Epidemiologia

Background: Maternal mortality remains a major global health challenge, disproportionately affecting black and Indigenous women. Hypertensive disorders of pregnancy and postpartum hemorrhage are the leading direct causes of maternal death. Artificial intelligence (AI) tools have emerged as potential strategies for predicting these complications, yet concerns persist about their equity and validation across racial groups. Methods: A rapid review was conducted in five databases, PubMed, EMBASE, Web of Science, Scopus and LILACS, to synthesize recent evidence on the use of AI for preventing maternal mortality due to hypertension and postpartum hemorrhage. Studies published in the last five years that included racial or ethnic data were selected and analyzed narratively. Results: Ten studies met the inclusion criteria, showing high predictive accuracy of AI models (AUROC often >0.95) for severe maternal outcomes. However, few models incorporated racial variables or underwent external validation in racially diverse or low-resource populations. Evidence suggests that unrepresentative datasets may perpetuate or exacerbate existing health inequities. Conclusions: AI demonstrates strong technical performance in predicting maternal complications but limited equity in application. Broader racial representation, external validation, and ethical governance are essential for ensuring that AI-based tools reduce rather than reinforce racial disparities in maternal mortality. Full article

Introduction: Cerebrovascular disorders are major contributors to maternal morbidity and mortality during pregnancy. In this nationwide study in Hungary, we evaluated the frequency of cerebrovascular diagnoses during first recorded pregnancies in a 17-year period. Material and Methods: In the framework of the NEUROHUN project utilising nationwide administrative healthcare data, we included women with at least one delivery and with at least one cerebrovascular diagnosis during their first pregnancies recorded between 2004 and 2020. To minimise the number of misclassified first pregnancies due to database limitations appearing towards the beginning of the database, trend analyses using linear regression models were restricted to the 2011–2020 period. Results: During first recorded pregnancies in the 17-year study time frame (n = 952,451), the frequency of ICD-10 cerebrovascular diagnoses was 0.17% (n = 1614), with an estimated overall prevalence rate of 169.4 per 100,000 women (95% CI: 161.4–177.9). Transient ischaemic attack (TIA) was the most prevalent specific diagnosis, with a rate of 72.7 per 100,000 (95% CI: 67.4–78.3). In a multiple linear regression model on the mean age at first recorded birth within 2004–2020, women diagnosed with a cerebrovascular disorder were, on average, 1.935 years older at the time of their first birth compared to those without a diagnosis (mean difference: 1.935 years; 95% CI [1.188–2.682], p < 0.001). This analysis, adjusted for calendar year trends between 2011 and 2020, suggests that higher maternal age is an important factor associated with these events. In a sensitivity analysis of the linear regression using the diagnoses of G45, I60, I61, I63, and I67 we found that the relationship between the presence of diagnosis and mean age remained significant in the case of G45, I63 and I67, but not for I60 and I61. In the logistic regression model, compared to the reference group of women < 25 years, the prevalence for all evaluable cerebrovascular diagnoses was significantly higher in the >34 age group, and was also significantly higher for TIA (G45) and cerebral infarction (I63) diagnoses in the 25–34 age group. The rate of cerebral infarction among cerebrovascular disorders showed an increasing trend towards higher maternal age (<25 years age group: 12%; 25–34 years age group: 16.5%; >34 years age group: 20.0%). Also, when compared to the reference category of diagnosed women < 25 years, the increase in the odds of cerebral infarction was significant at the 5% level among women > 34 years. In contrast, there was no increment in the proportion of intracranial bleedings at older age. Discussion and Conclusion: The prevalence of most cerebrovascular diagnoses increases significantly with higher maternal age. Allowing for the limitations of our study, we found that in a Central-Eastern European population, the prevalence of cerebrovascular diagnoses during first recorded pregnancies between 2004 and 2020 was 169.4 per 100,000 (0.17%), with TIA being the most common diagnosis in approximately one-third of cases. The rate of cerebral infarctions among cerebrovascular diagnoses was almost twice as high in those over 34 years of age compared to those below 25. The frequency of pregnancy-related ischemic strokes and cerebral haemorrhages in the Central-Eastern European population corresponds to published values. Full article

