Philosophical Transactions of the Royal Society B: Biological Sciences

Health inequalities are often examined through single axes such as class or ethnicity, obscuring how these dimensions interlock. This study applies a longitudinal intersectional approach to examine physical and mental health trajectories across five generations in the UK. We analysed 14 waves of the UK Household Longitudinal Study (2009-2024) using longitudinal Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). We modelled SF-12 physical and mental health trajectories for 398 intersectional strata defined by gender, ethnicity, occupational class, and generation. Physical health inequalities widened with age, consistent with cumulative disadvantage, while mental health inequalities were more evident among later-born cohorts. The 'Boomer' generation exhibited a relatively flat mental health trajectory across its observed age range. In contrast, 'Generation Z' had lower predicted mental health, particularly among White British women with no work history - a group with poorer predicted trajectories than their South Asian peers. Our study shows how health inequalities are structurally differentiated by cohort and intersectional position. Policy responses should support proportionate universalism, combining broad population-level support with intensified action for groups showing poorer health.

Recent studies report associations between the patient genome and the chronic wound microbiome, suggesting a causal relationship. Guided by the expectation that larger genomic perturbations are less likely to be neutral, here we study the association of genomic copy number variants (CNVs) with abundances of wound species. Genomic and metagenomic data were collected from 597 patients with chronic wounds at initial clinical visit. Association studies included 831 CNVs and 68 species, implementing a two-cohort design and study-wide significance threshold. There were 47 CNVs (5.7%) associated with 25 species (36.8%); an additional 1,730 associations achieved study-wide significance in one cohort. Associations with haplotype dosage variation dominated significant associations (69.4%) indicating haplotype dosage is important beyond simply locus copy count. Significant co-occurrences between associated and non-associated species, all involving anaerobes, support a model in which the genome selects for certain species that in turn shape the broader microbiome through ecological interactions. Significant CNVs encompassed 66 genes which were functionally overrepresented for several terms, with extracellular matrix (ECM) and ECM-cell interaction terms emphasized. Four collagen and collagen remodeling genes were distributed across four unlinked significant CNVs, a result that strikingly aligns with the previous studies reporting other collagen or ECM component associations. Related, cytoskeletal dynamics are also strongly implicated. Heritability estimates drawing on all available data and controlling for species correlation and patient factors yielded 30 species with significant heritabilities, 24 of which were greater than 20%. These findings extend the genomic basis of the chronic wound microbiome by emphasizing importance of genomic structural variation and suggest a prominent role for variation across ECM-cellular connections as mechanisms defining microbial selection.

Introduction: Raised blood pressure is an important cardiovascular risk factor in Cambodia; however, national averages may obscure substantial local geographic heterogeneity. We assessed the spatial distribution of raised blood pressure and its demographic, metabolic, behavioural, built-environment, and environmental correlates using the 2023 Cambodia STEPwise approach to noncommunicable disease (NCD) risk factor surveillance (STEPS) survey. Methods: We analysed 289 georeferenced primary sampling units (PSUs) from the 2023 Cambodia STEPS Survey. PSU-level case counts and numbers of adults with valid blood pressure data were modelled using a frequentist binomial generalised additive model with a two-dimensional Gaussian-process smooth. An explanatory model included selected PSU-level and contextual covariates; a separate mapping model used spatially continuous predictors to generate predictions on a 5-km grid. Design-based national and residence-specific prevalence estimates were calculated separately using the survey design and Step-2 weights. Results: Among 4,225 adults with valid blood pressure data, unweighted prevalence of raised blood pressure was 28.6%, compared with 18.8% after Step-2 weighting; weighted prevalence was 17.5% in rural areas and 21.7% in urban/suburban areas. Mean observed unweighted PSU-level prevalence was 29.0%. In the adjusted spatial explanatory model, the proportion aged 60-69 years ({beta}=1.969, SE=0.327; p<0.001) and overweight/obesity prevalence ({beta}=0.996, SE=0.265; p<0.001) were positive ecological correlates. The spatial model had lower Akaike information criterion and residual deviance than its non-spatial counterpart, although Bayesian information criterion was higher. Prediction uncertainty was greater in some sparsely sampled areas. Conclusions: Raised blood pressure showed significant geographic heterogeneity across Cambodia. Older age composition and overweight/obesity prevalence were positive PSU-level correlates, not individual-level causal effects. Predicted prevalence should be interpreted alongside uncertainty and should complement, rather than replace, design-based STEPS prevalence estimates for geographically informed NCD planning.

