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Teaching epidemiological concepts in academic settings poses a challenge due to the intricate nature of the discipline as both a science and a practice. Whereas traditional classroom-based teaching methods are commonly employed, evidence suggests they may not be the most effective approach for fostering core competencies and skills required in real-life scientific work. In this article, we describe our process of transitioning from traditional classroom teaching of epidemiology towards practice-based coaching to convey epidemiological concepts to bachelor's and master's students in Biomedicine. We chose the framework of randomized controlled trials (RCT) since they offer a great opportunity to teach epidemiological concepts in a hands-on course. This practice-based course encompasses the entire life cycle of a study, allowing students to design and conduct a short-term experiment, analyse its data and prepare a scientific paper. We provide a comprehensive overview of the course structure, content, learning objectives and course evaluation, while also discussing the advantages and disadvantages of this innovative format. Our approach offers a promising alternative to classroom teaching by incorporating practical, hands-on experiences offering students a high level of independence and self-determination, as well as facilitation and coaching by faculty. It has the potential to be applied across diverse academic settings, providing students with valuable skills and competencies in epidemiology., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Qualitative research and mixed methods are core competencies for epidemiologists. In response to the shortage of guidance on graduate course development, we wrote a course development guide aimed at faculty and students designing similar courses in epidemiology curricula. The guide combines established educational theory with faculty and student experiences from a recent introductory course for epidemiology and biostatistics doctoral students at the University of Zurich and Swiss Federal Institute of Technology, Zurich. We propose a student-centred course with inverse classroom teaching and practice exercises with faculty input. Integration of student input during the course development process helps align the course syllabus with student needs. The proposed course comprises six sessions that cover learning outcomes in comprehension, knowledge, application, analysis, synthesis and evaluation. Following an introductory session, the students engage in face-to-face interviews, focus group interviews, observational methods, analysis and how qualitative and quantitative methods are integrated in mixed methods. Furthermore, the course covers interviewer safety, research ethics, quality in qualitative research and a practice session focused on the use of interview hardware, including video and audio recorders. The student-led teaching characteristic of the course allows for an immersive and reflective teaching-learning environment. After implementation of the course and learning from faculty and student perspectives, we propose these additional foci: a student project to apply learned knowledge to a case study; integration in mixed-methods; and providing faculty a larger space to cover theory and field anecdotes. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) symptoms are expected to aggregate in specific patterns across different stages of the disease. Here, we studied the clustering of onset symptoms and examined their characteristics, comorbidity patterns and associations with potential risk factors. Methods: Data stem from the Swiss Multiple Sclerosis Registry, a prospective study including 2,063 participants by November 2019. MS onset symptoms were clustered using latent class analysis (LCA). The latent classes were further examined using information on socio-demographic characteristics, MS-related features, potential risk factors, and comorbid diseases. Results: The LCA model with six classes (frequencies ranging from 12 to 24%) was selected for further analyses. The latent classes comprised a multiple symptoms class with high probabilities across several symptoms, contrasting with two classes with solitary onset symptoms: vision problems and paresthesia. Two gait classes emerged between these extremes: the gait-balance class and the gait-paralysis class. The last class was the fatigue-weakness-class, also accompanied by depression symptoms, memory, and gastro-intestinal problems. There was a moderate variation by sex and by MS types. The multiple symptoms class yielded increased comorbidity with other autoimmune disorders. Similar to the fatigue-weakness class, the multiple symptoms class showed associations with angina, skin diseases, migraine, and lifetime prevalence of smoking. Mononucleosis was more frequently reported in the fatigue-weakness and the paresthesia class. Familial aggregation did not differ among the classes. Conclusions: Clustering of MS onset symptoms provides new perspectives on the heterogeneity of MS. The clusters comprise different potential risk factors and comorbidities. They point toward different risk mechanisms. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to describe the factors associated with mortality by suicide among working women focusing on work-related factors. Methods: The study population consisted in all Swiss residents recorded in the 1990 and/or the 2000 compulsory national censuses and were linked to emigration and mortality registers. We selected all women aged 18–65 and at work at the official census dates. Following work-related variables were available: socio-economic status, weekly hours of work, the sector of activity and the job title coded according to the International Standard Classification of Occupations (ISCO). The risk of suicide was modelled using negative binomial regression. Results: The cohort comprised 1,771,940 women and 2526 deaths by suicide corresponding to 24.9 million person-years. The most significant non-occupational predictors of suicide were age, period, civil status, religion, nationality and geographical regions. Adjusted on these factors, part-time work was associated with increased suicide rates. According to job codes, health and social activities, in particular care-worker had the highest suicide risks. Conclusion: Suicide among working women depended on work-related factors even taking into account other socio-demographic factors. [ABSTRACT FROM AUTHOR]

