Frontiers in Public Health

Background: Health and administrative professionals in tertiary hospitals face high levels of occupational stress, mental illness, and multimorbidity. The integrated measurement of these multidimensional health aspects is essential for informing effective workplace health promotion strategies. Objective: To describe the general health status of federal public hospital staff and correlate the measured health dimensions to inform institutional health promotion initiatives. Methods: A cross-sectional, online survey study was conducted at Hospital Universitario dos Servidores do Estado (HUSE) between November and December 2025. Data collection was performed via online REDCap questionnaires covering sociodemographic profiles and validated instruments (SRQ-20, MIDAS, AUDIT, WHOQOL-BREF, PHI, WHOQOL-SRPB BREF, CBI, GPAQ, and EPSO). Descriptive statistics, comparisons across employment ties (permanent vs. contracted staff), and Spearman correlation matrices were calculated. Results: Among 197 accesses, 117 completed the informed consent, and 86 finished all questionnaires. Participants were predominantly female, aged 40 to 60 years, and Christian. Screening positivity was 25% for common mental disorders, 21% for headache-related disability, and 10% for harmful drinking. Burnout scores clustered in the second quartile, while quality of life, happiness, and spirituality scores were in the upper third. Median physical activity was 670 min/week. Mental symptoms (SRQ-20), headache (MIDAS), and burnout (CBI) correlated positively with each other and negatively with quality of life, happiness, spirituality, and institutional support (EPSO). Conclusion: The set of instruments proved feasible for situational health diagnosis among hospital staff. Although the sample size was limited in this baseline wave, the initiative fostered workplace health awareness, driving concrete initiatives, including an on-site functional gym and workplace vaccination campaigns.

Background: General illness-related sick leave among teachers represents a relevant public health and workforce management issue. However, long-term population-based evidence describing its distribution and associated factors in Latin American urban educational systems remains limited. This study aimed to characterize the occurrence, distribution, duration, and sociodemographic, occupational, temporal, and territorial factors associated with general illness-related sick leave among public school teachers in Bogota between 2010 and 2025. Methods: A retrospective cohort study was conducted using integrated administrative databases from the Bogota District Department of Education. The primary outcome was the occurrence of at least one general illness-related sick leave episode in a teacher-month observation. Descriptive analyses were performed to characterize sociodemographic and occupational patterns. A multivariable logistic regression model was used to estimate associations. Month and year were included as temporal fixed effects to account for seasonal patterns, academic-calendar effects, pandemic-related disruption, and secular changes. Results: The cohort included 59,697 unique teachers, contributing 537,025 teacher-year observations from teachers with an active employment record between January 1, 2010, and July 31, 2025. Overall, 41.59% of teacher-year observations included at least one general illness-related sick leave episode, and 83.26% of teachers had at least one episode at any time during follow-up. Respiratory diseases accounted for the largest share of episodes, followed by musculoskeletal and infectious diseases. Mean duration varied substantially by diagnostic category, ranging from short respiratory and infectious episodes to longer absences related to neoplasms, circulatory diseases, injuries, and mental health conditions. In the multivariable teacher-month model, sick leave occurrence was associated with age, sex, occupational role, teaching area, contract type, locality, calendar month, and calendar year. Lower odds were observed among male teachers, principals, and teachers with provisional contracts, while temporal and territorial variation was observed across months, years, and localities. Conclusions: General illness-related sick leave among public school teachers in Bogota showed consistent sociodemographic, occupational, temporal, and territorial patterns. Respiratory and musculoskeletal conditions accounted for the largest share of episodes, while chronic, neoplastic, injury-related, circulatory, and mental health conditions were associated with longer durations. These findings provide population-level evidence to inform occupational health surveillance, seasonal preparedness, and workforce planning strategies within urban educational systems.