Japanese encephalitis virus (JEV) is a leading cause of viral encephalitis in humans in Asia. Prior to 2021, only sporadic outbreaks had been detected in Australia's tropical northern extremes. However, during 2021-23, JEV infection was identified in 45 people and in more than 85 piggeries, together with many detections in feral pigs, mosquitoes, and other livestock across Australia, including in the temperate far south. Here we estimated the spatial extent of virus transmission during the outbreak (the realised niche) and the area environmentally suitable for transmission (the potential niche). We collated a national dataset of JEV surveillance and detection in humans, mosquitoes, domestic pigs, feral pigs, and sentinel chickens from 2021-23. We combined these data with (1) previously published predictions of habitat suitability for vertebrate host and vector species, and (2) estimated densities of humans, domestic pigs, and feral pigs, in a multipart assessment of spatial risk. Our model projected broad potential environmental suitability over much of northern and eastern Australia during the outbreak period, but floodplain wetland areas in the north and the inland east of Australia had both the highest estimated environmental suitability for transmission, and the strongest evidence for virus circulation.

Background Interruptions are common in hospital outpatient departments (OPDs) and are linked to error. Many are clinically necessary, so the aim is to regulate them. Most interventions target the individual clinician. Little is known about how doctors manage interruptions in practice or what makes their strategies work. Methods Qualitative study using focus groups and interviews with 42 doctors working in UK National Health Service OPDs (19 sessions, September to November 2025). Participants were purposively sampled by clinical experience and self-reported patient complexity. Data were analysed using Framework Analysis, informed by Cognitive Load Theory and Social Identity Theory. Results We developed four themes. (1) Pre-emptive protection of attention. Doctors withdrew, signalled unavailability and set thresholds for interrupting. These depended on colleagues learning and sharing the norm, which staff rotation eroded. (2) Sharing the burden through team coordination. Designated roles and time-limited rotas moved interruptions to colleagues with capacity set aside for them and made interrupting legitimate. (3) Real-time cognitive repair. Doctors asked interrupters to wait while they secured the task, and rebuilt the consultation on return, sometimes with the patient's help. Asking a colleague to wait depended on seniority or team membership; some trainees described difficulty doing this with senior colleagues. (4) Organisational recognition as the precondition for sustainable regulation. Where supervision was built into job plans, the interruptions it generated were expected and doctors held capacity in reserve for them. Advice, vetting and telephone queries were rarely counted as work. Conclusions Each strategy served a cognitive purpose, and social and organisational conditions decided whether it was perceived to work. Interventions could make norms shared and roles explicit, count interruption work in job plans and keep routes open for junior staff to raise concerns. Evaluations should ask who is able to use them.

