calibration slope 1.01, 95% CI (0.99-1.03); a mean calibration -0.004, 95% CI (-0.035-0.027). While the model showed very good internal validity and geographic discrimination transportability, we found substantial heterogeneity of performance measures between ICUs (I-squared: 53.4% to 84.7%). CONCLUSION A novel framework evaluating the performance of our prediction model provided key information to judge the validity of our model and its adaptation for future use. WHAT IS NEW?: : Key findings; Our mortality prediction model-which combined established clinically relevant predictors with premorbid functional status and diagnoses as modeling variables-showed very good internal validity, geographic discrimination and temporal transportability, with a substantial heterogeneity of performance measures between ICUs. What does this add to what is known? Premorbid functional status and diagnosis are known predictors of ICU-relevant study outcomes, but are not regularly implemented in established scoring systems. The inclusion of this information showed increased predictive model performance compared to predictions from established risk scoring systems, while showing good internal validation and transportability properties. What is the implication and what should change now? To the best of our knowledge, this is one of the first development and validation studies to investigate geographical and temporal transportability properties of an ICU mortality prediction model. Transportability properties are key in the reliable monitoring and benchmarking of ICUs and for their planning. They provide an important piece of information about the model validity in other study populations and settings, and should be quantified in future validation studies of ICU prediction models.

Background The modifications to the standard intensive care unit (ICU) organization that had to be urgently implemented worldwide to overcome the surge of ICU admissions due to patients with a severe coronavirus disease 2019 (COVID-19) have resulted in increased workload and patients-to-nurse ratio. The aim of this study was to investigate whether level of critical care staffing could be associated with an increased risk of ICU mortality (primary endpoint), length of stay, mechanical ventilation and the evolution of disease (secondary study endpoints) in critically ill patients with COVID-19. Methods Retrospective multicenter analysis of the international Risk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry that prospectively enrolls patients developing critical illness due to COVID-19 in several countries worldwide. The analysis was limited to the period between March 1st, 2020 and May 31st, 2020, to ICUs in Switzerland that have collected additional data on nurse and physician staffing. Hierarchical regression models were used to investigate crude and adjusted effects of critical care staffing ratio on study endpoints. We adjusted for diseases severity and weekly caseload. Results Among the 38 Swiss participating ICUs, 17 recorded critical care staffing information. The study population included 437 patients and 2342 daily assessments of patient-to-nurse/physician ratio. Median of daily patient-to-nurse ratio started at 1.0 ([IQR] 0.5–1.5; calendar week 9) and peaked at 2.4 (IQR 0.4-2.0; calendar week 16), while the median of daily patient-to-physician ratio started at 4.0 (IQR 2.1-5.0; calendar week 9) and peaked at 6.8 (IQR 6.3–7.3; calendar week 19). Neither the patient-to-nurse ratio [adjusted Odds Ratio (OR) 1.28, 95% confidence interval (CI) 0.85–1.94; doubling of ratio] nor the patient-to-physician ratio [adjusted OR 1.08, 95% CI 0.87–1.32; doubling of ratio] was associated with ICU mortality. We found no association of critical care staffing on the investigated secondary study endpoints in adjusted models. COnclusion The Swiss health care system successfully overcame the first wave of the COVID-19 pandemic with regards to the unprecedented demand for ICU treatments. The reduced availability of critical care staffing resources per critically ill patient in Swiss ICUs did not translate in an overall increased risk of mortality.