Only a few efforts have been made to define core competencies for epidemiologists working in academic settings. Here we describe a multinational effort to define competencies for epidemiologists, who are increasingly facing emerging and potentially disruptive technological and societal health trends in academic research. During a 1.5-year period (2017–2019), we followed an iterative process that aimed to be inclusive and multinational to reflect the various perspectives of a diverse group of epidemiologists. Competencies were developed by a consortium in a consensus-oriented process that spanned 3 main activities: 2 in-person interactive meetings held in Amsterdam, the Netherlands, and Zurich, Switzerland, and an online survey. In total, 93 meeting participants from 16 countries and 173 respondents from 19 countries contributed to the development of 31 competencies. These 31 competencies included 14 on "developing a scientific question" and "study planning," 12 on "study conduct and analysis," 3 on "overarching competencies," and 2 on "communication and translation." The process described here provides a consensus-based framework for defining and adapting the field. It should initiate a continuous process of thinking about competencies and the implications for teaching epidemiology to ensure that epidemiologists working in academic settings are well prepared for today's and tomorrow's health research. [ABSTRACT FROM AUTHOR]

Background: Diagnosing multiple sclerosis (MS) early is crucial to avoid future disability. However, potentially preventable delays in the diagnostic cascade from contact with a physician to definite diagnosis still occur and their causes are still unclear. Objective: To identify the possible causes of delays in the diagnostic process. Methods: We analyzed the data of the Swiss MS Registry. With logistic regression, we modeled the time from the first contact to the first consultation (contact-to-evaluation time, ⩽1 month/>1 month) and the evaluation-to-diagnosis time (⩽6 months/>6 months). Potential factors were health system characteristics, sociodemographic variables, first symptoms, and MS type. Results: We included 522 participants. Mostly, general practitioners (67%) were contacted first, without delaying the diagnosis. In contrast, first symptoms and MS type were the major contributors to delays: gait problems were associated with longer contact-to-evaluation times, depression as a concomitant symptom with longer evaluation-to-diagnosis times, and having primary progressive MS prolonged both phases. In addition, living in mountainous areas was associated with longer contact-to-evaluation times, whereas diagnosis after 2000 was associated with faster diagnoses. Conclusion: For a quicker diagnosis, awareness of MS as a differential diagnosis of gait disorders and the co-occurrence of depression at onset should be raised, and these symptoms should be attentively followed. [ABSTRACT FROM AUTHOR]

