Frontiers in Public Health

Objectives: Heatwaves drive surges in acute care demand, yet heat-health action plans (HHAPs) lack tools to scale emergency care responses. This study validated a forecasting tool for heatwave-related emergency department (ED) demand across four clusters comprising the emergency care network of Ticino Canton, Switzerland. Methods: This retrospective, ecological, time-series study modeled daily mean temperature and ED presentations using a distributed lag non-linear model framework with autoregressive and calendar adjustment components. The model was trained on summers (June-August) 2016-2024 and tested on summer 2025, defining heatwaves as daily mean temperature >25 {degrees}C for [≥]3 consecutive days. Results: A non-linear temperature-demand association was shown across the clusters, with ED visits increasing at higher temperatures. Model fit varied across clusters (R2 0.389-0.672), and the reference model consistently outperformed naive baselines. During two heatwaves in 2025, prediction errors remained within acceptable ranges. Baseline demand, heatwave occurrence, and model performance varied substantially within the canton. Conclusions: These findings have implications for the design of HHAPs, suggesting that emergency care preparedness should rely on locally calibrated demand forecast rather than standardized activation protocols.

Background. Public-health use of influenza surveillance - situational awareness, planning for clinical surge, and issuing advisories or warnings - needs more than an accurate point estimate of next week's count. What matters operationally is whether a rise is caught early, whether the direction of change is right, and whether an alert threshold is about to be crossed, all with honest uncertainty. For such use a forecast must also respect reporting delay, later data revision, and the calibration of its prediction intervals. Using Japan's sentinel surveillance, we evaluated short-term probabilistic forecasts that respect the data release history, and we measured what adding other surveillance series contributes, focusing on the properties that matter for public-health decisions. Methods. The target was the number of influenza reports per sentinel site in each of the 47 prefectures. For each forecast we predicted, as quantiles, the value 1-4 weeks after the most recent observed week. We compared three models: a ridge regression trained jointly across prefectures; a gradient-boosting quantile regression (GBQR) that learns from many surveillance series; and their equal-weight combination on the log scale. Six seasons were used to develop the models. The 2025/26 season was held out as a temporal evaluation period after the specification was fixed; because its epidemic profile had already been seen, it is not a fully independent prospective test. We scored forecasts with the weighted interval score (WIS) and checked prediction-interval coverage. For the Japanese target series we used the value first published for each week; some auxiliary series were taken as retrieved and therefore include later revisions. Results. In 2025/26, the combination's WIS relative to a persistence forecast was 0.841, 0.811, 0.794 and 0.818 at horizons of 1-4 observed weeks - that is, 16-21% lower than persistence. Coverage of the 80% prediction interval was 79.7%, 77.1%, 74.5% and 75.1%, and of the 95% interval 94.3%, 93.4%, 92.6% and 91.8%. Adding auxiliary series improved the GBQR over the development period. However, on the original scale the combination's edge over ridge regression was not statistically clear, and in some low-level rising phases the combination did worse than ridge. Conclusions. Over the period studied, models that share information across regions scored better than a persistence forecast. For public-health use, however, the operative questions are the real lead time once reporting delay is accounted for, whether rises from low levels and threshold exceedances are caught in time, and whether the upper prediction intervals are wide enough; on these, the present evidence is not yet sufficient. The 2025 change to the sentinel system also means that pre-change advisory and warning thresholds cannot be read mechanically. A prospective evaluation with strictly controlled data availability is needed before such forecasts are used to support advisories or planning.