Introduction: Antimicrobial resistance poses a major global health threat, yet evidence on its economic impact in low- and middle-income countries remains limited. This study estimated the economic burden of infections caused by ESBL-producing Escherichia coli (E. coli), a key resistant pathogen, in Laos. Methods: A prospective cost-of-illness study was conducted among patients with laboratory-confirmed infections in Setthathirath hospital in Vientiane, Laos, collecting cost data through repeated interviews and medical records. Descriptive analyses and econometric modeling approaches, including inverse probability weighting (IPW) and instrumental variable (IV) analyses, were used to estimate out-of-pocket expenditures, public expenditures, total cost of illness, and length of stay, accounting for potential confounding. Results: ESBL-producing E. coli was consistently associated with higher economic burden across all analyses. The unadjusted per-patient cost was US$ 689.0 for ESBL-producing E. coli, compared with US$ 489.4 for non-ESBL-producing E. coli and US$ 537.6 for non-E. coli. The association remained statistically significant for out-of-pocket cost after IPW-adjustment (US$156.2; 95% CI, 14.3 to 298.1; P = 0.03), while other outcomes were not statistically significant. Instrumental variable analyses showed consistent directional effects but with wide confidence intervals and no statistically significant differences. Conclusions: Findings suggest that ESBL-producing E. coli may be associated with increased economic burden in Laos; however, this association was not consistently statistically robust across analytical approaches. These findings suggest a potential economic impact of ESBL infection, although uncertainty remains regarding the magnitude of the effect. Strengthening antimicrobial stewardship, infection prevention and control, and improved diagnostic capacity remain essential to mitigate the potential AMR burden.

Background: Three San Francisco health system emergency departments have developed Geriatric Emergency Department (GED) models of care programs supporting and providing care for emergency department (ED) patients at risk for or living with dementia. Each system recognized: 1) the high proportion of older adult ED patients and those at risk for dementia, 2) the need to identify cognitive impairment in older adult ED patients, 3) the importance of developing approaches to connect older adult ED patients and their care partners with resources and diagnostic specialty services. Methods: We describe how each hospital adopted and implemented pragmatic GED models of care to support and improve care for ED patients at risk or living with dementia. We also report the proportion of ED encounters made by patients with dementia histories and the number of these reached by GED programs. Results: Three San Francisco hospitals (a tertiary care, critical access, and large integrated health system-community ED) independently implemented GED programs to support and enhance emergency care for patients living with dementia. Each uses screening and assessment tools to identify patients at risk for cognitive impairment. Each captures screening and assessment data to facilitate care and resources for post-discharge care, ensuring coordinated transitions and support for older adults. Programs varied by target patient population age and staff and resource allocation to support program goals. Site-specific pathways differed by location, patient populations, and support from geriatrics, emergency medicine, palliative medicine, neurology, psychiatry, pharmacy, referral processes, and/or pastoral care. Conclusions: Developing GED care interventions that facilitate care for patients at risk of or living with dementia is possible and sustainable when the pathway aligns with health system leadership goals through persistent value demonstration, communication, and promotion. Ultimately, developing and disseminating models of GED care is designed to address geriatric syndromes inclusive of dementia care through continuous quality improvement.

Occupational ocular injuries are a preventable yet neglected public health problem, particularly in low- and middle-income countries. Maintenance workers are exposed to diverse ocular hazards daily, yet compliance with protective measures is consistently poor. A descriptive cross-sectional study was conducted among 85 maintenance workers at the Maintenance and Essential Services Organization (MESO) of Kwame Nkrumah University of Science and Technology (KNUST), Ghana, recruited through stratified convenience sampling across seven occupational sections. A structured questionnaire assessed knowledge of ocular hazards and protective equipment, attitudes toward ocular safety, and safety practices. Data were analyzed using IBM SPSS version 26 (IBM Corp., Armonk, NY, USA); chi-square and Fishers exact tests assessed associations (p < 0.05). Participants were predominantly male (84/85, 98.8%), with a mean age of 44.5 {+/-} 10.4 years. Overall knowledge was good (mean 9.40 {+/-} 1.59 out of 11), but attitude and practice scores were average (2.78 {+/-} 0.92 and 3.27 {+/-} 0.93, respectively). Most workers correctly identified goggles and face shields as protective, but only about half recognized that ordinary sunglasses and spectacles offer inadequate protection. Although 97.6% (83/85) recognized the need for ocular protection, only 7.1% (6/85) reported consistent protective eyewear use, and fewer than half (45.9%, 39/85) had received formal ocular safety training. Routine general protective equipment use was significantly associated with ocular protection use (Fishers exact test, p = 0.011). Sand and dust particles were the leading causes of injury and only 25% (5/20) of injured workers sought formal care. Workers demonstrated good knowledge but poor attitudes and practices toward ocular safety, suggesting that knowledge alone does not translate into protective behaviour even within a relatively well-resourced institutional setting. Findings suggest that limited access to task-appropriate protective eyewear may represent an important institutional barrier. Institutional PPE supply and section-specific safety training are essential to bridge this knowledge-practice gap.

