To analyse trends and characteristics of multidrug-resistant (MDR) bacteria over the past 7 years, in relation to patterns of antimicrobial use, to inform rational antimicrobial use and strengthen hospital infection control measures.

Retrospective cohort study.

A large teaching hospital in Tianjin, a major metropolitan city in northern China.

A total of 190 352 inpatients aged >18 years, admitted between 1 January 2017 and 31 December 2023, were included. Patients were eligible if they had complete clinical data and met the five quality control indicators for multidrug-resistant bacteria (QC-MRB), defined in the ‘Hospital Infection Surveillance Specifications’ (WS/T 312–2023). Patients with MDR infections before admission or those with duplicate results from multiple specimens were excluded.

Statistical analysis revealed a detection rate of 12.11% for the five QC-MRB and an incidence rate of 0.20%. The findings also indicated an upward trend in the detection and incidence rates of carbapenem-resistant Enterobacteriaceae, despite a relatively stable rate of antimicrobial use over 7 years. A positive correlation was observed between the incidence of MDR bacteria and the intensity of antimicrobial use within the hospital setting.

The hospital’s bacterial data align with national trends. It established an interdisciplinary management framework for clinical data analysis and prediction of antimicrobial resistance. This approach enhances infection control measures and supports the rational use of antimicrobials.

Our primary objectives were (1) to develop and validate an administrative data algorithm for the identification of hand trauma cases using clinical diagnoses documented in medical records as the reference standard and (2) to estimate the incidence of hand trauma in a universal public healthcare system from 1993 to 2023 using a population-based research cohort constructed using a validated case identification algorithm.

A population-based retrospective validation study.

Ontario, Canada, from 2022 to 2023 (validation) and from 1993 to 2023 (estimation).

Our reference standard was the known hand trauma status of 301 patients (N=147 with hand trauma) who presented to an urban tertiary-care hand trauma centre in Toronto, Ontario.

(1) The sensitivity, specificity, positive and negative predictive values of the optimal algorithm to identify hand trauma using provincial health administrative data and (2) age-standardised and sex-standardised incidence rates of hand trauma among men and women, by age, and by area of patient residence.

The optimal algorithm had a sensitivity of 73.8% (95% CI 66.6% to 81.0%), specificity of 80.1% (95% CI 73.8% to 86.5%), positive predictive value of 78.1% (95% CI 71.2% to 85.0%) and negative predictive value of 76.1% (95% CI 69.5% to 82.7%). Over the study period, the age-standardised and sex-standardised incidence of hand trauma increased from 384 to 530 per 100 000. The greatest increase was observed in males and individuals aged 0–19 and 80+, with higher incidence rates in Southern compared with Northern Ontario.

Our algorithm enabled identification of hand trauma cases using health administrative data suitable for population-level surveillance and health services research, revealing a rising burden of hand trauma from 1993 to 2023. These findings can support improved surveillance, resource allocation and care delivery for this public health problem.

We aim to use an agent-based model to accurately predict the spread of COVID-19 within multiple US state prisons.

We developed a semistochastic transmission model of COVID-19.

Five regional state-owned prisons within North Carolina.

Several thousand incarcerated individuals.

We measured (1) the observed and simulated average daily infection rate of COVID-19 for each prison studied in 30-day intervals, (2) the observed and simulated average daily recovery rate from COVID-19 for each prison studied in 30-day intervals, (3) the mean absolute percentage error (MAPE) of each prison’s summary statistics and the simulated results and (4) the parameter estimates of key predictors used in the model.

The COVID-19 pandemic disparately affected incarcerated populations in the USA, with severe morbidity and infection rates across the country. In response, many predictive models were developed to help mitigate risk. However, these models did not feature the systemic factors of prisons, such as vaccination rates, populations and capacities (to determine overcrowding) and design and were not generalisable to other prisons.

An agent-based model that used geospatial contact networks and compartmental transmission dynamics was built to create predictive microsimulations that simulated COVID-19 outbreaks within five North Carolinian regional prisons between July 2020 and June 2021. The model used the characteristics of an outbreak’s initial case size, a given facility’s capacity and its incarcerated vaccination rate as additional parameters alongside traditional susceptible-exposed-infected-recovered transmission dynamics. By fitting the model to each prison’s data using approximate Bayesian computation methods, we derived parameter estimates that reasonably modelled real-world results. These individualised estimates were then averaged to produce generalised parameter estimates for North Carolina state prisons overall.