Abstract Objective To estimate the burden and patterns of multimorbidity and cardiometabolic multimorbidity among university employees undergoing a comprehensive health assessment programme, and to examine demographic and behavioural factors associated with multimorbidity. Design Cross-sectional study. Setting A public university in Maharashtra, India. Participants A total of 266 university employees who underwent a comprehensive health assessment were included. Main outcome measures Multimorbidity was defined as the presence of two or more of nine chronic conditions: hypertension, diabetes mellitus, dyslipidaemia, ischaemic heart disease, chronic kidney disease, thyroid disease, stroke, chronic obstructive pulmonary disease and cancer. Cardiometabolic multimorbidity was defined as the presence of two or more of hypertension, diabetes mellitus, dyslipidaemia, ischaemic heart disease and chronic kidney disease. Results Hypertension was identified in 119 participants (44.7%), comprising 50 participants with pre-existing hypertension and 69 newly identified during the assessment. Dyslipidaemia was present in 189 (71.1%) and diabetes mellitus in 45 (16.9%). Overall, 108 participants (40.6%) had multimorbidity and 103 (38.7%) had cardiometabolic multimorbidity. The prevalence of multimorbidity increased progressively with age, from 17.5% among participants aged <30 years to 83.3% among those aged [&ge;]60 years. The predominant exact multimorbidity patterns were hypertension with dyslipidaemia alone (49 participants) and hypertension, diabetes mellitus and dyslipidaemia (27 participants). Overall, 173 participants (65.0%) had at least one newly identified hypertension, diabetes mellitus or dyslipidaemia diagnosis. In multivariable logistic regression, age (adjusted OR [aOR] 1.058 per year, 95% CI 1.027 to 1.091), BMI (aOR 1.163 per kg/m2, 95% CI 1.076 to 1.257) and tobacco use (aOR 3.296, 95% CI 1.377 to 7.888) were independently associated with multimorbidity. The model had an area under the receiver operating characteristic curve of 0.731. Conclusion Multimorbidity affected approximately two in five university employees, with cardiometabolic conditions accounting for most of the observed disease clustering. Comprehensive health assessment identified a substantial burden of previously unrecognised chronic disease. Integrating institutional or occupational health assessment with longitudinal primary care follow-up may provide an opportunity for earlier detection, risk-factor modification and coordinated management of multimorbidity. Keywords: Multimorbidity; cardiovascular diseases; hypertension; diabetes mellitus; dyslipidaemia; occupational health; university employees; India

Introduction: Lichen sclerosus (LS) is a chronic inflammatory dermatosis predominantly affecting the anogenital region of both women and men. Sexual dysfunction remains among the most debilitating and overlooked consequences of the disease, as available patient-reported outcome measures are either restricted to one sex or capture sexual health only partially. The aim of the present work is to validate the Qualisex questionnaire (in its the Italian version) in patients with LS and to evaluate its psychometric properties, factor structure, convergent, discriminant validity, and sex symmetry. Methods: A cross-sectional study was conducted on 211 patients (167 women, 44 men; mean age 52.9 years) with a confirmed diagnosis of LS. Participants completed the Italian Qualisex, Skindex-29, DASS-21, and sexual-health-specific scales, the Female Sexual Function Index (FSFI) for women, and the International Index of Erectile Function (IIEF) for men. Construct validity was assessed via Principal Component Analysis (PCA), and reliability via Cronbach's alpha. Convergent and discriminant validities were evaluated against standard psychometric batteries. Results: Item 2 was removed due to low communality (0.167). PCA on the remaining 9 items revealed a two-factor structure accounting for 72.5% of total variance: Component 1 (Sexual Functioning and Satisfaction, 59.89%) and Component 2 (Partner Devaluation, 12.66%). Internal consistency was high (alpha= 0.911 overall; alpha= 0.841 in women; alpha= 0.899 in men). Qualisex scores correlated strongly with Skindex-29 Social Functioning (r = 0.582) and Emotions (r = 0.531) subscales, as well as FSFI (r = -0.391) and IIEF (alpha= -0.566). Discriminant validity was supported by low-to-moderate correlations with DASS-21 domains (r < 0.38). While FSFI and IIEF showed significant negative correlations with age (p = 0.002), Qualisex remained age-independent across sexes (p > 0.05). Conclusion. The 9-item Italian Qualisex is a reliable, sex-symmetrical, and age-independent patient-reported outcome measure for assessing sexual health impairment in LS, successfully isolating disease-specific distress from physiological aging and general distress.