Background: Under the DRG/DIP payment reform, the cost structure and its driving factors for laparoscopic cholecystectomy (LC) in resource-limited plateau regions remain unclear. Methods: Based on a single-center cohort of 605 plateau LC patients from May 2020 to October 2025, natural log transformation was applied to total hospitalization costs. Pearson/Spearman correlation, multivariate linear regression (traditional clinical model vs system-driven model with year dummies), and quantile regression were used. Results: Mean hospitalization cost 8097.49+/-936.85 CNY, CV=11.6%, Gini=0.062, demonstrating high homogenization. Traditional six-variable clinical model yielded R^2=0.008 (F=0.78, P=0.587), no significant predictors. The system-driven model achieved R^2=0.143 (F=3.42, P=0.001), with year dummies as dominant predictors. The study proposes the SAO (System-Allocation-Outcome) paradigm to replace the traditional SPO framework.

Background: Evaluation of public health surveillance systems is a programmatic obligation but has largely been conducted as a periodic, externally commissioned activity requiring dedicated resources and additional data collection. India's Integrated Disease Surveillance Program (IDSP) generates continuous outbreak data through weekly reports but lacks a routine, embedded performance evaluation mechanism. This study assessed the quality of IDSP outbreak detection and response across multiple surveillance attributes and developed a weighted composite performance scoring framework using only routine program data. Methods: A cross-sectional evaluation study was conducted across 38 districts of Bihar using secondary data from IDSP Central Surveillance Unit weekly outbreak reports for 2016 - 2018 (n=559 outbreaks). Six surveillance quality attributes were assessed - timeliness, completeness, representativeness, relative sensitivity, acceptability and flexibility. A weighted composite performance scoring scale was developed using expert opinion-derived attribute weightages (n=25 experts). District-level scores were computed and scaled to 100. Results: Timeliness was the poorest-performing attribute, with fewer than 15% of outbreaks notified within 48 hours across all three years. Private sector participation was entirely absent - the acceptability score was 0 across all 38 districts for all three years. Completeness was the strongest attribute, exceeding 95% in all years. The mean composite score remained consistently low (23 - 27 out of 100) with widening inter-district disparity over time. Four districts (10.5%) scored 0 in all three years. Conclusions: This study presents a dynamic, routine-data-based composite performance evaluation framework for IDSP outbreak detection and response. The modular, configurable framework functions at any administrative level (from block to national) and is compatible with digital health information platforms, enabling continuous, embedded performance monitoring without additional data collection. The framework has been registered as an Intellectual Property with the Government of India. Keywords: Disease surveillance; IDSP; IDSR; performance evaluation; composite score; outbreak detection; timeliness; completeness; relative sensitivity; digital health