Our model had a mean average MAPE score of 23.0 across all facilities, meaning that it reasonably forecasted facilities’ average daily positive and recovery rates of COVID-19. Our model estimated an average incarcerated vaccination rate of 54% across all prisons (with a 95% CI of ±0.12). In addition, the prisons of this study were estimated to be operating at 90% of their capacity on average (95% CI ±0.16). Given the high levels of COVID-19 observed in these prisons, which averaged over one-third positive tests on respective 1-day maxima, we conclude that vaccination levels were not sufficient in curbing COVID-19 outbreaks, and high occupancy levels likely exacerbated the spread of COVID-19 within prisons.

In addition, data gaps in facilities without recorded daily testing resulted in poor spread predictions, demonstrating how important consistent data release practices are in incarcerated settings for accurate tracking and prediction of outbreaks.

The findings of this study better quantify how spatial contact networks and facility-level characteristics unique to congregate living facilities can be used to predict infectious disease spread. Our approach also highlights the need for increased vaccination efforts and potential capacity reductions to mitigate COVID-19 transmission in prisons.

Delays in cancer diagnosis for patients with non-specific symptoms (NSSs) lead to poorer outcomes. Rapid Diagnostic Clinics (RDCs) expedite care, but most NSS patients do not have cancer, highlighting the need for better risk stratification. This study aimed to develop biomarker-based clinical prediction scores to differentiate high-risk and low-risk NSS patients, enabling more targeted diagnostics.

Retrospective and prospective cohort study.

Secondary care RDC in London.

Adult patients attending an RDC between December 2016 and September 2023 were included. External validation used data from another RDC.

The primary outcome was a cancer diagnosis. Biomarker-based risk scores were developed using Latent Class Analysis (LCA) and Least Absolute Shrinkage and Selection Operator (LASSO). Model performance was assessed using logistic regression, receiver operating characteristic curves (AUROC) and decision curve analysis.

Among 5821 RDC patients, LCA identified high white cell count, low haemoglobin, low albumin, high serum lambda light chain, high neutrophil-to-lymphocyte ratio, high serum kappa light chain (SKLC), high erythrocyte sedimentation rate (ESR), high C-reactive protein (CRP) and high neutrophils as cancer risk markers. LASSO selected high platelets, ESR, CRP, SKLC, alkaline phosphatase and lactate dehydrogenase. Each one-point increase in score predicted higher odds of cancer (LCA: AOR 1.19, 95% CI 1.16 to 1.23; LASSO: AOR 1.29, 95% CI 1.25 to 1.34). Scores ≥2 predicted significantly higher cancer odds (LCA: AOR 3.79, 95% CI 2.91 to 4.95; LASSO: AOR 3.44, 95% CI 2.66 to 4.44). Discrimination was good (AUROC: LCA 0.74; LASSO 0.73). External validation in 573 patients confirmed predicted increases in cancer risk per one-point LASSO score rise (AOR 1.28, 95% CI 1.15 to 1.42), with a borderline increase for LCA (AOR 1.16, 95% CI 1.06 to 1.27).

Biomarker-based scores effectively identified NSS patients at higher cancer risk. LCA captured a broader biomarker range, offering higher sensitivity, while LASSO achieved higher specificity with fewer markers. These scores may also help detect severe benign conditions, improving RDC triage. Further validation is needed before broader clinical implementation.

Growing evidence suggests that vaccines targeting respiratory pathogens have non-specific and broader effects. We aimed to investigate the non-specific effects of respiratory vaccines on acute lower respiratory infection (ALRI) hospitalisations and associated outcomes in children

Systematic review and meta-analysis.

We searched online databases including Medline, Embase, CINAHL, Scopus and Clinical Trials.gov from inception to 24 January 2024.

We included human studies involving non-specific/off-target effects of respiratory vaccines (including maternal, infant and childhood vaccines) and excluded studies investigating the Bacille Calmette-Guérin vaccine and non-pathogen-confirmed outcomes following pneumococcal conjugate vaccination (PCV).

We used Research Screener, a machine learning tool, to semi-automate the abstract screening process and Covidence, a management and streamlining software for full-text reviews and data extraction. A meta-analysis was conducted if four or more studies reported on the same outcome and the same exposure vaccine.