BACKGROUND Mitigation of the spread of infection relies on targeted approaches aimed at preventing nonhousehold interactions. Contact tracing in the form of digital proximity tracing apps has been widely adopted in multiple countries due to its perceived added benefits of tracing speed and breadth in comparison to traditional manual contact tracing. Assessments of user responses to exposure notifications through a guided approach can provide insights into the effect of digital proximity tracing app use on managing the spread of SARS-CoV-2. OBJECTIVE The aim of this study was to demonstrate the use of Venn diagrams to investigate the contributions of digital proximity tracing app exposure notifications and subsequent mitigative actions in curbing the spread of SARS-CoV-2 in Switzerland. METHODS We assessed data from 4 survey waves (December 2020 to March 2021) from a nationwide panel study (COVID-19 Social Monitor) of Swiss residents who were (1) nonusers of the SwissCovid app, (2) users of the SwissCovid app, or (3) users of the SwissCovid app who received exposure notifications. A Venn diagram approach was applied to describe the overlap or nonoverlap of these subpopulations and to assess digital proximity tracing app use and its associated key performance indicators, including actions taken to prevent SARS-CoV-2 transmission. RESULTS We included 12,525 assessments from 2403 participants, of whom 50.9% (1222/2403) reported not using the SwissCovid digital proximity tracing app, 49.1% (1181/2403) reported using the SwissCovid digital proximity tracing app and 2.5% (29/1181) of the digital proximity tracing app users reported having received an exposure notification. Most digital proximity tracing app users (75.9%, 22/29) revealed taking at least one recommended action after receiving an exposure notification, such as seeking SARS-CoV-2 testing (17/29, 58.6%) or calling a federal information hotline (7/29, 24.1%). An assessment of key indicators of mitigative actions through a Venn diagram approach reveals that 30% of digital proximity tracing app users (95% CI 11.9%-54.3%) also tested positive for SARS-CoV-2 after having received exposure notifications, which is more than 3 times that of digital proximity tracing app users who did not receive exposure notifications (8%, 95% CI 5%-11.9%). CONCLUSIONS Responses in the form of mitigative actions taken by 3 out of 4 individuals who received exposure notifications reveal a possible contribution of digital proximity tracing apps in mitigating the spread of SARS-CoV-2. The application of a Venn diagram approach demonstrates its value as a foundation for researchers and health authorities to assess population-level digital proximity tracing app effectiveness by providing an intuitive approach for calculating key performance indicators.

Key Points Question What is the possible contribution of digital contact tracing (DCT) apps to the interruption of SARS-CoV-2 transmission chains? Findings This comparative effectiveness study found that the number of DCT app users receiving a quarantine recommendation corresponded to the equivalent of as many as 5% of all mandatory quarantined contacts identified by manual contact tracing in the canton of Zurich, Switzerland. Furthermore, approximately 1 in 11 notification triggers led to SARS-CoV-2 testing of an exposed proximity contact who subsequently had positive test results. Meaning These findings suggest that DCT apps can make a relevant contribution to transmission prevention, with the potential to scale as more persons use the apps., Importance Digital contact tracing (DCT) apps have been released in several countries to help interrupt SARS-CoV-2 transmission chains. However, the effect of DCT on pandemic mitigation remains to be demonstrated. Objective To estimate key populations and performance indicators along the exposure notification cascade of the SwissCovid DCT app in a clearly defined regional and temporal context. Design, Setting, and Participants This comparative effectiveness study was based on a simulation informed by measured data from issued quarantine recommendations and positive SARS-CoV-2 test results after DCT exposure notifications in the canton of Zurich. A stochastic model was developed to re-create the DCT notification cascade for Zurich. Population sizes at each cascade step were estimated using triangulation based on publicly available administrative and observational research data for the study duration from September 1 to October 31, 2020. The resultant estimates were checked for internal consistency and consistency with upstream or downstream estimates in the cascade. Stochastic sampling from data-informed parameter distributions was performed to explore the robustness of results. Subsequently, key performance indicators were evaluated to assess the potential contribution of DCT compared with manual contact tracing. Main Outcomes and Measures Receiving a voluntary quarantine recommendation and/or a positive SARS-CoV-2 test result after exposure notification. Results In September 2020, 537 app users received a positive SARS-CoV-2 test result in Zurich, 324 of whom received and entered an upload authorization code. This code triggered an app notification for an estimated 1374 (95% simulation interval [SI], 932-2586) proximity contacts and led to 722 information hotline calls, with an estimated 170 callers (95% SI, 154-186) receiving a quarantine recommendation. An estimated 939 (95% SI, 720-1127) notified app users underwent testing for SARS-CoV-2, of whom 30 (95% SI, 23-36) had positive results after an app notification. Key indicator evaluations revealed that the DCT app triggered quarantine recommendations for the equivalent of 5% of all exposed contacts placed in quarantine by manual contact tracing. For every 10.9 (95% SI, 7.6-15.6) upload authorization codes entered in the app, 1 contact had positive test results for SARS-CoV-2 after app notification. Longitudinal indicator analyses demonstrated bottlenecks in the notification cascade, because capacity limits were reached owing to an increased incidence of SARS-CoV-2 infection in October 2020. Conclusions and Relevance In this simulation study of the notification cascade of the SwissCovid DCT app, receipt of exposure notifications was associated with quarantine recommendations and identification of SARS-CoV-2–positive cases. These findings in notified proximity contacts reflect important intermediary steps toward transmission prevention., This data-informed simulation study estimates key populations and performance indicators along the exposure notification cascade of the SwissCovid digital contact tracing app in September and October 2020 in Zurich, Switzerland.