The National Special Pathogens System (NSPS) stratifies U.S. healthcare facilities by their readiness level to care for patients with high-consequence infectious diseases (HCIDs). While NSPS Level 1 and 2 facilities possess advanced biocontainment capabilities to care for patients for the duration of their illness, most U.S. hospitals fall under a NSPS Level 3 or 4 designation, with limited resources to manage patients with a suspected or confirmed HCID. However, emerging zoonotic threats like H5N1 underscore the need to bolster HCID preparedness across all NSPS Levels. Beginning in March 2024, the U.S. H5N1 outbreak has primarily impacted wild bird flocks, poultry, and cattle, along with some human infections. The continuation of this outbreak in wild and domesticated animals increases the likelihood of further human spillover and eventual viral evolution in human hosts. At the frontlines, rural farming communities are likely to be most affected, with potential outbreaks exacerbated by a lack of accessible NSPS Level 1, 2, or 3 facilities in these regions. Thus, strengthening the HCID preparedness of local NSPS Level 4 facilities is critical to preventing transmission, minimizing societal disruption, protecting communities and the healthcare workforce, along with ensuring an equitable, coordinated response to future emerging infectious disease threats. This manuscript explores the financial, societal and health system impacts of HCID outbreaks to delineate the necessity of strengthening the preparedness of NSPS Level 4 facilities. Full article

Between 2020 and 2025, Europe has faced multiple interacting public health threats shaped by and following the COVID-19 pandemic. Alongside COVID-19, the region experienced other infectious disease events, including monkeypox, measles resurgence, legionellosis and acute hepatitis of unknown origin in children. At the same time, non-communicable disease burdens, including obesity, type II diabetes mellitus, disruption of chronic disease care, mental health disorders and increased problematic digital use, intensified during and after the pandemic period. Antimicrobial resistance (AMR) remained a major cross-cutting threat because it undermines the effective treatment of infections and weakens emergency preparedness. This narrative review synthesizes peer-reviewed articles and selected reports from international organizations for the 2020–2025 period, using COVID-19 as the organizing context for examining interconnected infectious, chronic and system-level threats. Across these topics, recurring themes included vaccination gaps, fragmented surveillance, disruption of routine care, health system inequities, misinformation and insufficient preparedness for cross-border threats. The review supports integrated surveillance, continuity plans for essential services, stronger vaccination and risk-communication strategies and sustained AMR stewardship within a One Health framework. Coordinated action across public health, primary care, mental health and chronic disease policy is essential for future resilience. Full article

The COVID-19 pandemic disrupted diabetes care globally and created a complex bidirectional health crisis. Recent forecasting efforts using pre-pandemic data projected substantial increases in diabetes mortality through 2030, raising concerns about achieving Sustainable Development Goal (SDG) 3.4. However, these projections did not account for pandemic-related disruptions to health systems and chronic disease management. The newly released Global Burden of Disease (GBD) 2023 data, covering the pandemic period through 2023, now provide a comprehensive empirical reference for assessing COVID-19’s observed impact on diabetes trends. This perspective adopts a forecast reconciliation and interpretation approach by examining counterfactual pre-pandemic diabetes mortality projections alongside GBD 2023 data, thereby shedding light on how pandemic-era mortality diverged from pre-pandemic trajectories. Critically, we note that insulin-dependent diabetes mellitus (IDDM, Type 1) and non-insulin-dependent diabetes mellitus (NIDDM, Type 2) have distinct etiologies and pandemic vulnerabilities, a distinction this article addresses. The evidence is striking: by 2023, global diabetes deaths had already exceeded 2.0 million per year, surpassing the 2030 upper forecast bound of 1.91 million, seven years ahead of the forecast horizon. NIDDM was the primary driver, with deaths crossing 1.9 million per year in 2023. These findings underscore the urgent need to strengthen diabetes prevention and management strategies as the world recovers from the pandemic-era disruptions in health systems and chronic disease care. Full article