After removing duplicates, 9727 articles were identified. After screening and full-text reviews, 20 articles were eligible. Of those, four met the requirements for a meta-analysis which showed a 21% vaccine effectiveness (VE) (95% CI 8.0% to 32.0%) of maternal influenza vaccine against all-cause ALRI hospitalisations in infants

Our review demonstrated both protective and neutral non-specific effects of respiratory vaccines against ALRI-hospitalisations and related outcomes in young children. Such effects should be considered as part of the full value of a vaccine and how vaccine investments are prioritised. Further research on the impact of respiratory vaccines on antibiotic prescribing rates is essential as consistent reductions may help contribute to reducing the global burden of antimicrobial resistance.

CRD 42023476038.

The purpose of this study was to assess changes in diabetes management and healthcare utilisation among First Nations with diabetes in Alberta before and during the COVID-19 pandemic.

This analysis used a retrospective cohort in a case–control design. Individual-level administrative health datasets (1 April 2018 to 31 March 2022) were linked and data were formatted as a segmented interrupted time series.

This study took place in Alberta, Canada using administrative data.

Adult First Nations and non-First Nations (matched 1:1) with diabetes and living in Alberta were included (n=28 101; 53% female, 47% male).

The primary outcome was the change in incidence rate of general practitioner (GP) visits, emergency department (ED) visits, hospitalisations and diabetes-related drug dispenses during-COVID-19 versus pre-COVID-19, quantified using generalised linear regressions. The secondary outcome was to report the reasons for non-drug outcomes pre-COVID-19 and during-COVID-19, based on primary diagnosis International Statistical Classification of Diseases and Related Health Problems codes.

Pre-COVID-19, baseline rates of GP visits, ED visits, hospitalisations and drug dispenses were significantly higher among First Nations compared with non-First Nations (rate differences 398.32 (391.97–404.67), 100.58 (98.32–102.84), 14.49 (13.56–15.43), 876.98 (868.72–885.24) per 100 person-years (PY); p

Healthcare utilisation was substantially elevated among First Nations compared with non-First Nations peoples before and during COVID-19. While the generalisability of our findings to other health systems and populations may be limited, our findings are clinically applicable among First Nations across Alberta in order to help direct public health programming post-COVID-19.

To determine the survival rate and prognostic factors associated with tuberculosis (TB) mortality in Medellín between 2018 and 2023.

Quantitative observational analytical study of a retrospective cohort.

Based on notifications made to the Public Health Surveillance System and managed by the Secretary of Health of Medellín—Colombia between 2018 and 2023.

A total of 11 202 individuals diagnosed with TB, aged between 1 and 103 years.

The Kaplan-Meier method was employed to determine survival and risk functions, as well as median survival. Crude HRs and adjusted HRs (aHRs) were estimated using Cox proportional hazards regression models.

A median overall survival of 1410 days (3.86 years) and an adjusted mortality rate of 40 cases per 100 000 population were estimated for the study period (6 years). Factors associated with TB mortality were age (>59 years) (aHR 5.53; 95% CI 3.17 to 9.65), renal disease (aHR 2.98; 95% CI 2.27 to 3.90), HIV infection (aHR 2.82; 95% CI 1.39 to 3.32) and cancer (aHR 2.56; 95% CI 1.95 to 3.34).

TB survival is influenced by age and comorbidities, indicating the need for targeted strategies to protect high-risk groups. Strengthening comprehensive TB control through timely diagnosis, integrated management of chronic conditions and patient-centred care is essential to reduce preventable deaths. Furthermore, improving case notification and follow-up through integrated information platforms will contribute to more effective public health interventions.

Epilepsy prevalence varies widely across Nigeria, with rates ranging from 3.1 to 37.0/1000 population. There have been no studies on epilepsy prevalence and treatment gap in the Northeast Region of Nigeria. This study aimed to study epilepsy prevalence and the epilepsy treatment gap (ETG) in an urban and a rural community in Northeast Nigeria.

Cross-sectional, community-based survey.

Epilepsy screening of residents in two communities in Northeast Nigeria using a WHO screening tool and a validated study questionnaire from 1 March to 10 June 2022.

8599 community residents aged ≥2 years.

Prevalence of epilepsy, active epilepsy, ETG and associated factors.