Background: Disability progression independent of relapses (PIRA) has been described as a frequent phenomenon in relapsing-remitting multiple sclerosis (RRMS). Objective: To compare the occurrence of disability progression in relapse-free RRMS patients on interferon-beta/glatiramer acetate (IFN/GA) versus fingolimod. Methods: This study is based on data from the Swiss association for joint tasks of health insurers. Time to relapse and 12-month confirmed disability progression were compared between treatment groups using multivariable Cox regression analysis with confounder adjustment. Inverse-probability weighting was applied to correct for the bias that patients on fingolimod have a higher chance to remain relapse-free than patients on IFN/GA. Results: We included 1640 patients (64% IFN/GA, 36% fingolimod, median total follow-up time = 4–5 years). Disease-modifying treatment (DMT) groups were well balanced with regard to potential confounders. Disability progression was observed in 155 patients (8.8%) on IFN/GA and 51 (7.6%) on fingolimod, of which 44 and 23 were relapse-free during the initial DMT, respectively. Adjusted standard regression analysis on all patients indicated that those on fingolimod experience less frequently disability progression compared with IFN/GA (hazard ratio = 0.53 (95% confidence interval = 0.37–0.76)). After bias correction, this was also true for patients without relapses (hazard ratio=0.56 (95% confidence interval = 0.32–0.98). Conclusion: Our analysis indicates that fingolimod is superior to IFN/GA in preventing disability progression in both relapsing and relapse-free, young, newly diagnosed RRMS patients.

ImportanceDigital proximity tracing (DPT) apps were released in several countries to help interrupt SARS-CoV-2 transmission chains in the population. However, the impact of DPT on pandemic mitigation still remains to be demonstrated.ObjectiveTo estimate key populations and performance indicators along the DPT app notification cascade in a clearly defined regional (Canton of Zurich, using all of Switzerland as a comparison) and temporal context (September/October 2020).DesignPublicly available administrative and research data, including key DPT performance indicators, SARS-CoV-2 testing statistics, infoline call statistics, and observational study data, were compiled. A model of the DPT notification cascade was developed and key performance indicators for DPT processes were defined. Subpopulation sizes at each cascade step were estimated using data triangulation. Resulting estimates were systematically checked for internal consistency and consistency with other up- or downstream estimates in the cascade. Stochastic simulations were performed to explore robustness of results.ResultsFor the Canton of Zurich, we estimate that 537 app users received a positive SARS-CoV-2 test in September 2020, of whom 324 received and entered a CovidCode. This triggered an app notification for an estimated 1374 proximity contacts and led to 722 infoline calls. In total, 170 callers received a quarantine recommendation, and 30 app users tested positive for SARS-CoV-2 after an app notification, reflecting a performance above the national level.Based on this quantification, key performance indicators were evaluated. For September 2020, these analyses suggest that SwissCovid triggered quarantine recommendations in the equivalent of 5% of all exposed contacts placed in quarantine by manual contact tracing. Per 11 CovidCodes entered in the app, we estimate that almost 1 contact tested positive for SARS-CoV-2 upon app notification.However, longitudinal indicator analyses demonstrate bottlenecks in the notification cascade, as capacity limits were reached due to large increases in SARS-CoV-2 incidence in October 2020.ConclusionAlthough requiring confirmation, our estimations on the number of notified proximity contacts receiving quarantine recommendations or testing positive after notification suggest relevant contributions to mitigating the pandemic. Increasing SwissCovid app uptake and improving notification cascade performance may further enhance its impact.Key pointsQuestionWhat is the real-life impact of Digital proximity tracing (DPT) apps on interrupting SARS-CoV-2 transmission chains?FindingsThis data-informed simulation study found that, in the canton of Zurich, the number of app notified persons receiving a quarantine recommendation corresponds to the equivalent of up to 5% of all mandatory quarantined contacts identified by manual contact tracing. Furthermore, about 1 in 11 notification triggers led to SARS-CoV-2 testing of an exposed proximity contact who was consecutively tested positive.MeaningDPT apps exert a measurable impact that will further scale as more persons use the apps.