Background/Objectives: Vector-borne diseases (VBDs) remain a major global public health challenge, particularly in tropical and subtropical regions. In eastern Colombia, the department of Meta reports a high incidence of arboviral infections such as dengue, as well as parasitic diseases including malaria and leishmaniasis. This study aimed to conduct baseline entomological surveillance and molecular screening of Diptera vectors to detect the circulation of arboviruses and parasitic pathogens in two municipalities of Meta, Fuente de Oro and Vista Hermosa. Methods: Adult mosquitoes and sand flies were collected in both municipalities and identified primarily at the genus level, with Anopheles specimens identified to species level. A total of 790 insects were collected, of which 780 were processed in 148 pools and 10 were analyzed individually. Molecular detection of pathogens was performed using PCR and RT-PCR to screen for dengue virus (DENV) serotypes, Zika virus (ZIKV), Chikungunya virus (CHIKV), Oropouche virus (OROV), Plasmodium spp., and Leishmania spp. Results: DENV was detected in 34.8% (55/158) of the processed pools, with DENV-1 identified as the most prevalent serotype. Culex was the most abundant genus overall, particularly in Fuente de Oro, while Aedes predominated in Vista Hermosa. MIR estimates indicated higher molecular detection likelihood in Aedes compared with Culex. Plasmodium vivax and P. falciparum were detected in pools of Anopheles darlingi and Anopheles rangeli, respectively. No molecular evidence of Leishmania DNA was detected in Lutzomyia specimens, and no positive detections were observed for ZIKV, CHIKV, or OROV. Conclusions: The molecular detection of DENV and Plasmodium spp. in field-collected vectors provides valuable baseline evidence of pathogen circulation in Meta, Colombia. While the findings do not imply vector competence, they highlight the importance of sustained entomological surveillance to inform integrated vector control strategies and guide future studies incorporating species-level identification and longitudinal sampling in endemic regions. Full article

Introduction: Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with coronary artery disease (CAD), also known as ischemic heart disease (IHD), responsible for approximately 13% of global deaths in 2021. Studies applying machine learning (ML) and deep learning (DL) to heart disease classification have demonstrated promising results in risk prediction and feature extraction. Background/Objectives: In this study, we develop an AI/ML framework to predict and classify ischemic heart disease risk using publicly available datasets, the Framingham Heart Study and the Cleveland subset of the UCI Heart Disease dataset, along with explanations for how predictions were made by a process called SHAP (SHapley Additive exPlanations). Methods: We implemented a leakage-controlled machine learning pipeline that included data cleaning, stratified 80/20 train-test splitting, training-fold-only feature scaling and class balancing, 5-fold hyperparameter tuning, SHAP interpretability, and Brier score-based calibration assessment. Logistic regression, random forest, K-nearest neighbors, XGBoost, and a feedforward neural network were evaluated on the Framingham dataset and the Cleveland subset of the UCI Heart Disease dataset. Performance was assessed using accuracy, precision, recall, F1-score, Matthews correlation coefficient, AUROC, and Brier score. Results: After leakage-controlled evaluation, Framingham performance was more modest than in the preliminary analysis. Logistic regression achieved the highest AUROC on the Framingham dataset (0.7234), while random forest achieved the lowest Brier score (0.1750), and the feedforward neural network achieved the highest accuracy (0.7719). On the Cleveland subset, logistic regression achieved the strongest threshold-based performance (accuracy 0.8667, precision 0.8571, recall 0.8571, F1-score 0.8571, MCC 0.7321), whereas K-nearest neighbors achieved the highest AUROC (0.9531) and lowest Brier score (0.0942). SHAP highlighted systolic blood pressure, smoking status, and hypertension as influential predictors (Framingham) and number of major vessels, chest pain type, thallium stress-test result (thal; normal, fixed defect, or reversible defect), and age (Cleveland) as top predictors. Conclusions: Optimal model performance is dataset-dependent, and SHAP enhances clinical interpretability. Broader access to high-quality, de-identified medical data could accelerate reproducible ML research in cardiology. Full article