We screened 8599 residents, of whom 88 had epilepsy. Crude epilepsy prevalence was 10.2 per 1000 and was three times higher in the rural than in the urban community (18.5 vs 6.4; ²=26.79, p2=0.087, p=0.768). Logistic regression analysis showed that the ETG was associated with a lack of counselling (OR 15.8, 95% CI 3.5 to 70.7, p

The prevalence of epilepsy in Bauchi State was within the range reported in Nigeria but three times higher in the rural than in the urban community. A high ETG was associated with poor counselling of people with epilepsy. Epilepsy counselling, health education and wider access to neurology services could reduce the burden of epilepsy in Northeast Nigeria.

To systematically summarise and evaluate the existing evidence of the associations between diverse folate exposures and the risk of colorectal cancer (CRC), while identifying evidence quality.

Umbrella review of meta-analyses.

PubMed, Web of Science, Cochrane and Embase were searched from the database inception to March 2024, with an update to 12 October 2025.

We included meta-analyses of randomised controlled trials or observational studies that investigated the associations between folate exposures and CRC or precancerous lesions (ie, adenoma and polyps).

For each association, we recalculated the summary effect size with 95% CI using the DerSimonian and Laird random-effects model, heterogeneity (I² statistic), 95% prediction interval, small-study effect (Egger’s test) and excess significance bias (² test).

This umbrella review included five meta-analyses describing 10 associations between folate exposures and CRC risk. In the general population, moderate-quality evidence supported an inverse association between total folate intake (from foods and supplements) and CRC risk (RR 0.84; 95% CI 0.80 to 0.90), while low-quality evidence suggested inverse associations of dietary folate intake (from foods alone) (RR 0.88; 95% CI 0.81 to 0.96) and folic acid supplement intake (RR 0.83; 95% CI 0.77 to 0.90) with CRC risk. Among patients with inflammatory bowel disease, low-quality evidence suggested an inverse association between folic acid supplement intake and CRC incidence (HR 0.71; 95% CI 0.53 to 0.96). Additionally, elevated circulating folate levels were observed to have a provoking effect on advanced-stage tumours (OR 1.95; 95% CI 1.18 to 3.22; Grading of Recommendations Assessment, Development and Evaluation (GRADE): very low). Sensitivity analysis revealed a potential increased risk of adenoma recurrence associated with folic acid supplement use among patients with a history of adenoma (RR 1.05; 95% CI 0.86 to 1.29; GRADE: high).

These findings suggest that consuming dietary folate and total folate intake may be beneficial in CRC primary prevention. Specifically, folic acid supplements may inhibit colorectal carcinogenesis in normal tissues while promoting cancer in the established neoplastic foci.

CRD42024537550.

The main objective of the Health Survey of São Paulo or Inquérito de Saúde de São Paulo (ISA) in Portuguese, is to generate health indicators to support research and policy planning. The ISA-Physical Activity and Environment Longitudinal Study has the primary objective of examining built and social environmental determinants of leisure-time physical activity and active transportation.

The baseline (2014–2015) study included 4042 participants aged 12 years and older, men and women, living across the five regions of São Paulo city. Data were collected through household interviews. The second wave (2020–2021) used telephone interviews and included 1434 participants aged 18 or older, 58.6% female and representing 35% of the baseline sample. The third wave (2023–2024) included 1583 participants through household or telephone interviews, 58.6% of female and represented 39% of the original cohort.

The study has collected extensive individual-level data, including physical activity behaviours, health status and related behaviours, self-report of diseases and sociodemographic characteristics; built environment features such as public open spaces, transport infrastructure, schools and healthcare facilities, walkability index, sidewalks, traffic control and social environment features, such as crime occurrence and socioeconomic index. Analyses have identified changes in the built environment and their associations with physical activity and obesity. Infrastructure improvements, such as the increase of bike paths and outdoor gyms, have been more frequent in wealthier areas, reinforcing spatial inequalities. Increased availability of public open spaces has been associated with increased leisure-time walking. Obesity has shown a growing trend, particularly among specific sociodemographic groups, while physical activity has demonstrated protective effects against obesity. Cycling for transportation has remained stable over time, with disparities by gender and physical activity status.

The plan is to conduct the fourth wave in 2026 and 2027 and the fifth wave in 2029 and 2030.