Bioprocess development and optimization are still cost- and time-intensive due to the enormous number of experiments involved. In this study, the recently introduced model-assisted Design of Experiments (mDoE) concept (Möller et al. in Bioproc Biosyst Eng 42(5):867, 10.1007/s00449-019-02089-7, 2019) was extended and implemented into a software (“mDoE-toolbox”) to significantly reduce the number of required cultivations. The application of the toolbox is exemplary shown in two case studies with Saccharomyces cerevisiae. In the first case study, a fed-batch process was optimized with respect to the pH value and linearly rising feeding rates of glucose and nitrogen source. Using the mDoE-toolbox, the biomass concentration was increased by 30% compared to previously performed experiments. The second case study was the whole-cell biocatalysis of ethyl acetoacetate (EAA) to (S)-ethyl-3-hydroxybutyrate (E3HB), for which the feeding rates of glucose, nitrogen source, and EAA were optimized. An increase of 80% compared to a previously performed experiment with similar initial conditions was achieved for the E3HB concentration.

New innovative Digital Twins can represent complex bioprocesses, including the biological, physico-chemical, and chemical reaction kinetics, as well as the mechanical and physical characteristics of the reactors and the involved peripherals. Digital Twins are an ideal tool for the rapid and cost-effective development, realisation and optimisation of control and automation strategies. They may be utilised for the development and implementation of conventional controllers (e.g. temperature, dissolved oxygen, etc.), as well as for advanced control strategies (e.g. control of substrate or metabolite concentrations, multivariable controls), and the development of complete bioprocess control. This chapter describes the requirements Digital Twins must fulfil to be used for bioprocess control strategy development, and implementation and gives an overview of research projects where Digital Twins or "early-stage" Digital Twins were used in this context. Furthermore, applications of Digital Twins for the academic education of future control and bioprocess engineers as well as for the training of future bioreactor operators will be described. Finally, a case study is presented, in which an "early-stage" Digital Twin was applied for the development of control strategies of the fed-batch cultivation of Saccharomyces cerevisiae. Development, realisation and optimisation of control strategies utilising Digital Twins.

A future-oriented approach is the application of Digital Twins for process development, optimization and finally during manufacturing. Digital Twins are detailed virtual representations of bioprocesses with predictive capabilities. In biotechnology, Digital Twins can be used to monitor processes and to provide data for process control and optimization. Central and crucial components of Digital Twins are mathematical process models, which are capable to describe and predict cultivations with high fidelity. Detailed mechanistic models in particular are suitable for both use in Digital Twins and for the development of process control strategies.In this chapter the requirements that process models must fulfil in order to be used for process optimization and finally in Digital Twins will be described. Different types of models, including mechanistic as well as compartmentalized models, are outlined and their application in Digital Twins and for process optimization is explained. Finally, a structured, compartmentalized process model, which was specifically designed for process optimization and has already been used in Digital Twins, is highlighted.