Cancer prevalence is distributed unevenly across regions and caused by the interaction of multiple risk factors. Previous studies focused on the use of global modeling techniques to predict cancer at the county level that overlooks important spatial differences. This study aims to develop geographically weighted machine learning models to predict cancer prevalence at the census tract level in the United States and identify local determinants of cancer burden. First, a scoping review was conducted to find a list of measurable drivers of cancer in the United States. Using this list, the data of these variables for 84415 census tracts were obtained from the Center for Disease Control and Prevention PLACES dataset and other publicly accessible resources. Then, several predictive models, including Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR), as well as Random Forest, XGBoost, and Deep Neural Network and their geographically weighted counterparts, were developed and compared using the Coefficient of Determination, Root Mean Square Error, and Absolute Error. Results presented that geographically weighted models outperformed other methods, and geographically weighted XGBoost achieved the strongest and most consistent overall performance with pseudo-R2 ranging between 0.89 and 0.98. Feature importance analysis of this model illustrated that most important cancer drivers changed location by location. Aged people, racial composition, preventative behaviors, and metabolic conditions such as diabetes, hypertension, and high cholesterol were determined as influential predictors, although their relative importance varied across regions. These findings revealed the value of localized models at a small geographic scale to identify regional cancer risk patterns and help the allocation of proper resources to hotspot areas. Keywords: Cancer prevalence, Census tracts, geographically weighted machine learning models, Deep neural network, XGBoost, Random Forest, Ordinary Least Squares, risk factor, determinant

Background Although often perceived as a technical tool, a data bank is fundamental for district performance management, facilitating integrated coordination, data consolidation, and routine information use for decision-making. However, implementation unfolds within hierarchical bureaucratic systems shaping authority distribution, workload allocation, coordination, and resource use. This study examines the political economy of institutionalizing a district-level health data bank in West Sumbawa District, Indonesia. Method A longitudinal qualitative case study was conducted in West Sumbawa District, West Nusa Tenggara Province, Indonesia, from November 2025 to March 2026 across three evaluation phases (baseline, midline, endline), involving 25 District Health Office (DHO) officers appointed to the Health Data Bank team, representing five organizational units, including the Secretariat, General and Human Resources Unit, and Public Health Division. Data were collected through participatory workshops, focus group discussions, in-depth interviews, observation, and document review, including official decrees, SOPs, meeting minutes, and implementation records, and analysed using Bossert's Decision Space Framework combined with a problem-driven political economy analysis examining how power relations, institutional norms, workload, resource support, and perceived incentives influenced whether technical reforms became operationalized in routine practice. Results The Health Data Bank progressed from strong institutional acceptance to structural formalization. Decision-making authority remained centralized within the Secretariat, enabling coordination but limiting distributed ownership. Resource constraints increased workload, concentrated in the Secretariat and division coordinators responsible for data consolidation and validation, without dedicated financing or staffing, despite improved analytical capacity. Accountability mechanisms were established through governance instruments, though enforcement and feedback loops remained underdeveloped. Data submission, validation, and use were not yet fully institutionalized, resulting in a gap between structural readiness and functional use. Conclusion Data institutionalization involves both technical and organizational processes, requiring collaborative negotiation of authority, workload, and resources. Continued attention to these factors will help structural formalization translate into sustainable operational outcomes.

Objective: The Brief-cope questionnaire explore coping behavior. However, the underlying factor structure remains a subject of ongoing debate. Exploratory factor analyses (EFA) conducted across different populations have identified factor solutions ranging from two to fourteen factors. As of yet, the underlying factor structure of the Brief-cope has not been investigated in patients with seropositive rheumatoid arthritis (RA). Therefore, the aim of this study was to explore the underlying factor structure of the Brief-cope in a German population of seropositive RA. Methods: 216 outpatients with seropositive RA completed the Brief-cope. An EFA with principal axis factoring and Promax rotation was conducted. Results: EFA indicated a five-factor solution. The five-factor solution explained 51.95% of variance. The identified factors were: (1) problem-focused coping (Cronbach's = .851), (2) emotion-focused coping ( = .754), (3) maladaptive coping ( = .747), (4) religious coping ( = .851), and (5) substance-use coping ( = .869). Conclusion: A five-factor solution provided the most appropriate representation of the underlying factor structure of the Brief-cope in patients with seropositive RA. This factor structure may serve as a suitable basis for future analyses of Brief-cope data in comparable RA populations.

Multi-Cancer Detection (MCD) tests can detect more than 50 different types of cancer using a blood test. Recently passed law in the U.S. guarantees that Medicare will pay for these tests when they are FDA approved and show evidence for clinical benefit. This manuscript provides estimates of the cost of MCD tests to Medicare under different assumptions of cost per test, eligibility, and screening uptake in the eligible population. This manuscript additionally estimates the cost of follow-up testing resulting from false positive results, which are considered avoidable costs caused by the screening test.