To estimate the sociodemographic and geographical variation in prescribing selective serotonin reuptake inhibitors (SSRIs) and medications for attention-deficit/hyperactivity disorder (ADHD) to children and young people (CYP) in North West London, UK.

Cross-sectional population-based study.

General practices in North West London, UK, with data for the period 2020–2022 obtained from the Discover Now platform, which covers approximately 95% of the local population.

762 390 CYP aged 5–24 years in the year 2022.

Primary outcome: Prescription rates of SSRIs and ADHD medications. Secondary outcomes: Associations between prescription rates and sociodemographic factors, including age, gender, geographical area (local authority), ethnicity and socioeconomic deprivation (measured using the Index of Multiple Deprivation).

The total sample comprised 762 390 CYP. 2.20% of the sample were prescribed an SSRI (95% CI 2.17% to 2.24%) and 0.50% an ADHD medication (95% CI 0.49% to 0.52%) in years 2020–2022. High deprivation was associated with the highest rates of an SSRI prescription (2.5%). In contrast, low deprivation was associated with the highest rates of an ADHD medication prescription (0.70%). This divergent pattern was evident in some London boroughs and not in others. The relationship between level of area deprivation and prescription rates also differed by borough. Overall, the sociodemographic factors could not explain most of the variation in prescription rates (Pseudo R² 0.18 for SSRI and 0.06 for an ADHD medication).

Prescriptions for common mental disorders and ADHD for CYP from North West London varied by sociodemographic characteristics and London borough of residence, potentially exacerbating mental health inequalities. To monitor and address these inequalities, more extensive use of linked electronic health records should be undertaken; for example, data on mental health diagnosis and service utilisation are needed to investigate the relationship between diagnosis and treatment over time.

Childhood cancer survivors (CCSs) experience educational disruptions during and following treatment, yet robust, longitudinal evidence on educational performance remains limited. We will investigate differences in educational outcomes between CCSs and non-cancer peers during primary and secondary school. We will also explore how sociodemographic factors and age at diagnosis contribute to potential differences in General Certificate of Secondary Education (GCSE) examinations, a critical indicator of future academic and employment prospects.

We will use the Education and Child Health Insights from Linked Data (ECHILD) to capture linked health and education data for children born in National Health Service (NHS)-funded hospitals in England. We will generate birth cohorts spanning September 1997 to August 2015 (estimated sample size: ~10 million), formed of pupils expected to have undertaken national curriculum assessments between academic years 2004/2005 and 2021/2022 including Key Stage (KS) 1, 2 and 4, corresponding to ages 7, 11 and 16 respectively. Cancer diagnosis will be identified from inpatient hospital records, using International Classification of Diseases, 10th Revision codes (ICD-10). We will investigate differences between CCS and their non-cancer peers in terms of their sociodemographic characteristics and describe trends in educational performances at all KSs, recorded Special Educational Needs and Disabilities (SEND) and school absences. Differences in KS4 (GCSE) performances between CCS and non-cancer peers will be quantified, according to and accounting for geographic region, sex, deprivation, ethnicity and birth characteristics. To assess whether cancer diagnosis disrupts academic trajectories, we will restrict analysis to those with KS2 attainment data and investigate KS4 performance. We will finally explore the influence of age at diagnosis on educational performance at KS4.

Ethics approval was granted by NHS Health Research Authority Research Ethics Committee (20/EE/0180). Findings will be shared with academics, policymakers, children and families affected by childhood cancer, and published in journals. Code/metadata will be shared on ECHILD GitHub repository.

The aim of this study was to assess the incidence, prevalence and mortality of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) in Lithuania.

Retrospective cohort study.

Lithuanian National Health Insurance Fund and Causes of Death registries, covering 1 January 2012 through 31 December 2021.

Patients were identified from national healthcare registries in Lithuania. The following inclusion criteria were applied: 1) diagnosis of eosinophilic granulomatosis with polyangiitis (EGPA), granulomatosis with polyangiitis (GPA) or microscopic polyangiitis (MPA) (diagnosis codes M30.1, M31.3 and M31.7, according to International Classification of Diseases 10^th version (ICD-10)) recorded between 1 January 2012 and 31 December 2021; 2) diagnosis of AAV was recorded in the database at least twice with at least 1-month period between the two timepoints; 3) a record of at least once prescribed reimbursed medication—glucocorticoids (prednisolone or methylprednisolone), conventional synthetic disease-modifying anti-rheumatic drugs (methotrexate, azathioprine, hydroxychloroquine and cyclophosphamide) or biological disease-modifying anti-rheumatic drug (rituximab or available biosimilars); and 4) age >18 years at the time of diagnosis.