Introduction: This study quantifies excess mortality in Spain during and after the COVID-19 pandemic and assesses whether mortality levels are returning to pre-pandemic patterns. Methods: Expected mortality was estimated using stochastic forecasting models calibrated on pre-pandemic data (1990–2019) and compared with observed mortality over the period 2020–2023. The analysis relies on a multi-model framework including the Lee–Carter, Cairns–Blake–Dowd, and age–period–cohort models. Results: The results show a substantial excess mortality during the pandemic years, with the proportion of ages exhibiting punctual excess mortality increasing from around 65% before the pandemic to approximately 85% during 2020–2022. Excess mortality declined sharply in 2023, when indicators returned to levels comparable to those observed prior to COVID-19, suggesting a transition toward near-normal mortality. The Lee–Carter model showed superior short-term performance in detecting abrupt mortality deviations, while APC and CBD models captured longer-term structural patterns. Conclusions: These findings highlight the usefulness of multi-model stochastic approaches for monitoring excess mortality and assessing recovery trajectories following major epidemiological shocks. Full article

Background: The COVID-19 pandemic has been a global crisis, affecting healthcare systems and professionals worldwide. This study investigates the prevalence and factors associated with burnout and insomnia among Greek physicians affiliated with the Athens Medical Association after the acute phase of the COVID-19 pandemic. Methods: Data were collected through an anonymous online survey distributed to active physician members of the Athens Medical Association between 15 June 2023 and 15 July 2023. Burnout was assessed using the Maslach Burnout Inventory (MBI), and insomnia was assessed using the Athens Insomnia Scale (AIS). Descriptive, unadjusted, and multivariable analyses were performed. Results: A total of 1023 physicians participated. Insomnia (AIS ≥ 6) affected 83.0% of the participants. Based on standard MBI cut-offs, 52.4% had high emotional exhaustion, 35.9% had high depersonalization, and 39.2% had low personal accomplishment. In multivariable logistic regression, older age was significantly associated with lower odds of insomnia, while public-sector employment and high concern about future career consequences were associated with higher odds. In multiple linear regression models, a higher AIS total score was significantly associated with higher emotional exhaustion and depersonalization and with lower personal accomplishment. Conclusions: These findings suggest high rates of insomnia and burnout in this physician sample. Greater insomnia was significantly associated with less favorable scores across all three burnout dimensions. Younger age, public-sector employment, and higher concern about future career consequences were associated with insomnia. These findings should be interpreted as associations, rather than causal effects. Full article

Background: Hepatitis A (HA) and E (HE) represent a significant global health burden. Despite the development of effective vaccines against hepatitis A virus (HAV) and hepatitis E virus (HEV), outbreaks of acute HA and HE continue to occur worldwide. This study aimed to assess the seroprevalence of anti-HAV and anti-HEV IgG antibodies (Abs) in the population of Belgrade and to analyze their association with socio-demographic and clinical factors. Materials and Methods: A cross-sectional study was conducted on a sample of 2533 healthy volunteers in Serbia in May 2024. Participation was voluntary and web-based, leading to an overrepresentation of women and middle-aged adults, while children were underrepresented. Due to this non-probabilistic recruitment, the absolute seroprevalence estimates have limited generalizability to the entire population of Belgrade. Serum samples were tested for anti-HAV and anti-HEV IgG using commercial ELISA kits. The anti-HEV estimate is based on a single ELISA without confirmatory testing and should be interpreted with this limitation in mind. Statistical analysis included confidence interval estimation, chi-square tests, and Spearman’s correlation. Results: Overall seroprevalence was 20.5% (95% CI: 18.9–22.1) for anti-HAV and 22.6% (95% CI: 21.0–24.3) for anti-HEV. A strong, non-linear increase in anti-HAV seroprevalence with age was observed, rising sharply from 2.8% in the 18–29 group to 78.3% in those aged 70+. Anti-HEV seroprevalence also featured a significant positive correlation with age (rs = 0.99, p < 0.0001), increasing from 4.2% in children (1–17 years) to 49.2% in the 70+ group. Men had significantly higher anti-HAV seroprevalence than women (23.1% vs. 19.3%, p = 0.029). Individuals with a history of surgical interventions or blood transfusions had significantly higher odds of being anti-HEV positive (OR = 1.41, p = 0.0005). Vaccination coverage against HAV was low (1.8%), and Abs were detected in only 28.6% of vaccinated individuals. Conclusions: This study suggests high HEV seroprevalence and an age-polarized HAV seroprevalence in Serbia, indicating a significant shift in the epidemiological landscape while acknowledging the sampling and assay limitations stated above. The findings underscore a growing population susceptible to HAV and highlight the need for reinforced vaccination strategies, improved diagnostics, and targeted public health interventions. Full article