Rationale: Most studies determining the prevalence of airway obstruction are limited to short time periods.Objectives: Because temporal trends of obstruction in populations are largely unknown, we determined the prevalence of airway obstruction over 20 years in yearly general population samples in Switzerland between 1993 and 2012.Methods: We analyzed data of 85,789 participants aged 35 years and older who provided spirometric measurements as part of the LuftiBus lung function campaign. We linked data from the 2003-2012 period to the Swiss National Cohort to adjust for annual population differences. Spirometry was performed without bronchodilation, according to American Thoracic Society guidelines. We used Global Lung Initiative (GLI) and Hankinson reference equations to identify obstruction.Results: Obstruction prevalence increased between 1993 and 2012 from 6.1% (95% confidence interval [CI], 5.5 to 6.7) to 15.6% (95% CI, 13.8 to 17.3) based on GLI estimates and from 5.3% (95% CI, 4.7 to 5.9) to 15.4% (95% CI, 13.6 to 17.1) based on Hankinson estimates. When adjusted for participant demographics, air pollutant and occupational exposures, altitude, and season, the prevalence ratios of obstruction were 1.54 (95% CI, 1.22 to 1.93) and 1.65 (95% CI, 1.33 to 2.04) for GLI- and Hankinson-defined airway obstruction, respectively, for 2012 compared with 2003.Conclusions: Though prebronchodilator measurements likely overestimate the prevalence of airway obstruction in absolute terms compared with post-bronchodilator measurements, we found an increase in airway obstruction prevalence. Even with adjustment for several well-known risk factors for obstruction to make the populations across the years more comparable, we still saw a statistically significant increase in prevalence over this time period. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) is the most common chronic, non-traumatic, neurologic disease in young adults. While approximate values of the disease burden of MS are known, individual drivers are unknown. Objective: To estimate the age-, sex-, and disease severity-specific contributions to the disease burden of MS. Methods: We estimated the disease burden of MS using disability-adjusted life years (DALYs) following the Global Burden of Disease study (GBD) methodology. The data sources consisted of the Swiss MS Registry, a recent prevalence estimation, and the Swiss mortality registry. Results: The disease burden of MS in Switzerland in 2016 was 6,938 DALYs (95%-interval: 6,018-7,955), which corresponds to 97 DALYs per 100,000 adult inhabitants. Morbidity contributed 59% of the disease burden. While persons in an asymptomatic (EDSS-proxy 0) and mild (EDSS-proxy >0–3.5) disease stage represent 68.4% of the population, they make up 39.8% of the MS-specific morbidity. The remaining 60.2% of the MS-specific morbidity stems from the 31.6% of persons in a moderate (EDSS-proxy 4–6.5) or severe (EDSS-proxy ≥7) disease stage. Conclusions: Morbidity has a larger influence on the disease burden of MS than mortality and is shared in a ratio of 2:3 between persons in an asymptomatic/mild and moderate/severe disease stage in Switzerland. Interventions to reduce severity worsening in combination with tailored, symptomatic treatments are important future paths to lower the disease burden of MS. [ABSTRACT FROM AUTHOR]

Background: When population-based databases are unavailable, nationwide assessments of the disease burden of multiple sclerosis (MS) resort to clinical, administrative or convenience-sampled data sources, which may produce results of limited external validity. Our aim was to develop a framework for estimating measures of occurrence of chronic diseases, and more broadly disease burden, that mitigate these limitations and to apply this framework to estimate the prevalence of multiple sclerosis (MS) in Switzerland. Methods: We developed a 7-step framework which implements the combination of several data sources together with a resampling and critical appraisal approach. The framework was applied to estimate the MS prevalence for 2016 in Switzerland, for which four distinct data sources (Swiss MS registry, Swiss national MS treatment registry, MediService database, and Swiss MS cohort study) were combined. Results were reviewed by disease experts and compared to earlier Swiss estimates and current prevalence estimates from other countries. Results: We estimate that in the year 2016 between 14,650 and 15,700 persons with MS have been living in Switzerland, yielding a period prevalence of 174–187/100,000 inhabitants. Compared to the last estimate in 1986, we detected a substantial increase of MS diagnoses which coincides with a higher number of diagnoses in women below the age of 65. Conclusions: Internationally, Switzerland is a high-prevalence country for MS, although estimates were somewhat lower than recent evaluations of Northern European countries. In addition, we corroborate previous reports that the prevalence increase coincides with a higher number of MS diagnoses among women. The proposed framework has wide applicability and the potential to place estimates of disease occurrence and burden with imperfect data availability on more solid grounds. [ABSTRACT FROM AUTHOR]

Background New research methods offer opportunities to investigate the influence of environment on health during travel. Our study uses data from a smartphone application to describe spatial and environmental patterns in health among travellers. Methods A prospective cohort of travellers to Thailand used a smartphone application during their trips to 1) answer a daily questionnaire about health behaviours and events, and 2) collect streaming data on environment, itinerary, and weather. Incidence of health events was described by region and trip type. The relationship between environmental factors and health events was modelled using a logistic mixed model. Results The 75/101 (74.3%) travellers that completed the study answered 940 questionnaires, 796 (84.7%) of which were geolocated to Southeast Asia. Accidents occurred to 20.0% of participants and were mainly in the Thai islands, while self-rated “severe” mental health events (21.3%) were centred in Bangkok. The odds of a health event were higher in Chiang Mai (2.34, 95% CI: 1.08, 5.08) and on rainy days (1.86, 95% CI: 1.03, 3.36). Conclusions Distinct patterns in spatial and environmental risk factors emerged in travellers to Thailand. Location based tracking could identify “hotspots” for health problems and update travel advice to target specific risk groups and regions. [ABSTRACT FROM AUTHOR]