Purpose: The internship period is a critical stage for nursing students to develop professional values. This study aimed to investigate the current status of professional identity among nursing interns, analyze the effects of social support, perceived stress, psychological resilience, and career adaptability on professional identity, and explore the mediating role of career adaptability between social support and professional identity, so as to provide empirical evidence for enhancing professional identity and optimizing nursing talent training systems. Methods: Using convenience sampling, 407 nursing interns from a tertiary hospital in Quanzhou were selected as participants from May to July 2025. Data were collected using a general information questionnaire, the Social Support Scale, the Perceived Stress Scale, the Psychological Resilience Scale, the Professional Identity Questionnaire for Nursing Students, the Career Adaptability Scale, and the Questionnaire for Nurse Intention to Retention Employed. SPSS 26.0 was used for reliability analysis, descriptive analysis, independent samples t-test, one-way ANOVA, Pearson correlation analysis, and multiple linear regression analysis. The PROCESS macro was employed to test the mediating effect. Results: The total score of professional identity among nursing interns was (61.74{+/-}11.08), with 73.5% showing moderate professional identity. Parents' attitude toward nursing, reasons for choosing the profession, personal attitude toward the major, and employment intention showed statistically significant differences in professional identity scores (p<0.05). Pearson correlation analysis revealed that professional identity was significantly positively correlated with social support (r=0.474), psychological resilience (r=0.389), and career adaptability (r=0.609) (p<0.01), and significantly negatively correlated with perceived stress (r=-0.378) (p<0.01). Multiple linear regression analysis indicated that career adaptability ({beta}=0.309, p<0.001) and social support ({beta}=0.383, p<0.001) were significant positive predictors of professional identity, whereas reasons for choosing the profession ({beta}=-3.603, p=0.001) and employment intention ({beta}=-7.116, p<0.001) were significant negative predictors. The model explained 49.2% of the variance in professional identity. Mediation effect analysis showed that career adaptability played a partial mediating role between social support and professional identity, with a mediation effect value of 0.288 (95% CI: 0.221-0.363), accounting for 40.2% of the total effect. Conclusions: Nursing interns' professional identity is at a moderately high level. Social support and career adaptability are positive influencing factors. Career adaptability plays a partial mediating role between social support and professional identity; social support indirectly enhances professional identity by strengthening career adaptability.

Introduction:Although the COVID-19 pandemic clearly showed the potential consequences of a world without vaccinations, vaccine hesitancy is likely to be more pronounced in the post-COVID-19 era. The introduction of human papillomavirus (HPV) vaccines in this context is likely to raise particular concerns. In Tunisia, decision-makers have prioritized the introduction of HPV vaccine into the immunization schedule. This study assessed individual barriers and facilitators to HPV vaccine acceptability in Tunisia, with the aim of guiding an effective communication strategy for HPV vaccination campaigns in Tunisia and neighboring countries in a post-pandemic context.Methods: Using a qualitative design, we conducted 14 focus groups (FG) with healthcare professionals (HCP) (N=32) and community representatives (CR) (N=89) in five regions of the country. The discussion followed a semi-structured guide designed on the basis of vaccine hesitancy determinants matrix. Transcripts were deductively analyzed according to the 'social processes' and 'thinking and feeling' of the behavioural and social drivers (BeSD) Framework. Inductive approach was used to analyze participants suggestions for promoting HPV vaccination.Results:The FG analysis demonstrated that the historically strong trust in vaccination in Tunisia has weakened after the COVID-19 pandemic. Mistrust of health system and experts, the pandemic management and vaccine mandates measures had negative influence on the vaccine attitudes in a post pandemic Tunisian context. Persistent concerns about COVID-19 vaccines safety were frequently intertwined with widespread distrust of pharmaceutical companies and their profit motives, perceived as imposing inequitable access and lower-quality vaccines on countries in the Global South. These concerns fueled confusion about vaccines side effects. The weakening of immunity was recurring, as well as memory issues, impacts on fertility, and sudden deaths. Regarding information, our research revealed that although digital platforms were perceived as widely used, a significant part of the population interviewed considered public TV channel, as the most reliable source of health information.Conclusions: Emphasizing how the pandemic has shaped individual and collective perceptions and attitudes toward vaccination, our findings underline the importance of leveraging lessons learned from the pandemic to develop a context tailored and coherent communication strategy for successful HPV vaccine implementation.