Background/Objectives: Understanding nutrient intake and diet quality in older adults is essential for promoting healthy ageing and quality of life. The aim of the study was to assess dietary intake and nutritional status in two age groups of older adults in Croatia (65–74 years and ≥75 years). Methods: A total of 786 participants aged 65 and older were included in this cross-sectional study. Data from the National food consumption survey (OC/EFSA/DATA/2017/01), based on the EU Menu methodology, were used. Data collection included a general questionnaire, the International Physical Activity Questionnaire, two 24-h recalls or food diaries, and anthropometric measurements. The effects of body mass index and physical activity level on dietary intake were analysed using a general linear model. Results: 21.5% of older adults in Croatia had a normal weight, while 78.5% of were classified as overweight or obese. Significant differences were recorded in energy and macronutrient intake between the two age groups. Body mass index was significantly associated with energy (kcal/day), fat intake (g/day), and intake of the meat, poultry, fish and eggs food group in the 65–74 year age group. In the ≥75 year age group, physical activity level showed an effect on energy, carbohydrates, and milk and dairy product intake. Intake of nutrient-dense foods and fluids was below recommendations in both observed groups. Conclusions: The study results, based on a representative sample, provide the first overview of the nutritional status of older adults in Croatia. These findings offer a foundation for public health initiatives and further research on the nutritional status of the older population in Croatia. Full article

Background and Objectives: New Caledonia, an archipelago in the South Pacific, experienced an unprecedented conjunction of prolonged border closure during the COVID-19 pandemic (2020 to 2022) and marked influence of the El Niño/Southern Oscillation (ENSO). This context provided a unique opportunity to explore how environmental drivers, island isolation, and socio-demographic factors interact to shape infectious disease dynamics. This study aimed to assess the respective and combined effects of climatic variability, travel restrictions, and socio-demographic factors on the dynamics of four priority infectious diseases. Materials and Methods: We retrospectively analysed data from 2017 to 2023 on four infectious diseases: leptospirosis, dengue, influenza, and hepatitis A (HAV). Satellite precipitation data and the Multivariate El Niño/Southern Oscillation Index (MEI) were used. Socio-demographic and economic variables were gathered. Statistical analyses employed descriptive analysis and Generalized Additive Mixed Models to evaluate the associations between climatic events, travel restrictions, and disease circulation using the communal level as a random effect and time (daily) as a spline effect. Results: We analysed 878 cases of leptospirosis, 165 of HAV, 6607 of influenza, and 7377 dengue cases. Influenza was associated with rainfall before lockdown (Odds Ratio (OR) 0.7, Confidence interval 95%, (CI95%), (0.6–0.8)) and disappeared during lockdown but resurged post-reopening losing its meteorological association. Dengue epidemics declined, coinciding with the Wolbachia program and border closure, and were associated with lower MEI (OR 0.78, CI95% (0.6–1) during the 2017 to 2020 period. HAV cases were correlated with the MEI (OR: 1.8, CI95% (1–3.3)). Leptospirosis cases were associated with cumulative rainfall (OR 1.12 (1.1–1.2)) and lower education (OR 1.04, CI95% (1–1.1)) and decreased with water supply (OR 0.7, CI95% (0.5–0.8)). Conclusions: Our findings highlight how climatic conditions, mobility restrictions, and socio-environmental inequities differentially shape infectious disease risks in island ecosystems. These results reinforce the need for integrated One Health surveillance that jointly addresses environmental change, social vulnerability, and infectious disease prevention. Full article