BACKGROUND Digital proximity tracing apps have been released to mitigate the transmission of SARS-CoV-2, the virus known to cause COVID-19. However, it remains unclear how the acceptance and uptake of these apps can be improved. OBJECTIVE This study aimed to investigate the coverage of the SwissCovid app and the reasons for its nonuse in Switzerland during a period of increasing incidence of COVID-19 cases. METHODS We collected data between September 28 and October 8, 2020, via a nationwide online panel survey (COVID-19 Social Monitor, N=1511). We examined sociodemographic and behavioral factors associated with app use by using multivariable logistic regression, whereas reasons for app nonuse were analyzed descriptively. RESULTS Overall, 46.5% (703/1511) of the survey participants reported they used the SwissCovid app, which was an increase from 43.9% (662/1508) reported in the previous study wave conducted in July 2020. A higher monthly household income (ie, income >CHF 10,000 or >US $11,000 vs income ≤CHF 6000 or CONCLUSIONS Eliminating technical hurdles and communicating the benefits of digital proximity tracing apps are crucial to promote further uptake and adherence of such apps and, ultimately, enhance their effectiveness to aid pandemic mitigation strategies.

Background The COVID-19 pandemic challenges societies in unknown ways, and individuals experience a substantial change in their daily lives and activities. Our study aims to describe these changes using population-based self-reported data about social and health behavior in a random sample of the Swiss population during the COVID-19 pandemic. The aim of the present article is two-fold: First, we want to describe the study methodology. Second, we want to report participant characteristics and study findings of the first survey wave to provide some baseline results for our study. Methods Our study design is a longitudinal online panel of a random sample of the Swiss population. We measure outcome indicators covering general well-being, physical and mental health, social support, healthcare use and working state over multiple survey waves. Results From 8,174 contacted individuals, 2,026 individuals participated in the first survey wave which corresponds to a response rate of 24.8%. Most survey participants reported a good to very good general life satisfaction (93.3%). 41.4% of the participants reported a worsened quality of life compared to before the COVID-19 emergency and 9.8% feelings of loneliness. Discussion The COVID-19 Social Monitor is a population-based online survey which informs the public, health authorities, and the scientific community about relevant aspects and potential changes in social and health behavior during the COVID-19 emergency and beyond. Future research will follow up on the described study population focusing on COVID-19 relevant topics such as subgroup differences in the impact of the pandemic on well-being and quality of life or different dynamics of perceived psychological distress.

Background Digital proximity tracing (DPT) apps have been released to mitigate SARS-CoV-2 transmission. But it remains unclear how their acceptance and uptake can be improved. The aim of this study was to investigate SwissCovid app coverage and reasons for not using the app in Switzerland during a time of increasing SARS-CoV-2 incidence. Methods By use of data collected between 28.09.2020 to 08.10.2020 for a nationwide online panel survey (Covid-19 Social Monitor, n=1’511 participants), socio-demographic and behavioral factors associated with app usage were examined using multivariable logistic regression. Reasons for app non-use were analyzed descriptively. Results Overall, 46.5% of participants reported using the SwissCovid app (up from 43.9% in a study wave conducted in July 2020). A higher monthly household income (e.g. OR 1.92 [1.40-2.64] for an income >CHF 10’000 vs. an income ≤ CHF 6’000), more frequent internet use (e.g., daily (reference) vs. less than weekly OR 0.37 [0.16-0.85]), better adherence to mask-wearing recommendations (e.g., always or most of the time (reference) vs. rarely or never OR 0.28 [0.15-0.52]), and being a non-smoker (OR 1.32 [1.01-1.71]) were associated with an increased likelihood for app uptake. Citizenship status (e.g., non-Swiss citizenship 0.61 [0.43-0.87] vs. Swiss citizenship only), and language region (French 0.61 [0.46-0.80], vs. Swiss German) were associated with a lower app uptake probability. In a randomly selected subsample (n=711) with more detailed information, higher levels of trust in government and health authorities were additionally associated with a higher app uptake probability (e.g., OR 3.13 [1.58-6.22] for high vs. low trust (reference)). The most frequent reasons for app non-use was lack of perceived benefit of the app (36.8%), 22.8% reported to have no compatible phone, and 22.4% had privacy concerns. Conclusion Removing technical hurdles and communicating the benefits of DPT-apps are crucial to promote further uptake, compliance, and ultimately to enhance effectiveness of DPT-apps for pandemic mitigation.