Background: Travel medicine research has remained relatively unchanged in the face of rapid expansion of international travel and is unlikely to meet health challenges beyond infectious diseases. Our aim was to identify the range of health outcomes during travel using real-time monitoring and daily reporting of health behaviours and outcomes and identify traveller subgroups who may benefit from more targeted advice before and during travel.Methods: We recruited a prospective cohort of travellers ≥ 18 years and planning travel to Thailand for <5 weeks from the travel clinics in Zurich and Basel (Switzerland). Participants answered demographic, clinical and risk behaviour questionnaires pre-travel and a daily health questionnaire each day during travel using a smartphone application. Environmental and location data were collected passively by GPS. Classification trees were used to identify predictors of health behaviour and outcomes during travel.Results: Non-infectious disease events were relatively common, with 22.7% (17 out of 75 travellers) experiencing an accident, 40.0% ( n  = 30) a wound or cut and 14.7% ( n  = 11) a bite or lick from an animal. Mental health associated events were widely reported, with 80.0% ( n  = 60) reporting lethargy, 34.7% ( n  = 26) anxiety and 34.7% ( n  = 26) feeling tense or irritable. Classification trees identified age, trip length, previous travel experience and having experienced a sports injury in the past year as the most important discriminatory variables for health threats.Conclusions: Our study offers a revolutionary look at an almost real-time timeline of health events and behaviours during travel using mHealth technology. Non-infectious disease related health issues were common in this cohort, despite being largely unaddressed in traditional travel medicine research and suggest a substantial potential for improving evidence-based travel medicine advice. [ABSTRACT FROM AUTHOR]

Background: COPD prevalence is highly variable and geographical altitude has been linked to it, yet with conflicting results. We aimed to investigate this association, considering well known risk factors.Methods: A pooled analysis of individual data from the PREPOCOL-PLATINO-BOLD-EPI-SCAN studies was used to disentangle the population effect of geographical altitude on COPD prevalence. Post-bronchodilator FEV1/FVC below the lower limit of normal defined airflow limitation consistent with COPD. High altitude was defined as >1500 m above sea level. Undiagnosed COPD was considered when participants had airflow limitation but did not report a prior diagnosis of COPD.Results: Among 30,874 participants aged 56.1 ± 11.3 years from 44 sites worldwide, 55.8% were women, 49.6% never-smokers, and 12.9% (3978 subjects) were residing above 1500 m. COPD prevalence was significantly lower in participants living at high altitude with a prevalence of 8.5% compared to 9.9%, respectively (p < 0.005). However, known risk factors were significantly less frequent at high altitude. Hence, in the adjusted multivariate analysis, altitude itself had no significant influence on COPD prevalence. Living at high altitude, however, was associated with a significantly increased risk of undiagnosed COPD. Furthermore, subjects with airflow limitation living at high altitude reported significantly less respiratory symptoms compared to subjects residing at lower altitude.Conclusion: Living at high altitude is not associated with a difference in COPD prevalence after accounting for individual risk factors. However, high altitude itself was associated with an increased risk of undiagnosed COPD. [ABSTRACT FROM AUTHOR]

Background: Prediction models in autosomal dominant polycystic kidney disease (ADPKD) are useful in clinical settings to identify patients with greater risk of a rapid disease progression in whom a treatment may have more benefits than harms. Mayo Clinic investigators developed a risk prediction tool for ADPKD patients using a single kidney value. Our aim was to perform an independent geographical and temporal external validation as well as evaluate the potential for improving the predictive performance by including additional information on total kidney volume.Methods: We used data from the on-going Swiss ADPKD study from 2006 to 2016. The main analysis included a sample size of 214 patients with Typical ADPKD (Class 1). We evaluated the Mayo Clinic model performance calibration and discrimination in our external sample and assessed whether predictive performance could be improved through the addition of subsequent kidney volume measurements beyond the baseline assessment.Results: The calibration of both versions of the Mayo Clinic prediction model using continuous Height adjusted total kidney volume (HtTKV) and using risk subclasses was good, with R2 of 78% and 70%, respectively. Accuracy was also good with 91.5% and 88.7% of the predicted within 30% of the observed, respectively. Additional information regarding kidney volume did not substantially improve the model performance.Conclusion: The Mayo Clinic prediction models are generalizable to other clinical settings and provide an accurate tool based on available predictors to identify patients at high risk for rapid disease progression. [ABSTRACT FROM AUTHOR]