Introduction: Primary care electronic health records (EHRs) are an important resource for health research, but death recording in primary care EHRs may be incomplete or differ from Office for National Statistics (ONS) death registrations. We used OpenSAFELY-TPP to assess the completeness and concordance of death recording and provide recommendations for using date-of-death information. Methods: Using linked primary care EHRs and ONS death registrations, we assessed whether ONS-registered deaths from 2020-2025 had a primary care date of death and, where present, calculated the difference between dates. Where a primary care date was absent, we assessed death-related SNOMED CT codes. Analyses were conducted overall and by year, population subgroup, and general practice. We also examined GP registration end dates and primary-care-recorded deaths without a corresponding ONS record, including monthly patterns near the data extraction date. Results: Among 1,409,275 ONS-registered deaths, 88% had the same date recorded in primary care and 8% had no corresponding primary care date. Among 1,324,995 deaths recorded in primary care, <2% had no corresponding ONS record. Deaths recorded in only one source were more frequent among people aged <45 years and those from Mixed, Asian or Asian British, Black or Black British, and Chinese or Other ethnic groups. ONS-only dates were also more frequent in London and the West Midlands. Primary-care-only deaths increased close to date of data extraction, reaching 7% in February 2026. Same-day GP deregistration increased from 9% in 2020 to 85% in 2025. Conclusions: Death recording in primary care EHRs showed high completeness and concordance with ONS registrations, but discrepancies remained for recent deaths and some population groups. Data recency and population-specific completeness should therefore be considered when using linked mortality data for research.

Globally, measles is re-emerging in countries that have previously achieved elimination, including the United States. As immunization rates decline, characterizing the dynamics and evolving spatial pattern of measles re-emergence is critical to inform the public health response. We analyze annual county-level measles cases and vaccine coverage data in the United States (US) from 2011-2025 and find a shift in measles epidemiology in recent years indicative of re-emergence. While outbreak risk is spatially concentrated, we find that outbreaks are increasingly spreading throughout the broader population and across counties, but targeted interventions are predicted to prevent re-emergence nationwide. During the first decade of this period (2011-2020), outbreaks were only weakly associated with county-level vaccine coverage and predominantly isolated to single counties; however, recently (2021-2025), vaccine coverage has become strongly associated with outbreak size and spread across neighboring counties has increased. These findings suggest that measles transmission is increasingly sustained across the broader population rather than only in socially clustered communities. We developed a spatial statistical model to predict outbreak risk and size in all US counties with validation over 2021-2025; the model predicted counties with [&ge;]10 cases with a sensitivity of 95% (range across 2021-2025: 75-100%) and specificity of 83% (64-98%). Mechanistic models based on county vaccine coverage alone had worse performance, particularly in predicting larger outbreaks. Using the spatial statistical model, we find that prioritizing interventions in the areas of greatest model-predicted risk (e.g., top decile of US counties) was more impactful than state-level interventions (e.g., top five states) or targeting based on low vaccine coverage alone. Achieving even modest (5 percentage point) increases in vaccine coverage in counties in the top decile of model-predicted risk reduced long-term measles risk nationwide by over 90%. Together, these findings demonstrate that predictive risk modeling to inform spatially targeted interventions can likely mitigate the re-emergence of vaccine-preventable diseases.

This systematic review aimed to synthesize evidence on the association between DNA methylation (DNAm) age and all-cause and disease-specific mortality risks in adults. A systematic search of six databases from Jan 1 2011 to April 15 2026 identified articles assessing the association of DNAm age measures and all-cause or disease-specific mortality in adults from general or disease-specific populations. Effect sizes were pooled as hazard ratios (HRs) with 95% confidence intervals (CIs) using inverse-variance random-effects models. Of 42 023 records screened, 125 articles (380 705 participants) met the inclusion criteria, with 53 included in meta-analyses. Overall, 48 distinct DNAm clocks were evaluated. Higher DNAm ages were associated with higher risks of all-cause, cardiovascular, and cancer mortality risks. In general populations, GrimAge epigenetic age acceleration (EAA) showed consistent associations across mortality outcomes, with each 1 year higher GrimAge EAA associated with ~6-10% higher all-cause (31 cohorts, n=53 642, HR per SD: 1.46 [95% CI 1.38, 1.55], HR per 1-year: 1.09 [95% CI 1.08, 1.11], I^2=84.1%, p-value=1.21 x 10^(-14)), cardiovascular (6 cohorts, n=30 751, HR per SD: 1.55 [95% CI 1.38, 1.73], HR per 1-year: 1.10 [95% CI 1.07, 1.13], I^2=28.0%, p-value=1.71 x 10^(-4)), and cancer (5 cohorts, n=27 187, HR per SD: 1.31 [95% CI 1.15, 1.50], HR per 1-year: 1.06 [95% CI 1.03, 1.10], I^2=33.6%, p-value=4.76 x 10^(-3)) mortality. Clocks incorporating additional surrogates and technical refinements showed numerically larger pooled associations than their original counterparts. GrimAge2 (HR per SD: 1.65 [95% CI 1.53, 1.77] vs 1.46 [1.38, 1.55]) and PCGrimAge (1.56 [1.36, 1.78] vs 1.51 [1.32, 1.74]) showed higher pooled HR association with all-cause mortality than GrimAge. Further work is warranted to evaluate the responsiveness of DNAm clocks to interventions and potential clinical utility.