Data for the analysis included sex, age, ICD-10 code of AAV, the first date of AAV diagnosis and date of death. The study period was subdivided into periods 1 (2013–2015), 2 (2016–2018) and 3 (2019–2021). Temporal trends of the incidence of AAV were assessed. Point prevalence data were recorded. Sex- and age-standardised mortality ratios (SMRs) were calculated. The life expectancy of patients with AAV was estimated by standard single-decrement life-table analysis.

We identified 236 patients with AAV (female, 58%) with an annual incidence of 8.22 per 1 000 000 adult inhabitants (period 1, 9.83; period 2, 6.88; period 3, 7.95). Increasing incidence was noted for MPA (period 1, 0.9; period 3, 2.49). The incidence of GPA (4.89 per 1 000 000 inhabitants per year) was three times higher than the total incidence of EGPA and MPA. The prevalence of AAV per 1 000 000 adult population increased from 35.92 in 2015 to 69.14 in 2021. 40 deaths were recorded during the study period, with a mean age at death of 65.2 (±13.03). AAV was associated with reduced life expectancy compared with the general population, especially when diagnosed at a young age. The SMRs for the total AAV cohort revealed a decreasing trend: 1.79 in period 1 and 1.67 in period 3.

AAV is associated with increased mortality. During the study period, the incidence of AAV was found to be stable, and the prevalence has increased.

Data quality in epidemiological studies is a basic requirement for good scientific research. The aim of this study was to examine an important indicator of data quality, data completeness, by investigating predictors of missing data.

Baseline data of a cohort study, the population-based Hamburg City Health Study, were used. Missingness was investigated at the levels of a whole research unit, on the two segments of health service utilisation and psychosocial variables, and two sensitive items (income and number of sexual partners). Predictors for missingness were sociodemographic variables, cognitive abilities and the mode of data collection. Associations were estimated using binary and multinomial logistic regression models.

Of 10 000 participants (mean age=62.4 years; 51.1% women), 32.9% had complete data at the unit level, 66.8% had partially missing data and 0.3% missed all items. The highest proportions of missing values were found for income (27.8%) and the number of sexual partners (36.7%). At both the unit, segment and item level, older age, female sex, low education, a foreign mother language and cognitive impairment were significant predictors for missingness.

For analysing population-based data, dealing with missingness is equally important at all levels of analysis. During the design and conduct of the study, the identified groups may be targeted to reach higher levels of data completeness.

With the acceleration of globalisation and the increasing frequency of international exchanges, the risk of cross-border transmission of emerging respiratory infectious diseases (ERIDs) has significantly increased. Since the year 2002, epidemics of SARS, Middle East respiratory syndrome (MERS) and COVID-19 have exemplified this trend. These epidemics have impacted the prevalence and transmission of traditional respiratory infectious diseases (RIDs), such as influenza, which share similar transmission routes and control measures. To better explore the impact of ERIDs epidemics on influenza, our study quantitatively evaluates the epidemiological changes in influenza during three representative emerging respiratory coronavirus epidemics: SARS, MERS and COVID-19.

Using Global Influenza Surveillance and Response System data, we examined influenza trends across different periods and regions affected by the three coronavirus epidemics. The impact of the epidemic on influenza was revealed by comparing and analysing the reported positive cases (RPCs) of influenza during the pre-epidemic and epidemics, and during the three postpandemic periods. Based on the Susceptible-Exposed-Infected-Asymptomatic-Recovered (SEIAR) compartmental model, the time-varying effective reproduction number () over time was calculated, and the Farrington surveillance algorithm was used to calculate the RPCs in the absence of an epidemic to analyse the characteristics of influenza transmissibility during the epidemics of the three respiratory coronavirus changes.

There was a significant decline in the RPCs of influenza and transmissibility. The suppressive effect of the COVID-19 epidemic on influenza prevalence was the most pronounced. During the COVID-19 epidemic, the RPCs of the three major influenza subtypes showed the largest decrease compared with historical predictions, with reduction rates of –53.30% for A(H1N1), –57.50% for A(H3N2) and –48.56% for influenza B (p0.05). During the MERS epidemic, the RPCs of A(H1N1) and A(H3N2) decreased by 28.75% and 17.62%, respectively, although influenza B partially rebounded in the later stages, resulting in a relatively smaller overall impact.