Background: Hypertension (HTN) and Type 2 diabetes mellitus (T2DM) are leading drivers of the global cardiometabolic disease burden and major contributors to preventable morbidity and mortality. In Hong Kong, where population ageing and lifestyle-related risk factors are increasingly prevalent, both conditions and their complications pose substantial challenges to the healthcare system. Although territory-wide prevalence figures are available, small area district-level evidence on the burden of these diseases and their associated complications remains limited. Disparities are likely due to heterogeneity in demographic composition, socioeconomic status, and primary care accessibility across Hong Kong's eighteen administrative districts. There is also a lack of accessible, age-adjusted, district-level disease visualization in Hong Kong. Objectives: This study estimates the age-standardized prevalence rates (ASPR) of HTN, T2DM, and their associated complications across the eighteen districts of Hong Kong, formally evaluate the statistical significance of inter-district disparities, and rank the districts according to disease burden to inform place-based health planning. Methods: This study analyzed the prevalence of chronic diseases from 2014 to 2023 in 18 districts among an adult cohort aged equal or above 35 years using data collected from the Hong Kong Hospital Authority (HA) electronic health records, using the International Classification of Diseases, Ninth Revision (ICD-9) diagnostic codes, the International Classification of Primary Care (ICPC) codes, and the disease flags to identify diseases. Sample weights are used to reflect the total population. HTN, T2DM, and their major complications were identified according to standardized diagnostic criteria. ASPR were calculated for each district with the WHO World Standard Population as the standard. Inter-district disparities in disease prevalence were assessed using Cochran's Q test, with statistical significance set at P <0.05. The slope index of inequality (SII) was also used to analyze the socioeconomic inequality between districts. Districts were subsequently ranked according to their ASPR for each condition to identify high-burden and low-burden areas. Results: 1,756,521 patients (52.71% females) contribute 9,906,729 patient-years from 2014 to 2023. Substantial inter-district variation and increasing trend were observed in the ASPR of HTN, T2DM, and their complications. The weighted ASPR of HTN varied by 27.3% from 46,701 (95% CI: 45,691-47,711) per 100,000 population in Tsuen Wan district to 59,445 (95% CI: 58,759-60,130) per 100,000 population in Yuen Long district, and the weighted ASPR of T2DM ranged from 20,464 (Tsuen Wan, 95% CI: 19,803-21,124) per 100,000 population to 28,275 (Yuen Long, 95% CI: 27,792-28,758) per 100,000 population across the districts in 2023. All diseases showed district disparities (all P <0.05). Cochran's Q test demonstrated statistically significant disparities across districts and showed no convergence through the period. The SII test also showed the most serious inequality exists in HTN, with the lower socioeconomic position districts have more burden. Conclusion: Significant geographic disparities exist in the prevalence of HTN, T2DM, and their complications across Hong Kong's eighteen districts. These findings highlight the need for district-specific public health strategies, equitable allocation of primary care resources, and targeted chronic disease prevention and management programs in high-burden areas.

Objectives: A previously published conceptual mapping review integrated fragmented evidence on dental anxiety (DA) into a broader conceptual model of potential causes and consequences. This study focused on consequences, extending from oral health-related behaviours through oral disease to systemic health, and empirically evaluated these hypothesized relationships on the population level. Methods: Cross-sectional data from the 46-year follow-up of the Northern Finland Birth Cohort 1966 (n = 1,859) were analysed using structural equation modelling. DA was modelled as a latent construct; delayed/problem-oriented dental attendance and home oral care as behavioural proxies; periodontal disease burden as the percentage of sites with probing pocket depth >=4 mm; and cardiovascular risk as a Framingham-based risk score. Generalized anxiety, sex, and education were covariates. Smoking-stratified multigroup analyses assessed model robustness. Results: The prespecified associations were observed across behavioural, periodontal, and systemic-risk domains. Higher DA was associated with more delayed/problem-oriented attendance and poorer home care; both were associated with greater periodontal disease burden, which in turn was associated with higher cardiovascular risk. Model fit was good (chi-square(119) = 529.98, CFI = 0.962, TLI = 0.951, RMSEA = 0.043, SRMR = 0.051). The overall association between DA and cardiovascular risk was small (beta = 0.066, p = .004), with a small decomposed indirect association (beta = 0.013, p = .006) and a remaining direct association (beta = 0.053, p = .022). Smoking-stratified multigroup comparisons found no differences in the structural associations by smoking status. Conclusions: This population-based evaluation provides preliminary empirical support for the conceptual model. Findings extend the relevance of DA beyond dental attendance and oral health outcomes to a broader oral-systemic public-health context. Cross-sectional data cannot establish temporal or causal ordering; longitudinal replication is needed.