Background: Traumatic spinal cord injuries (TSCI) are a neurological condition associated with reduced well-being, increased morbidity and reductions in life expectancy. Estimates of all-cause and cause-specific mortality can aid in identifying targets for prevention and management of contributors for premature mortality. Objectives: To compare all-cause and cause-specific rates of mortality to that of the Swiss general population; to identify differentials in risk of cause-specific mortality according to lesion characteristics. Methods: All-cause and cause-specific standardized mortality ratios (SMRs) were calculated using data from the Swiss Spinal Cord Injury cohort study. Cause-specific subhazard ratios were estimated within a competing risk framework using flexible parametric survival models. Results: Between 1990 and 2011, 2,492 persons sustained a TSCI, of which 379 died. Persons with TSCI had a mortality rate more than 2 times higher than that of the Swiss general population (SMR 2.32; 95% CI 2.10–2.56). Tetraplegic lesions were associated with an increased risk of mortality due to respiratory and cardiovascular diseases, infections, and accidents. Cause-specific SMRs were notably elevated for SCI-related conditions such as urinary tract infections (UTIs) and septicemia. Conclusions: Elevated SMRs due to cardiovascular disease, UTIs and septicemia-related mortality suggest the need for innovation when managing associated secondary health conditions.

In a recent issue of the American Journal of Public Health, Herna´n and other colleagues strongly plea for causal thinking in scientific research where the research question investigates consequences of decisions and interventions (Ahern 2018; Begg and March 2018; Chiolero 2018; Glymour and Hamad 2018; Herna´n 2018a, b; Jones and Schooling 2018). Herna´n argues that causal reasoning improves quality of observational research; however, the causal terminology is often loomed by the ‘association is not causation’ argument and is viewed with skepticism (Herna´n 2018b). Health services research (HSR) supports decision making by investigating the effect of complex ‘interventions’ or ‘policies’ on different healthcare system outcomes (Glass et al. 2013). Thus, some of the research questions in HSR are inherently causal. Surprisingly, there is no consensus on how to integrate causal inference into tasks of HSR (Dowd 2011; O’Malley 2011; Pearl 2011; Herna´n et al. 2019). Typically, tasks in data science are classified into ‘description’, ‘modeling’ and ‘causal inference’ (Herna´n et al. 2019). In the present Hints and Kinks, we explain why a solidly principled causal inference framework should be integrated into the tasks of HSR.

OBJECTIVES To develop a predictive model and risk score for 10-year mortality using health-related quality of life (HRQOL) in a cohort of older women with early-stage breast cancer. DESIGN Prospective cohort. SETTING Community. PARTICIPANTS U.S. women aged 65 and older diagnosed with Stage I to IIIA primary breast cancer (N=660). MEASUREMENTS We used medical variables (age, comorbidity), HRQOL measures (10-item Physical Function Index and 5-item Mental Health Index from the Medical Outcomes Study (MOS) 36-item Short-Form Survey; 8-item Modified MOS Social Support Survey), and breast cancer variables (stage, surgery, chemotherapy, endocrine therapy) to develop a 10-year mortality risk score using penalized logistic regression models. We assessed model discriminative performance using the area under the receiver operating characteristic curve (AUC), calibration performance using the Hosmer-Lemeshow test, and overall model performance using Nagelkerke R(NR). RESULTS Compared to a model including only age, comorbidity, and cancer stage and treatment variables, adding HRQOL variables improved discrimination (AUC 0.742 from 0.715) and overall performance (NR 0.221 from 0.190) with good calibration (p=0.96 from HL test). CONCLUSION In a cohort of older women with early-stage breast cancer, HRQOL measures predict 10-year mortality independently of traditional breast cancer prognostic variables. These findings suggest that interventions aimed at improving physical function, mental health, and social support might improve both HRQOL and survival.