The COVID-19 epidemic demonstrated the most pronounced suppressive effect on influenza prevalence. The impact of SARS was secondary, while MERS had the least effect. Among different influenza subtypes, A(H3N2) and influenza B exhibited greater declines compared with A(H1N1). The decrease in RPCs during coronavirus epidemics highlighted the importance of non-pharmaceutical interventions (NPIs), demonstrating the broad applicability and high efficacy of comprehensive control strategies for RIDs. Furthermore, when NPIs are lifted during the later stages of coronavirus epidemics, attention should be paid to the potential rebound of traditional respiratory diseases such as influenza.

Despite substantial research investments aiming to prevent cancer and develop therapeutic interventions, cancer remains a formidable challenge. In view of the persistent rise in cancer prevalence, the condition should also be recognised as a chronic disease. Such an approach can enhance the quality of life of patients with cancer, inhibit treatment-related adverse events and prevent recurrence via comprehensive post-treatment management. The core objective of this study is to investigate the association between dietary factors and treatment-related adverse events in patients with cancer, with the aim of providing individualised dietary recommendations to reduce adverse events and enhance quality of life.

The study cohort will include 600 participants aged ≥20 years. The participants will be assessed for dietary intake, cancer therapy-related adverse events and single-nucleotide polymorphisms using genomic DNA extracted from saliva. In addition, general and clinical information, lifestyle patterns and general/biochemical data of the blood will also be collected. The primary outcome is dietary factors that mitigate chemotherapeutic adverse events, and the secondary outcome is the association between nutritional status and survival in Korean patients with cancer. Considering the potential impact of dietary habits on the adverse events of cancer treatment, the findings of this study can be used as a basis for the establishment of new dietary guidelines for patients with cancer.

The Institutional Review Board of Severance Hospital, Yonsei University Health System, Seoul, Korea, approved the study protocol (4-2021-1110). Further, all participants provided a written informed consent prior to the study. The findings will be shared via publications.

Leishmaniases are a group of vector-borne diseases caused by parasites of the genus Leishmania, which are renowned for increasing global spread due to factors like climate change, globalisation, urbanisation and migration. Leishmaniasis is classified as a neglected tropical disease but is endemic in several areas of the Mediterranean Basin, including Italy, where Leishmania infantum is most involved as the parasite, phlebotomine sand fly as the vector and dog as the principal reservoir. Effective surveillance of communicable infectious diseases is a goal worldwide for organisations such as the WHO and for local and national governments but is an unfulfilled objective. Even in Italy and particularly in the region of Tuscany, despite mandatory reporting, significant gaps each year are identified between reported cases and hospital admissions. By estimating the underreporting of confirmed human leishmaniasis cases, this protocol aims to suggest actions to strengthen the current epidemiological surveillance system to enable timely and effective public health intervention in human and veterinary populations.

This retrospective multicentre study, conducted in the Central Tuscany Health District, the most populous area of the Tuscany region with approximately 1.6 million inhabitants, is based on the analysis of data collected from 2014 to 2024 using diagnostic laboratory, hospital and regional information system sources. The primary objective is to estimate the degree of underreporting of leishmaniasis in this area through the application of capture-recapture models. The secondary objective is to analyse the clinical and demographic characteristics of individuals diagnosed as confirmed leishmaniasis cases between January 2014 and December 2024, as well as to perform a geolocation analysis of the cases. The study includes the entire population, both adult and paediatric, of the Central Tuscany Health District who underwent laboratory testing for leishmaniasis (serological tests identifying the presence of antibodies; parasitological examination with evidence of amastigotes in aspirates, smears or biopsy sections; culture examination of aspirates, biopsies and/or peripheral blood positive for the presence of promastigotes; identification of Leishmania nucleic acid in aspirates, biopsies and/or peripheral blood samples via molecular diagnosis).

The study is being conducted in accordance with the protocol approved by the Ethics Committee of the Tuscany Region – Pediatrics Section, in November 2024. Ethics Committee opinion register number: 219/2024. Because the study uses only pseudonymised, routinely collected administrative and laboratory data with no direct patient contact or intervention, individual informed consent was not required, as confirmed by the Ethics Committee. Findings will be submitted to a peer-reviewed journal, presented at international conferences and presented at stakeholder workshops.