Abstract Background: In Pakistan approximately 7 million people were living with diabetes in 2014. To address the burden of diabetes, a randomized controlled trial was conducted to evaluate the effectiveness of a standardized care package in improving diabetes outcomes in health care settings of Punjab, Pakistan. A costing study was embedded within this RCT to estimate the cost-effectiveness of the standardized diabetes care package in improving diabetes outcomes. Methods: 166 patients were recruited for the costing study from 14 public health clusters in Sargodha district of Pakistan. Analyses was conducted using the societal perspective, broader societal perspective and sensitivity analyses to explore the uncertainty in analyses. Data was analysed for both 166 participants enrolled in costing study and for the 495 participants recruited in the cRCT, using multiple amputations. Results: Using the societal perspective, standardized diabetes care package was found to be cost-effective as compared to the standardized care and was cost saving as the costs in the intervention arm were lower than those in the control arm whereas greater effects were demonstrated in the intervention arm. As per the broader societal perspective and the healthcare perspective only, the standardized care package was not proven to be cost-effective. Keywords: Diabetes management, health services cost, out of pocket cost, cost-effectiveness.

Automated surveillance systems can prove to be extremely useful in detecting outbreaks of respiratory diseases that need further epidemiological investigation. In order for the system to be effective, careful attention has to be paid to the baseline used, absence of the observations, and the use of proper statistical methods. As a solution, the paper describes EpiAlert, a weekly surveillance system based on CDC FluView ILINet. The system is able to transform the number of ILI visits and the total number of visits into a ILI prevalence for the region, create the first reference from the three previous years using a +/- 2-week interval, transform the rate value, and apply two different detectors - CUSUM and EWMA. CUSUM is set at k=0.5 and h=5, whereas EWMA uses {lambda}=0.2 and H=2.7 values. Among the 55 districts, the system gives 45,138 pieces of information about the disease by transforming 44,297 pieces of data into alerts. It is found that there are 2,820 alerts in total (out of which 2,711 alerts used CUSUM, 402 used EWMA, and 293 used both detectors). Additionally, the experiments show that the sensitivity of the device depends greatly on the detector. The latest statistics can be tracked in the report for week 37 of 2026 that recently concluded in West.

Background Chronic diseases are the leading causes of illness, disability, and death worldwide, with a disproportionate burden in low- and middle-income countries. Hospitalization is a critical outcome in chronic disease management, reflecting disease severity, treatment failure, and healthcare utilization. However, data on hospitalization burden and its associated factors among chronic disease patients in Ethiopia, are limited. This study aimed to determine the rate of hospitalization and its associated factors among patients with chronic diseases attending a tertiary hospital in Wolaita Zone, South Ethiopia. Methods A facility-based cross-sectional study was conducted among 321 patients with chronic diseases attending the chronic follow-up clinic at Wolaita Sodo University Comprehensive Specialized Hospital from November to December 2022. Consecutive recruitment was used, with unique medical record numbers tracked to prevent double recruitment. Data were collected through structured questionnaires and medical record review. Negative binomial regression was used to identify factors associated with hospitalization rate, with incidence rate ratios (IRR) and 95% confidence intervals (CI) reported. A p-value < 0.05 was considered statistically significant. Results Of the 321 participants, 66% reported at least one hospitalization while on treatment, with a mean of 1.70 {+/-} 1.81 hospitalizations per patient. Drug discontinuation was the most frequently documented reason for hospitalization (39.5%), followed by disease complications (22.3%) and infections (11.7%). Multimorbidity was prevalent, with the majority (59.8%) had 2-3 conditions, and a mean of 2.40 {+/-} 1.02 chronic diseases per patient. Male sex was associated with a higher hospitalization rate, while regular physical exercise was associated with a lower number of hospitalizations. Conclusion This study found a high burden of hospitalization among chronic disease patients, with drug discontinuation being the leading documented reason. Male sex and regular physical exercise were significantly associated highlighting the need for medication adherence support programs and structured exercise programs integrated into routine chronic disease care, as well as gender-sensitive interventions.