Infectious disease dynamics is a growing, interdisciplinary field that aims to advance the understanding of how infectious diseases spread and how to control them. Most trainees enter the field through established disciplines and assemble ad hoc training and experience in infectious disease dynamics. As such, expectations for doctoral training remain largely implicit and highly variable across institutions. Other fields have formalized training expectations though defined training competencies, which promote transparency and alignment across institutions without prescribing specific approaches to training or research. In this paper, we set out to define the core competencies that characterize doctoral-level expertise in infectious disease dynamics. We assembled a team of seven people at the University of Utah and drafted a competency set. We then validated the competency set with experts in the field using an e-Delphi process. We did not restrict participation by location, job title, or sector. We set an a priori threshold for consensus to 70% and sent out two rounds of surveys to experts, asking them to rank the competencies by order of importance. Our team initially generated a list of 13 proposed Cross-cutting, 24 Applied Modeling, 17 Data Science, and 16 Theory competencies. After completing two rounds of validation, we validated two tracks comprised of 7 Cross-cutting, 10 Applied Modeling, and 12 Theory competencies. This study represents the first structured effort to define doctoral-level competencies in infectious disease that can help guide curriculum development, comprehensive exam preparation, and trainee evaluation, while also supporting alignment between academic training and workforce needs.

Despite known carcinogenic properties, indoor tanning remains popular among young adults and may contribute to early-onset melanoma. Our study aims to compare early-onset melanoma incidence by state availability of tanning beds. We analyzed population-based melanoma incidence data (2019-2023) from the National Program of Cancer Registries and calculated Incidence Rate Ratios (IRR) using verified state-level quintiles of tanning bed availability. Overall, in the Midwest/South regions, melanoma incidence increased with greater tanning-bed availability, from 8.7 cases per 100,000 population in Quintile 1 to 14.8 cases per 100,000 population in Quintile 5 (IRR = 1.69; CI = 1.65-1.74). No such relationship was found in the Northeast/West regions. In conclusion, we found that in Southern and Midwest states, increased availability of tanning beds was associated with higher early-onset melanoma in non-Hispanic White males and females, in both metro and non-metro counties. Policies which reduce tanning bed availability in high utilization regions may have potential to reduce early-onset melanoma.

The prevalence of shift work-centric industries and the rise of flexible working render it crucial to investigate the health risks posed by unnatural patterns of work and sleep. Shift working in healthcare has been linked to emotional dysregulation, reduced alertness, and cognitive impacts, with Shift Work Disorder (SWD) classified as a circadian rhythm sleep-wake disorder in the DSM-5. These impacts have historically been attributed to schedule-related sleep disturbances; however certain individuals appear more acutely affected. One measure of individual inflexibility to altered routines is chronotype distinctness, an amplitude dimension of the Caen Chronotype Questionnaire (CCQ). Here, we use Structural Equation Modelling (SEM) to unravel the mechanisms by which sleep and chronotype distinctness govern the neuropsychiatric symptom profiles of a cohort of National Health Service (NHS) shift workers (n=102). We constructed a measurement model, extracting latent constructs from questionnaires for sleep disturbances (PSQI), chronotype distinctness (CCQ), mood disorder (MDQ), depression (PHQ8) and emotional reactivity (ERS), and cognitive assessments. Correlations were identified between constructs, then translated into two SEMs - day and rotating shifts respectively - with sleep and distinctness as predictors of detrimental effects. Models were tested for direct effects, significant paths, and overall model fit. We found that, whilst sleep governed fatigue-based symptoms in day-shift workers, chronotype distinctness determined the severity of adverse effects in rotating-shift workers, including mood disorders and cognitive impairments. We surmise that high chronotype distinctness should be considered a risk factor for adverse effects surrounding night and rotating-shift work, and that interventions should incorporate chronotype-specific remediation.