Objectives This study sought to evaluate whether frailty improves mortality prediction in combination with the conventional scores. Background European System for Cardiac Operative Risk Evaluation (EuroSCORE) or Society of Thoracic Surgeons (STS) score have not been evaluated in combined models with frailty for mortality prediction after transcatheter aortic valve replacement (TAVR). Methods This prospective cohort comprised 330 consecutive TAVR patients ≥70 years of age. Conventional scores and a frailty index (based on assessment of cognition, mobility, nutrition, and activities of daily living) were evaluated to predict 1-year all-cause mortality using Cox proportional hazards regression (providing hazard ratios [HRs] with confidence intervals [CIs]) and measures of test performance (providing likelihood ratio [LR] chi-square test statistic and C-statistic [CS]). Results All risk scores were predictive of the outcome (EuroSCORE, HR: 1.90 [95% CI: 1.45 to 2.48], LR chi-square test statistic 19.29, C-statistic 0.67; STS score, HR: 1.51 [95% CI: 1.21 to 1.88], LR chi-square test statistic 11.05, C-statistic 0.64; frailty index, HR: 3.29 [95% CI: 1.98 to 5.47], LR chi-square test statistic 22.28, C-statistic 0.66). A combination of the frailty index with either EuroSCORE (LR chi-square test statistic 38.27, C-statistic 0.72) or STS score (LR chi-square test statistic 28.71, C-statistic 0.68) improved mortality prediction. The frailty index accounted for 58.2% and 77.6% of the predictive information in the combined model with EuroSCORE and STS score, respectively. Net reclassification improvement and integrated discrimination improvement confirmed that the added frailty index improved risk prediction. Conclusions This is the first study showing that the assessment of frailty significantly enhances prediction of 1-year mortality after TAVR in combined risk models with conventional risk scores and relevantly contributes to this improvement.

In a previous Hints and Kinks, we discussed the role of causal inference in tasks of health services research (HSR) using examples from health system interventions (Moser et al. 2020). In the present Hints and Kinks, we more formally introduce a principled framework for causal inference. Specifically, we discuss in more detail the role of counterfactuals for the definition of a causal effect and the ‘association is not causation’ adage. We continue on the example of a hospital merger (HM) as a health system intervention.

New innovative Digital Twins can represent complex bioprocesses, including the biological, physico-chemical, and chemical reaction kinetics, as well as the mechanical and physical characteristics of the reactors and the involved peripherals. Digital Twins are an ideal tool for the rapid and cost-effective development, realisation and optimisation of control and automation strategies. They may be utilised for the development and implementation of conventional controllers (e.g. temperature, dissolved oxygen, etc.), as well as for advanced control strategies (e.g. control of substrate or metabolite concentrations, multivariable controls), and the development of complete bioprocess control. This chapter describes the requirements Digital Twins must fulfil to be used for bioprocess control strategy development, and implementation and gives an overview of research projects where Digital Twins or "early-stage" Digital Twins were used in this context. Furthermore, applications of Digital Twins for the academic education of future control and bioprocess engineers as well as for the training of future bioreactor operators will be described. Finally, a case study is presented, in which an "early-stage" Digital Twin was applied for the development of control strategies of the fed-batch cultivation of Saccharomyces cerevisiae. Development, realisation and optimisation of control strategies utilising Digital Twins.

Die Versorgungsforschung ist wichtig zur Steuerung des Gesundheitswesens. Entsprechend wurde sie in der Schweiz in den vergangenen Jahren finanziell ge­fördert. Es entstanden interessante Beschreibungen der Situation. Für die nächste Stufe – fundierte Antworten bezüglich der Auswirkungen von getroffenen/geplanten Massnahmen – braucht es gezielte Versuche und eine intelligente Zusammen­führung von Daten.