Abstract Background: Cyprus has transitioned into a high-alert zone for mosquito-borne viruses. This necessitates a proactive assessment of its future physicians. Following the 2022 re-establishment of Aedes aegypti in Larnaca and Aedes albopictus in Limassol, Cyprus, the island is now biologically primed for local outbreaks of dengue, Zika, and chikungunya, alongside Culex-borne West Nile virus. The study assessed medical students' knowledge and risk perception. Methods: A cross-sectional online survey administered the validated MosquitoWise Health Belief Model instrument to undergraduate-entry and graduate-entry students at a university in Cyprus in mid-2026. Results: Of 1023 students, 119 responded (11.6%), with pre-clinical students overrepresented (p<0.001). Mean knowledge was 5.43/9, stronger on mosquito biology (72.5%) than virus knowledge (54.2%). Median severity was 6.00/7 against susceptibility 4.25/7. Knowledge differed by study stage (p<0.001), correlated with severity (rs = 0.399) but not susceptibility. Conclusions: The study establishes a critical baseline for pre-clinical medical students in Cyprus. Overall, participants performed better on mosquito biology when compared to mosquito-borne viruses and how they spread. Our findings highlight the value of integrating theoretical microbiology with clinical practice in medical education to enhance physicians' preparedness for the changing landscape of newly emerging infections in Cyprus and across Europe as a whole. Key Words: Arboviruses, Cross-Sectional Studies, Cyprus, Health Belief Model, Medical Students, Risk Perception.

Background: Antimicrobial resistance (AMR) is a growing global health threat, and India's high antibiotic consumption makes public knowledge, attitudes, and practices (KAP) a critical determinant of stewardship outcomes. Existing Indian KAP evidence is drawn from small, localised cohorts, leaving a gap in nationwide, digitally-sourced data. This study aimed to describe antibiotic-related knowledge, attitudes and self-reported practices among users of a digital healthcare platform in India, examine demographic and regional variation, and identify potential areas for future stewardship interventions. Methods: A cross-sectional survey was conducted among adult users of the Tata 1mg platform (December 2025-February 2026), with participants invited via an in-app banner. Knowledge and attitude were each scored on a 0-4 scale (4 items); practice was scored as a percentage of applicable items answered favourably, with scoring adjusted for branching logic based on antibiotic-access route. Of 10,726 respondents who started the survey, 4,883 completed it (45.5%). City of residence was mapped to one of six regions (India's five statutory Zonal Council zones plus a North-Eastern region) for 4,187 respondents. Associations with demographic characteristics were assessed using multivariable linear regression, and regional differences were assessed using one-way ANOVA. A parallel survey of 256 physicians was conducted to enable patient-provider comparison. Results: Mean scores were: knowledge 2.28 (SD 1.19), attitude 0.91 (SD 1.14), practice 44.9% (SD 33.4); attitude, not knowledge, was the weakest domain. Older age was associated with higher scores across all domains (practice: B=12.52, p<0.001 for age [&ge;]65 vs. 18-34); city tier was independently associated with lower knowledge and attitude (Tier 3 vs. Tier 1: p=0.010 and p<0.001, respectively). Regional differences were non-significant for knowledge and practice but significant for attitude (F=2.56, p=0.026, ^2=0.003), driven by lower scores in the North-Eastern region. In the parallel physician survey, 55.5% of respondents estimated that more than half of their patients self-medicated before consultation. Conclusion: In this platform-based sample, attitudes were the weakest domain, not knowledge, and 42.0% said their last antibiotic did not come on a doctor's recommendation. The findings may inform digital stewardship touchpoints, such as point-of-purchase guidance and prescription verification, in line with India's National Action Plan on Antimicrobial Resistance 2.0. As a cross-sectional survey of platform users, it cannot establish the relative contributions of knowledge, beliefs and access pathways to antibiotic use.