Background: Only few countries have cohorts enabling specific and up-to-date cardiovascular disease (CVD) risk estimation. Individual risk assessment based on study samples that differ too much from the target population could jeopardize the benefit of risk charts in general practice. Our aim was to provide up-to-date and valid CVD risk estimation for a Swiss population using a novel record linkage approach. Methods: Anonymous record linkage was used to follow-up (for mortality, until 2008) 9,853 men and women aged 25–74 years who participated in the Swiss MONICA (MONItoring of trends and determinants in CVD) study of 1983–92. The linkage success was 97.8%, loss to follow-up 1990–2000 was 4.7%. Based on the ESC SCORE methodology (Weibull regression), we used age, sex, blood pressure, smoking, and cholesterol to generate three models. We compared the 1) original SCORE model with a 2) recalibrated and a 3) new model using the Brier score (BS) and cross-validation. Results: Based on the cross-validated BS, the new model (BS = 14107×10−6) was somewhat more appropriate for risk estimation than the original (BS = 14190×10−6) and the recalibrated (BS = 14172×10−6) model. Particularly at younger age, derived absolute risks were consistently lower than those from the original and the recalibrated model which was mainly due to a smaller impact of total cholesterol. Conclusion: Using record linkage of observational and routine data is an efficient procedure to obtain valid and up-to-date CVD risk estimates for a specific population. [ABSTRACT FROM AUTHOR]

Background: The population with multiple chronic conditions is growing. Prior studies indicate that patients with comorbidities are frequently excluded from trials but do not address whether information is available in trials to draw conclusions about treatment effects for these patients. Methods and Findings: We conducted a literature survey of trials from 11 Cochrane Reviews for four chronic diseases (diabetes, heart failure, chronic obstructive pulmonary disease, and stroke). The Cochrane Reviews systematically identified and summarized trials on the effectiveness of diuretics, metformin, anticoagulants, longacting beta-agonists alone or in combination with inhaled corticosteroids, lipid lowering agents, exercise and diet. Eligible studies were reports of trials included in the Cochrane reviews and additional papers that described the methods of these trials. We assessed the exclusion and inclusion of people with comorbidities, the reporting of comorbidities, and whether comorbidities were considered as potential modifiers of treatment effects. Overall, the replicability of both the inclusion criteria (mean [standard deviation (SD)]: 6.0 (2.1), range (min-max): 1-9.5) and exclusion criteria(mean(SD): 5.3 (2.1), range: 1-9.5) was only moderate. Trials excluded patients with many common comorbidities. The proportion of exclusions for comorbidities ranged from 0-42 percent for heart failure, 0-55 percent for COPD, 0-44 percent for diabetes, and 0-39 percent for stroke. Seventy of the 161 trials (43.5%) described the prevalence of any comorbidity among participants with the index disease. The reporting of comorbidities in trials was very limited, in terms of reporting an operational definition and method of ascertainment for the presence of comorbidity and treatments for the comorbidity. It was even less common that the trials assessed whether comorbidities were potential modifiers of treatment effects. Conclusions: Comorbidities receive little attention in chronic disease trials. Given the public health importance of people with multiple chronic conditions, trials should better report on comorbidities and assess the effect comorbidities have on treatment outcomes. [ABSTRACT FROM AUTHOR]