Background Decision-making in emergency services involving the allocation of scarce resources is a key challenge for large, complex organisations required to prioritise demand against multiple, often competing criteria. Emergency Medical Dispatch is a case in point, where Enhanced and Critical Care Teams (ECCTs) represent a scarce and lifesaving clinical resource. Despite its operational and system-level significance, the allocation of ECCTs remains under-researched. Methods We conducted a methodological development study using the P.A.T.H.S. framework (Participants, Artefacts, Transition Stages, Historicity, Setting). We designed and piloted this in our previous work under the 999 R.E.S.P.O.N.D. project, which examined the decision-making process for ECCT dispatch. We applied P.A.T.H.S. to 17 dispatch cases (comprising 100 decision-making episodes). We analysed five data sources: recordings of emergency calls and internal dispatch-related interactions, sequence-of-events records, policy documents, and ethnographic observations. A four-phase analysis--indexing & data mapping, transcription & coding, charting, and synthesising & outputs--was undertaken taking Interactional Sociolinguistics as the theoretical approach and methodology. Results P.A.T.H.S. enables the mapping of non-linear, multifactorial textual trajectories across human and non-human actors. The case example presented herein illustrates how information on key risk indicators (e.g. mechanism of injury) were often delayed, fragmented, or lost between the caller, call-handler, and written records. P.A.T.H.S. provides a framework and analytical tool capturing the textual trajectory of information flow, and trace how dispatch decision making unfolds. We subsequently developed a template and codebook for other researchers to further study complex decision making in multi-actoral systems using a textual trajectory approach. Conclusion This methodological development work demonstrates the potential of P.A.T.H.S. to capture and clarify complex decision-making processes. P.A.T.H.S. offers a practical and theoretically grounded framework for future research, training, and policy that addresses risk points in communication between oral and written forms among teams of actors, to support optimal deployment of scarce resources.

Objectives: Collaboration among health care professionals and the services they provide can be strengthen by interprofessional education (IPE). IPE can be implemented at the undergraduate level. Accordingly, the objective of the present study was to evaluate senior students' understanding of the terms interdisciplinarity and multidisciplinarity within the context of IPE. Methods: A retrospective cross-sectional study design was used. Students understanding of interdisciplinarity and multidisciplinarity was assessed through an assessment question completed by three consecutive cohorts of senior undergraduate dental students at the UBC Faculty of Dentistry between 2021/22 and 2023/24 (N = 177). Responses had a maximum of 100 words and were categorized into one of four predetermined themes: concordant knowledge (when both definitions were correct), discordant rhetoric (when both definitions were incorrect), switched ideas (when the definitions were reversed), and altered discourse (when the concepts of discipline and specialty were conflated). Descriptive and inferential statistical analyses were performed using SPSS Version 31. Results: Of the 177 students enrolled, 164 provided responses to the question on multidisciplinarity and interdisciplinarity: 60 students in 2021/22, 51 students in 2022/23, and 53 students in 2023/24; the mean age was 25 years and 88 were female. Of the four predetermined themes, 45.7% of responses reflected concordant knowledge, 15.9% discordant rhetoric, 18.3% switched ideas, and 20.1% altered discourse. The logistic regression analysis showed age associated with a higher probability of providing the correct definitions (adjusted OR = 1.39; 95% CI: 1.06 - 1.83; p = 0.017). Conclusions: Knowledge of interdisciplinary and multidisciplinary appeared to be retained by the majority of students. However, dental education programs, alongside other health professional training programs, should continue to incorporate interprofessional education through both didactic and experiential learning opportunities to equip students with the skills necessary to provide collaborative care in future practice.

Objectives: To describe age-group differences in inability to afford dental treatment and cost related dental delay, among the US community-dwelling population. Study design: Descriptive analysis of nationally representative survey data. Methods: Using nationally representative Medical Expenditure Panel Survey data (2018-2021), we examined trends in inability to afford dental treatment and cost-related dental treatment delays across four age groups (2-17, 18-39, 40-64, [&ge;]65 years). Weighted analyses accounted for the complex survey design; statistical significance was set at p<0.001. Results: Cost-related delays declined modestly from 2018 to 2021 but remained most prevalent among adults aged 40-64 (4.8% for ages 40-64, 3.4% for ages 18- 64, 2.2% for ages>65 in 2021; p<0.001). Conclusion: Middle-aged adults seem to experience delays due to cost, underscoring the need for dental coverage to expand dental coverage for this group and to reduce their out-of-pocket costs.