Background: COVID-19 vaccination uptake is influenced by various sociodemographic and psychological factors. Previous studies have suggested that the relationship between personality traits and vaccination is context-dependent. However, this association has not been investigated in Japan, a unique sociocultural context characterized by historically low vaccine confidence but exceptionally high COVID-19 vaccine uptake. We examined the association between the Big Five personality traits and completion of the primary COVID-19 vaccination series, exploring potential gender-personality interactions. Methods: A web-based, cross-sectional survey was conducted among 7,210 Japanese adults (aged 20-85 years) in December 2021. Personality was assessed using the Japanese version of the Ten-Item Personality Inventory. Multivariable Poisson generalized estimating equations were used to calculate adjusted prevalence ratios (PRs) and assess gender-personality interactions. Results: Higher extraversion and lower openness were significantly associated with vaccination completion across genders. A significant gender-agreeableness interaction was observed: agreeableness (PR = 1.016, 95% CI: 1.008-1.024) was positively associated with vaccination completion among men but not women. A similar, though only marginally significant, interaction pattern was observed for neuroticism (PR = 1.011, 95% CI: 1.004-1.019 among men). Conclusions: Personality traits act as modest but meaningful, gender-specific psychological modifiers of vaccination behavior in Japan. Public health campaigns should transition from traditional "one-size-fits-all" messages to personality-tailored and gender-responsive communication strategies to optimize vaccine uptake and bolster psychological resilience in future pandemics.

Electronic health record foundation models are traditionally trained on the scale of years, days, or hours. These timescales, however, lack the minute-scale resolution required to directly guide clinical decisions at the bedside. We introduced minute-scale learning, a new paradigm for training and evaluating models, and developed MINT, a minute-scale foundation model for pediatric emergencies. MINT was pretrained and validated on 766,733 pediatric emergency department visits at five health systems, comprising 16 years of data from 10 hospitals. On minute-scale forecasting tasks, MINT outperformed and generalized to external health systems better than task-specific models (superior in 21 of 25 comparisons). MINT outperformed physicians in forecasting escalations of respiratory support. MINT demonstrated uniquely minute-scale capabilities including department-scale monitoring, dynamic risk explanations, individualized physiologic response forecasts, and hypothesis generation. Learning at the minute-scale improves performance, strengthens generalizability, and provides insights, actionability, and scientific capabilities that are not accessible at other timescales.

Abstract Background: Rising global temperatures are intensifying exposure to extreme heat, yet access to air conditioning (AC) remains unequal which leaves vulnerable populations without protection against the heat. Household survey data on AC ownership is scarce in low- and middle-income countries limiting the ability to identify areas of cooling gaps. Methods: In this study, we develop a geospatial machine learning framework that integrates household data from the Demographic and Health Surveys (DHS) program with high resolution climatic, socioeconomic and demographic covariates to generate a 5km resolution prediction of AC ownership across low- and middle-income countries in Africa and Asia for the year 2023. Results: The resulting map reveals strong spatial inequalities with high predicted prevalence in wealthier and urban regions, and near zero prevalence across much of Central and West Africa and rural areas. These patterns reflect the adaptation cooling gap where those most exposed to extreme heat are least able to adapt through access to cooling. Conclusion: By producing the first continental-scale, high resolution map of AC ownership, this study lays the foundation for designing and targeting equitable cooling strategies, support heat-health planning particularly in communities most affected and informing sustainable energy policy.

To deal with the COVID-19 pandemic, Denmark implemented an aggressive program aimed at controlling the pandemic which included both testing and contact tracing programs. The large amount of data collected in Denmark on the pandemic and its integrated nature made it possible to investigate the effectiveness of the testing and contact tracing effort. The results of that investigation and a discussion of the effectiveness and limitations of the different control efforts are reported herein, as are lessons learned concerning possible improvements for the future. The analysis is limited to the period from the start of the COVID-19 pandemic in Denmark (late Feb. 2020) into May 2021, at which time the impact of vaccination intervention was already playing a role with ~25% of the Danish population at least partially vaccinated. From the available data sets we estimate the national Infection Detection Efficiency (IDE) starting around July 1, 2020, the time at which the national infection detection program started to be implemented in a more robust form. The results rely on daily COVID-19 hospital admissions, PCR test results, and anti-body prevalence values for the Danish population. We find that for the long-term average, the combined Danish national testing and contact tracing program identified on average about 55 to 60% of the infected individuals during the period from Sept. 1, 2020, into early May 2021. However, higher infection detection efficiencies were achieved in localized areas for short time intervals. Our investigations further indicate that the Danish testing and contact tracing program, which was among the most ambitious in the world, could have had a better balance between voluntary probing on the one hand and focused contact tracing and targeted testing on the other hand. As typically implemented, it proved to be largely ineffective in controlling the pandemic. However, in at least one case when it was implemented in an enhanced and focused mode, it was able to bring a large local outbreak that dominated the country's cases under control. We have compiled a list of lessons learned regarding the use of contact tracing procedures to control potential future pandemics before vaccinations become available.