Background: Lebanon adopted the World Health Organization (WHO)’s regional strategic plan (2012–2020) to achieve measles elimination. We aimed to analyze WHO measles surveillance performance indicators to identify areas for improvement. Methods: We reviewed suspected measles and rubella cases notified to the national epidemiological surveillance program between January 2013 and December 2024. A suspected case was defined as any patient with a febrile maculopapular rash or considered clinically compatible by physicians. We assessed notification rates of discarded non-measles/rubella suspected cases, timeliness of investigations within 48 h, completeness of case investigations (demographic and vaccination data), and proportion of cases tested for measles/rubella. Mean proportions and standard deviations were calculated across years and provinces. Results: A total of 6581 suspected cases were reported, predominantly from hospitals (66%). Outbreaks occurred in 2013 (n = 1760), 2018–2019 (n = 1984) and 2023–2024 (n = 346). Outside outbreak years, the notification rate ranged between 0.7 and 1.8 per 100,000 population. Timely investigation was achieved in 72% (±30%) of cases, while adequate investigation reached 52% (±19%). Laboratory testing was performed in 62% (±16%) of cases. Conclusions: Surveillance in Lebanon showed suboptimal sensitivity, a high proportion of hospitalized cases, and variability in completeness of epidemiological and laboratory investigations. Strengthening outpatient reporting and continuous training of healthcare professionals are essential to improve surveillance performance. Full article

Background and Objectives: Community fluoridation is an effective public health measure for dental caries prevention; however, knowledge and risk perception vary. This study assessed knowledge, attitudes, and sociodemographic determinants related to community fluoridation. Materials and Methods: A cross-sectional study was conducted in May–June 2023 among 200 adults from Iași, Romania, using a self-administered questionnaire. Chi-square tests were applied. Results: Most respondents were familiar with fluoride (94%) and its protective role (91%), but fewer knew fluoridation methods (34%) or dental fluorosis (53%). Educational level was associated with awareness of water fluoridation (χ² = 32.219, p < 0.001), and gender with safety perceptions (χ² = 6.031, p = 0.049). Perceived toxicity was strongly associated with fluoridation safety attitudes (χ² = 29.116, p < 0.001). Conclusions: Although general awareness is high, understanding remains limited. Sociodemographic factors influence knowledge and risk perception, highlighting the need for targeted communication. Full article

Background/Objectives: Aim: Dental practice involves continuous exposure to saliva and blood, creating persistent opportunities for cross-infection if contaminated instruments are not processed correctly. This study aimed to evaluate dental students’ knowledge regarding blood-borne infections and infection prevention measures, and to compare knowledge levels according to academic year and sex. Materials and Methods: A structured questionnaire consisting of 21 single-best-answer questions was administered to 93 undergraduate dental students (Years I–VI) from the Faculty of Dental Medicine, “Gr. T. Popa” University of Medicine and Pharmacy, Iași, Romania. The questionnaire evaluated knowledge related to instrument classification, cleaning and disinfection procedures, sterilization parameters, autoclave monitoring tests, and storage conditions. Demographic data were also collected. Statistical analysis was performed using IBM SPSS Statistics version 31, and associations between responses and demographic variables were assessed using chi-square tests. Associations between responses and demographic variables (academic year and sex) were evaluated using chi-square tests (p < 0.05). Results: Most participants correctly identified several key steps in the instrument processing circuit, including the use of high-level disinfectant–detergent solutions (88.2%) and the need for disinfection followed by sterilization (76.3%). However, important knowledge gaps were identified regarding autoclave pre-use checks, correct sterilization temperatures and exposure times, recommended sterile storage periods, and the interpretation of sterilization monitoring tools such as type 5 chemical integrators, Bowie–Dick tests, and Helix tests. Knowledge levels differed significantly according to academic year (p < 0.05). Conclusions: Although overall awareness of instrument processing procedures among dental students was generally satisfactory, several inconsistencies were observed in critical technical aspects of sterilization and monitoring. These findings highlight the need for strengthened infection control education and repeated practical training to reduce the risk of cross-infection in dental practice. Full article

Background: Human visceral leishmaniasis remains a serious public health problem in Brazil, especially in the Northeast, where transmission persists in various vulnerable settings. Objective: This study aimed to assess temporal trends in the incidence of human visceral leishmaniasis in Maranhão, northeastern Brazil, with emphasis on social vulnerability and regional heterogeneity. Methods: We conducted an ecological, population-based study using confirmed cases of human visceral leishmaniasis reported in Maranhão from 2007 to 2024. Case data were obtained from the Brazilian Notifiable Diseases Information System, and population denominators were derived from national census counts and annual population estimates. Temporal trends in incidence rates were analyzed using joinpoint regression models, stratified by sex, age group, Social Vulnerability Index, and Health Regions. Results: A total of 7830 new cases of human visceral leishmaniasis were reported during the study period. Incidence showed a significant upward trend from 2007 to 2017, followed by a marked decline from 2018 to 2024. A heterogeneous pattern was observed in the average incidence rate of human visceral leishmaniasis across municipalities’ vulnerability categories, as measured by each subindex of the Social Vulnerability Index. Substantial regional heterogeneity was identified, with marked reductions in incidence in the Health Regions of Caxias, Timon, Barra do Corda, and Codó, whereas Santa Inês and Viana showed increasing trends. Conclusions: Despite the decline in incidence, human visceral leishmaniasis remains unevenly distributed throughout Maranhão. These findings underscore the need for geographically targeted interventions and the expansion of public health strategies aimed at preventing and controlling the disease. Full article