AIMS OF THE STUDY During the transitional phase between the two pandemic waves of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infection rates were temporarily rising among younger persons only. However, following a temporal delay infections started to expand to older age groups. A comprehensive understanding of such transmission dynamics will be key for managing the pandemic in the time to come and to anticipate future developments. The present study thus extends the scope of previous SARS-CoV-2-related research in Switzerland by contributing to deeper insight into the potential impact of “social mixing” of different age groups on the spread of SARS-CoV-2 infections. METHODS The present study examined persons aged 65 years and older with respect to possible SARS-CoV-2 exposure risks using longitudinal panel data from the Swiss COVID-19 Social Monitor. The study used data from two assessments (survey “May” and survey “August”). Survey “May” took place shortly after the release of the lockdown in Switzerland. Survey “August” was conducted in mid-August. To identify at-risk elderly persons, we conducted a combined factor/k-means clustering analysis of the survey data assessed in August in order to examine different patterns of adherence to recommended preventive measures. RESULTS In summary, 270 (survey “May”) and 256 (survey “August”) persons aged 65 years and older were analysed for the present study. Adherence to established preventive measures was similar across the two surveys, whereas adherence pertaining to social contacts decreased substantially from survey “May” to survey “August”. The combined factor/k-means clustering analysis to identify at-risk elderly individuals yielded four distinct groups with regard to different patterns of adherence to recommended preventive measures: a larger group of individuals with many social contacts but high self-reported adherence to preventive measures (n = 86); a small group with many social contacts and overall lower adherence (n = 26); a group with comparatively few contacts and few social activities (n = 66); and a group which differed from the latter through fewer contacts but more social activities (n = 78). Sociodemographic characteristics and risk perception with regard to SARS-CoV-2 infections among the four groups did not differ in a relevant way across the four groups. CONCLUSIONS Although many elderly persons continued to follow the recommended preventive measures during the transitional phase between the two pandemic waves, social mixing with younger persons constitutes a way for transmission of infections across age groups. Pandemic containment among all age groups thus remains essential to protect vulnerable populations, including the elderly.

A future-oriented approach is the application of Digital Twins for process development, optimization and finally during manufacturing. Digital Twins are detailed virtual representations of bioprocesses with predictive capabilities. In biotechnology, Digital Twins can be used to monitor processes and to provide data for process control and optimization. Central and crucial components of Digital Twins are mathematical process models, which are capable to describe and predict cultivations with high fidelity. Detailed mechanistic models in particular are suitable for both use in Digital Twins and for the development of process control strategies.In this chapter the requirements that process models must fulfil in order to be used for process optimization and finally in Digital Twins will be described. Different types of models, including mechanistic as well as compartmentalized models, are outlined and their application in Digital Twins and for process optimization is explained. Finally, a structured, compartmentalized process model, which was specifically designed for process optimization and has already been used in Digital Twins, is highlighted.

To estimate excess mortality and life years lost in a Swiss cohort of individuals with traumatic spinal cord injury (TSCI). This study uses population-based data collected in the Swiss Spinal Cord Injury Cohort (SwiSCI) study, which covers all specialized rehabilitation centres. Flexible parametric survival models were used to model life years remaining (LYR), potential years life lost (PYLL), relative survival and excess hazard ratios. Men and women with TSCI and an attained age of 30 were estimated to have 42 LYR (95% CI = 37.9–45.5) and 43 LYR (95% CI = 40.1–45.5), respectively; this equates to a life expectancy (LE) of 80.6 and 76.9% of that of the Swiss general population. With respect to lesion level and completeness, persons with incomplete paraplegia had 45.1 LYR at an attained age of 30, whereas individuals with complete tetraplegia only had 28.7 LYR. This pattern was similar for PYLL. The extended LE following TSCI, even for the most severe lesions, underscores the need for sustained follow-up to support functioning and health for individuals ageing with SCI.