The assessment of physical activity in healthy populations and in those with chronic diseases is challenging. The aim of this systematic review was to identify whether available activity monitors (AM) have been appropriately validated for use in assessing physical activity in these groups. Following a systematic literature search we found 134 papers meeting the inclusion criteria; 40 conducted in a field setting (validation against doubly labelled water), 86 in a laboratory setting (validation against a metabolic cart, metabolic chamber) and 8 in a field and laboratory setting. Correlation coefficients between AM outcomes and energy expenditure (EE) by the criterion method (doubly labelled water and metabolic cart/chamber) and percentage mean differences between EE estimation from the monitor and EE measurement by the criterion method were extracted. Random-effects meta-analyses were performed to pool the results across studies where possible. Types of devices were compared using meta-regression analyses. Most validation studies had been performed in healthy adults (n = 118), with few carried out in patients with chronic diseases (n = 16). For total EE, correlation coefficients were statistically significantly lower in uniaxial compared to multisensor devices. For active EE, correlations were slightly but not significantly lower in uniaxial compared to triaxial and multisensor devices. Uniaxial devices tended to underestimate TEE (-12.07 (95%CI; -18.28 to -5.85) %) compared to triaxial (-6.85 (95%CI; -18.20 to 4.49) %, p = 0.37) and were statistically significantly less accurate than multisensor devices (-3.64 (95%CI; -8.97 to 1.70) %, p<0.001). TEE was underestimated during slow walking speeds in 69% of the lab validation studies compared to 37%, 30% and 37% of the studies during intermediate, fast walking speed and running, respectively. The high level of heterogeneity in the validation studies is only partly explained by the type of activity monitor and the activity monitor outcome. Triaxial and multisensor devices tend to be more valid monitors. Since activity monitors are less accurate at slow walking speeds and information about validated activity monitors in chronic disease populations is lacking, proper validation studies in these populations are needed prior to their inclusion in clinical trials. [ABSTRACT FROM AUTHOR]

The adoption of mHealth technology in travel medicine is a relatively new and unexplored field. We have further developed a TRAVEL application (app) for real-time data monitoring during travel. In this manuscript we report on the feasibility using this new app in a large and diverse cohort of travellers to three continents. We enrolled 1000 participants from the travel clinics of Zurich and Basel, Switzerland, aged ≥18 years, travelling to Thailand, India, China, Tanzania, Brazil and Peru between 09/2017–01/2019. Participants included healthy travellers, individuals with pre-existing chronic diseases and elderly travellers (≥60 years). Participants completed an app-based daily survey on risk behaviours/health incidents pre-, during and after travel. Simultaneously, GPS locations were tightly collected and linked to environmental data. 793 (79%) travellers answered at least one questionnaire during their trip. Participants' median age was 34 years (range 18–84 years); 8% were aged ≥60 years; 55% female; 32% had pre-existing chronic diseases. Completion rates were similar in younger and elderly travellers and in those with and without pre-existing diseases. The use of a smartphone app is a feasible method for collecting behavioural and health data in elderly travellers and individuals with chronic diseases travelling to three continents. [ABSTRACT FROM AUTHOR]

Background: Despite the continuing growth of international tourism, very little research has been done on the link between individual risk attitudes and health behaviours during travel. Our study uses a validated risk-taking questionnaire Domain-Specific Risk-Taking Scale (DOSPERT) and data from a smartphone application to study the association between pre-travel risk attitudes and the occurrence of behaviours during travel.Methods: A prospective cohort of travellers to Thailand used a smartphone application to answer a daily questionnaire about health behaviours and events. Prior to travel, participants completed the DOSPERT, a validated 30-item scale that assesses risk-taking and perception in five content domains: financial decisions, health/safety, recreational, ethical and social decisions. Multiple linear regression models were used to model the relationship between DOSPERT risk-taking subdomain score and health behaviour.Results: Of the 75 travellers that completed the study, 70 (93.3%) completed the DOSPERT pre-travel. Men, backpackers and young travellers reported a higher willingness to take recreational risks than women, luxury travellers and older travellers. Incidence of drug and alcohol risk behaviours during travel, itching from mosquitoes, smoking and failing to use a seatbelt in automobiles while at home were all significantly associated with an individual's score on the health and safety DOSPERT subdomain.Conclusions: In our study, individual scores on risk-taking in the health and safety subdomain of the DOSPERT questionnaire seem to be predictive of health behaviours both during travel and at home. By pairing new methods of data collection with questionnaires such as DOSPERT that identify key traveller characteristics to intervene on, travel medicine doctors will be able to provide more specialised health advice, ensuring that all travellers receive well-rounded advice about the full range of health challenges they will face during travel. [ABSTRACT FROM AUTHOR]