Background: Estimates of life expectancy of people with disabilities are scarce and tend to focus on individuals with specific diseases. The health conditions of people with disabilities are often very poor, which is reflected in their significantly lower life expectancy compared to the rest of the population. Objectives: This study aims to estimate the life expectancy of people with severe disabilities in Italy. Methods: Data from the 1999–2000 Health Interview Survey, linked to the register of causes of death up to 2012, were utilized for the purpose of this study. Survival was analyzed using a Weibull regression model. Hazard ratios for subjects with and without disabilities were employed to estimate the mortality risk among subjects with disabilities compared to all surveyed subjects. These ratios were then employed to construct a life table for people with disabilities by multiplying the death probabilities of the general population by the ratio. Results: The life expectancy at 15 years for people with disabilities was found to be 59.1 years for males and 66.2 years for females. The life expectancy (LE) gap between people with disabilities and the general population at 15 years was 6.6 years for men and 4.1 years for women. Conclusions: These findings provide reliable and robust information on the life expectancy gap between people with and without disabilities and can be used as a reference point when evaluating policies aimed at people with disabilities. Full article

The application of the Health Technology Assessment Regulation (HTAR) gives way to joint European work, such as the Joint Clinical Assessment (JCA). This requires the definition of a PICO (Population–Intervention–Comparator–Outcome) question representative of all the member states of the European Union. The key to answering the PICO will be the synthesis of evidence through direct comparisons when there are randomized clinical trials (RCTs) including the same comparators, and via indirect treatment comparisons (ITCs) when comparators differ across RCTs. The aim of this report is to provide a synthesized and clear methodological framework to guide those stakeholders involved in JCAs when interpreting the results of ITCs, including descriptions on: (1) assumptions associated with ITCs; (2) how to select the method for ITC; (3) strengths and limitations associated with the methods; and (4) basics for understanding the method for ITC. This methodological framework could help those health care institutions, patient associations, consumer organizations, health-related nongovernmental organizations, health technology developers, and healthcare professionals involved in JCAs to better understand ITCs and incorporate this evidence into decision-making. Full article

Background/Objectives: Bone fractures represent a growing public health concern worldwide, yet national epidemiological assessments remain limited in Brazil. Understanding temporal trends, demographic disparities, and geographic heterogeneity is essential to guide prevention, resource allocation, and trauma-care planning. To characterize the epidemiological profile of bone-fracture-related hospitalizations and mortality in Brazil between 2015 and 2024, analyzing trends by sex, age, fracture type, and geographic and ethnic distribution. Methods: An epidemiological, observational, descriptive, and population-based ecological study was conducted using Hospital Information System of the Unified Health System SIH/SUS and IBGE data. Hospitalization rates, case fatality rates (CFR), relative risks, odds ratios, and Years of Life Lost (YLL) were calculated. Temporal trends were evaluated using Annual Percent Change (APC). Results: Other limb fractures were the most frequent injuries, while femur fractures showed the highest lethality. Men had nearly twice the hospitalization rate of women, driven by high-energy trauma in adults aged 20–59 years, whereas women experienced a sharp increase in femur-fracture admissions at older ages. Skull, facial, and thorax/pelvis fractures contributed disproportionately to premature mortality. Marked geographic and ethnic disparities were observed, with higher burdens in the North/Northeast and predominance among Brown and Indigenous populations. Conclusions: Fracture-related hospitalizations in Brazil have increased consistently, with distinct epidemiological patterns across demographic and regional groups. These findings highlight the need for targeted prevention and improved trauma-care strategies. Full article