Background: Multiple factors can drive heat susceptibility, but are typically analyzed individually. This study investigates high-dimensional heterogeneity across multiple domains in the effect of hot days on emergency hospitalizations across German districts. Methods: We obtained emergency hospitalization rates per 1,000 in 3-day windows for the summers of 2005-2023 from the German Diagnosis-Related Groups-Statistic, linked with spatio-temporal temperature information. A hot day was defined as at least one day above the district-level 98th percentile heat index. Multiple characteristics of the demographic, health/social, and environmental domains were selected as potential effect modifiers. We implemented a generalized random forest, where outcome and propensity scores were modeled with fixed effects estimators to control for seasonality and district-level confounding. We divided the conditional average treatment effects (CATE) into quartiles to map their spatial distribution and identify key effect modifiers via the variable importance and observed indicator profiles across quartiles. Results: We found substantial variation across districts regarding heat-related emergency hospitalizations. The top three indicators for predicting this effect heterogeneity were the percentage of people seeking protection, population below age 6, and air pollution levels. The observed indicator profile for the most susceptible districts was characterized by a larger percentage of vulnerable populations, higher car density, and fewer hospital beds. Conclusion: There is substantial variation in heat susceptibility across and within districts in Germany. We propose an approach that can help understanding such complex interplay of indicators from different domains driving heterogeneity.

BackgroundIn rural Alaska, where most communities lack road access, air ambulances serve as a critical link between remote communities and hospital services. ObjectiveTo examine how air ambulance utilization decisions are made within the rural Alaskan health organization ecosystem. MethodsWe conducted semi-structured interviews with five key stakeholders. Transcripts were analyzed thematically using the Practical, Robust Implementation and Sustainability Model (PRISM). ResultsFour themes emerged that collectively define the structure of the air ambulance decision-making system, each reflecting interactions across multiple PRISM domains: limited formal guidance, logistical constraints affecting transport options, variability driven by communication and clinician risk tolerance, and reliance on unwritten rules. Together, these describe decision-making in a limited information state with incomplete feedback, leading to experiential and locally evolved practices. ConclusionAir ambulance use reflects clinical-logistical constraints rather than critical illness alone. Linking transport decisions to outcomes and developing structured decision support may improve consistency and optimize care delivery.

Infectious disease forecasting supports public health preparedness and response by informing resource allocation, intervention planning, and situational awareness. Infectious disease forecasting capabilities in the United States have grown over the past decade yet whether forecast quality has improved over this time remains unclear. Current evaluation metrics describe relative performance for a common set of forecast targets but cannot evaluate performance across different outcomes, seasons, and pathogens. We addressed this challenge by developing a novel skill score metric to assess forecasts based on performance relative to two benchmark models: a hindcast as an idealized upper bound of performance and a baseline model as a minimal performance standard. To study the impact of the baseline choice, we considered three types of baseline models with varying levels of complexity. Using this skill score framework, we retrospectively evaluated short-term influenza (influenza-like illness and hospitalization) and COVID-19 (case, death, and hospitalization) forecasts, focusing on how the performance of team and multi-model ensemble forecasts changed over time. The ensemble outperformed 99% of forecasts from a simplistic, naive baseline, and 84-91% of forecasts from more complex baseline models that incorporate recent data. We found consistent improvements in ensemble and team forecast skill over time for both influenza forecast targets, with 4-week horizon forecasts in the most recent year having higher skill scores than 1-week horizon forecasts in the first year of each challenge. Results were mixed for COVID-19 forecasts. This framework provides a comprehensive picture of progress in infectious disease forecasting over the past decade enabled by improved standardization, data, models, and collaboration.