Background: Sepsis is a life-threatening condition triggered by infection and associated with dysregulated immune response of the patient followed often by multiorgan dysfunction or failure. In the clinical evolution of sepsis towards organ dysfunction, early initiation of a suited therapy significantly increases patient outcomes and reduces mortality rates. Since electronic health records provide data in a machine-readable format, this process could be supported by computerized systems. Methods: We developed an interoperable, time-sensitive CDSS that able to detect systemic inflammation and the different classifications of sepsis (bacterial/viral, suspected/proven, on admission/PICU acquired) in pediatric patients based on the analysis of routine clinical data. This application is provided as part of this publication as an open demonstrator (web application), and the usability and accuracy of the CDSS is shown by a retrospective creation of sepsis outcome labels for a routine data set of 4,655 pediatric patients. As a reference standard, the patients were manually assessed by blinded clinical experts. Results: In comparison with the reference standard, the CDSS achieved sensitivity of 96.9% (95% CI: 80.9-99.6%) and specificity of 99.1% (95% CI: 95.1-99.8%). In the context of a sepsis outcome labeling for 4,655 patients, the CDSS detected 4,342 episodes of inflammation of which 1,723 were classified as sepsis. Conclusions: We demonstrated that our routine-data based CDSS is able to perform a complex sepsis detection process with high diagnostic accuracy. Such CDSS with the ability to differentiate between SIRS, sepsis on admission, suspected and proven sepsis can prospectively support clinical management, monitoring and quality management.

Objective This study evaluated how well subjective life expectancy (SLE) predicts mortality and actual life expectancy (ALE), along with factors associated with inaccurate expectations. Methods Using panel data on approximately 2,000 individuals with up to 28 years of follow-up from a nationally representative sample of older Japanese adults, we examined relationships among SLE, actual mortality, and ALE by survival analysis. We also evaluated health and socioeconomic disparities using concentration indices and investigated factors influencing SLE and ALE discrepancies and focal-point (i.e. rounded or anchored estimates) and do-not-know responses. SLE was measured as a self-reported point estimate, whereas ALE mainly came from official records and family reports. Results SLE was significantly associated with both actual mortality and ALE, even after accounting for demographic and socioeconomic variables. Nonetheless, significant inaccuracies remain: approximately 59% of individuals surpassed their expected lifespan. SLE was positively associated with ALE; however, the association was inelastic. Women and those with higher education levels were more likely to outlive their SLE, whereas those in poorer health were less likely to do so. Higher education correlated with fewer focal point responses to the SLE question. Discussion SLE effectively predicts ALE; however, gaps are non-negligible and differ across gender and socioeconomic groups. Offering more precise data, such as sex- and age-specific remaining life expectancy, can enhance SLE formation and lead to more informed economic choices.

Within our synchronous, online global health-focused upper-level microbiology course, we find that students struggle to translate learning to real-world applications. For examples, consider the recent measles outbreaks and major events such as the COVID-19 pandemic, which prompt many questions about how basic microbiological information is used by public health professionals. To address these points, we created a simulation-based curriculum that places students in an action role during an infectious disease outbreak. Our stand-alone curriculum walks through a historical measles outbreak that introduces outbreak investigation, community communication, and how these depend on microbiological knowledge. By using breakout groups, students have an opportunity to decide classifications, public messaging, and intervention metrics. We provide students with an outbreak investigation reference worksheet and interweave breakout rooms with didactic vignettes covering background information while revealing actual responses to outbreaks in conjunction with data obtained by responding scientists. Students synthesize material and apply it in real-time - allowing them to exercise critical thinking while bolstering relevance of microbiology and public health to popular media.