Adolescent pregnancy is a global issue. Early childbearing is strongly linked to poverty and negative health outcomes, including increased neonatal death risk. This study explores spatial patterns of adolescent pregnancies and neonatal deaths and their association with socioeconomic characteristics.

This population-based study used spatial analysis techniques to investigate the geographical distribution of adolescent pregnancies, socioeconomic characteristics and neonatal mortality rate (NMR).

The 645 municipalities of State of Sao Paulo, Brazil.

All live births to mothers residing in the State of Sao Paulo, Brazil, between 2004 and 2020.

The socioeconomic indicators used were: municipal human development index and per capita income (PCI). Spatial patterns were assessed for spatial autocorrelation (Moran’s I, LISA), and smoothed using local Bayesian estimation. Spearman’s correlation was used to ascertain the relationship between the percentage of live births to adolescent mothers and socioeconomic indexes. This calculation was also undertaken between different maternal age groups of NMR.

The study analysed over 10 million live births, with 14.3% attributed to adolescent mothers. Spatial analysis revealed significant clustering of adolescent pregnancies, strongly associated with lower socioeconomic indicators. NMR also exhibited spatial clustering, particularly after smoothing. Statistically significant differences were observed in PCI medians between high–high and low–low clusters for adolescent births. High and low incidence areas of NMR, both in all maternal ages and stratified by adolescent and non-adolescent mothers, demonstrated considerable overlap.

The results indicated the existence of clustering areas of adolescent pregnancy and neonatal deaths and suggested that the prevalence of births to adolescent mothers is not distributed equally and is higher in lower socioeconomic developed areas.

To determine what drives participation in clinical trials with decentralised elements and to estimate trial participation probabilities for trials with different degrees of decentralisation.

Patient preference study using a discrete choice experiment.

Recruitment in primary, secondary, tertiary care and other settings in the Netherlands (NL), Austria (AT) and Germany (DE).

People with type 2 diabetes mellitus (T2DM) aged ≥18 years. A total of 787 people (NL n=276, AT n=265, DE n=246) participated in the study.

Preferences for participation in clinical trials with different options for location and type of contact with the study team, activities to perform by participant, use of digital technologies by participant, number of scheduled contacts, trial duration, known safety and efficacy of the drug.

How much was known about the safety and efficacy of the drug was the most important element in the decision whether to participate in a clinical trial in all countries. The trial duration, location and type of contact with the study team, and number of scheduled contacts were other important elements. Participation probabilities for hypothetical trial scenarios differed between countries, with the highest rates for a decentralised trial involving video contact (NL: 89%; AT: 99%; DE: 84%).

People with T2DM prefer to take part in clinical trials with decentralised approaches. Information on preferences can help trialists and protocol developers to design and plan future trials that integrate patients’ needs and thus reduce barriers to participation.

Within the Canadian context, we sought to examine the relationship between households with autistic children/youths and household income.

We used data from the 2019 Canadian Health Survey on Children and Youth (CHSCY) to analyse households with a child/youth aged 1–17. Propensity-score matching was used to pair records for children/youths with a reported autism diagnosis to those without. We used linear regression for continuous outcomes (eg, total household income) and Poisson regression for binary outcomes (eg, low household income). All analyses were adjusted for the correlation between matched pairs.

Total annual income of all household members.

Low household income; single-parent or single-income status; and whether at least one parent was not working or absent from work during the past week.

Among a total of 39 951 CHSCY records, we identified a cohort of 815 autistic children/youths. The characteristics of the matched cohort were well-balanced. Households with an autistic child/youth had a mean annual household income that was lower (mean difference: $C16 489; 95% CI $C6384 to $C27 149) compared with matched households without an autistic child/youth. Households with an autistic child/youth were also 26% more likely to be classified as having a low household income (Relative risk (RR)1.26; 95% CI1.17 to 1.35) and 20% more likely to rely on a single income (RR1.20; 95% CI 1.10 to 1.33) compared with households without an autistic child/youth.

Compared with households without an autistic child/youth, those with an autistic child/youth often face more economic challenges, including lower household income and greater risk of food insecurity. Households with an autistic child/youth are more likely to rely on a single income.