OBJECTIVE: To describe (1) US emergency department-treated pickleball injury burden and the injury-to-participation measure among total players, with burden among adults aged 60 to 79 years as a descriptive subgroup, and (2) determine whether general internet search interest for 'pickleball' is also associated with total pickleball-related injuries. DESIGN: Ecological time series study, United States, 2014 to 2023. DATA SOURCES: National Electronic Injury Surveillance System (NEISS) emergency department microdata yielded 1,738 adjudicated pickleball cases, 921 of them orthopedic, weighted to an estimated 101,450 injuries nationally. Google Trends, English Wikipedia pageviews, and GDELT news volume served as general pickleball attention signals, with the Trends index for 'sourdough' as a negative control. Sports and Fitness Industry Association (SFIA) participation estimates supplied a total player denominator. MAIN OUTCOME MEASURES: Annual national injury estimates with design-based 95 percent confidence intervals; injury-to-participation measures; and correlations between total pickleball-related injuries and general pickleball attention signals before and after removing trend and seasonality. RESULTS: Estimated emergency department-treated pickleball injuries rose 17.5-fold, from 1,391 in 2014 (highly unstable) to 24,294 in 2023. 70 percent of adjudicated cases involved adults aged 60 to 79. During 2017-2023, injury estimates rose 4.0-fold and participation rose about 4.4-fold. No temporal trend was detected in the injury-to-participation measure (P=0.59). Search interest looked like an excellent proxy: in annual levels it correlated with total pickleball-related injuries at R=0.96, and Pickleball Wikipedia pageviews at R=0.98. However, so did searches for "sourdough", at R=0.76. Removing trend and seasonality left little (monthly residual R=0.084; year-on-year R=0.28 over 96 months, 2015-2023), and the seasons ran opposite, with injuries peaking in February and searches in July, such that, on 12-month mean profiles, the sourdough negative control fitted the injury season (R=0.96) while pickleball ran against it (R=-0.40). General pickleball search interest and pickleball news coverage remained correlated in year-on-year changes in 2017-2023 (R=0.64), whereas their corresponding correlations with total pickleball-related injuries in 2017-2023 were 0.25 and 0.20. CONCLUSIONS: The absolute burden of emergency department-treated pickleball injury has grown substantially, but the available surveillance data cannot resolve whether the sport has become more hazardous per participant. The observed rise is consistent with growth in exposure alone. The strong correlation between search interest and injury counts was not specific, the association was substantially attenuated after detrending, and the seasonal patterns were opposed. These descriptive results do not establish that search interest can substitute for injury surveillance, and series that rise together should not be assumed to be related.

Brazil experienced its worst dengue epidemic in 2024, with an increase in severe outcomes among elderly individuals, highlighting the need for vaccination strategies informed by population immunity. We reconstructed state- and age-specific immune profiles by fitting an age-structured catalytic model to dengue surveillance data from 2000-2025. This inferred immune profile was incorporated into an SIR-type transmission model to project disease burden and to evaluate the public health impact of vaccine allocation strategies. We observed substantial spatial heterogeneity in accumulated immunity, which was closely associated with projected burden and optimal allocation. Strategies prioritizing states with lower historical incidence and larger susceptible populations yielded greater benefits. Under limited vaccine supply, targeting children resulted in the greatest reductions in DALYs, whereas targeting elderly populations achieved smaller DALY reductions but larger reductions in mortality. We further showed that accelerated vaccine supply markedly increased impact, while allocation choices remained critical when availability was constrained.

We develop an age- and immunity-structured COVID-19 model with setting-specific contacts, calibrated to Ontario incidence and hospital admissions before Omicron. We simulate counterfactual vaccination strategies and contact restrictions in schools, workplaces, and other community settings, evaluating projected severe-case demand against an illustrative healthcare-capacity benchmark. Vaccination combined with workplace and community contact restrictions keeps simulated demand within capacity. In contrast, relaxing restrictions in either setting produces large surges and repeated capacity threats, even when school restrictions remain. School-only changes produce smaller effects on severe disease. These findings highlight the value of vaccination and setting-specific contact restrictions that prioritize workplace and community settings for pathogens with adult-concentrated severe outcomes.

Financial well-being (FWB) encompasses objective and subjective financial status and may influence health. We developed and validated a parsimonious FWB index using data from 23,006 Health and Retirement Study (HRS) participants aged 50 years and older from 2006 to 2022. The FWB-5 Index was derived using correlated two-factor confirmatory factor analysis accounting for household clustering. Indicators included household wealth, household income-to-poverty ratio, monthly financial strain, satisfaction with one's financial situation, and perceived financial mastery. We assessed convergent and discriminant validity using the Consumer Financial Protection Bureau Financial Well-Being (CFPB-FWB) Scale and Satisfaction with Life Scale, respectively. Associations with pre-baseline socioeconomic factors and subsequent depressive symptoms and health conditions were examined to assess construct and predictive validity. Model fit indices supported the two-factor structure (robust comparative fit index = 0.99; robust root mean square error of approximation = 0.05). Correlations were stronger with the CFPB-FWB Scale (Spearman P = 0.80) than with life satisfaction (Spearman P = 0.43). Associations with socioeconomic factors and subsequent health outcomes were in the hypothesized directions. These findings support the FWB-5 Index as a parsimonious measure for examining financial well-being and its associations with health across HRS waves, including those predating the CFPB-FWB Scale.

Objective. Temperature readings are routinely stratified by race and ethnicity, though significant group differences may reflect physiology, instrument noise, or categorization rather than biology. This study tests whether these categories partition facial infrared thermography measurements beyond individual variation and baseline device noise. Approach. A secondary analysis of thermography data (n = 951 adults) compares inner-canthus maximum (TCEmax) and full-face maximum (Tmax) temperatures across five administrative categories via one-way analysis of variance (ANOVA), mixed-effects modeling, Bland-Altman analysis against oral reference, and Monte Carlo sensitivity analysis. Main results. ANOVA returns significant group differences (p < 0.001; eta-squared = 0.04 for TCEmax, 0.03 for Tmax), but the total spread (0.2 to 0.3 degrees Celsius) is comparable to device accuracy and within-subject variability. Individual variation accounts for 95% of TCEmax variance, and adding simulated Gaussian noise to participant-level temperatures (sigma = 0.10 to 0.30 degrees Celsius) preserves the complete group-mean rank order in as few as 37.5% of iterations. Significance. Testing whether a group difference survives perturbation at the scale of instrument accuracy offers a check against treating significance alone as evidence of physiology. Here, observed group differences are small relative to measurement variability, and their physiological interpretation remains uncertain, with implications for clinical tools that treat administrative categories as biologically meaningful.

Background. Nigeria's reported Lassa fever case fatality ratio (CFR) rose from 18.9% at week 23 of 2025 to 25.0% in 2026, prompting concerns over failing clinical care. Because surveillance artefacts can also alter CFRs, candidate mechanisms that published data can resolve were identified and evaluated. Methods. This ecological study extracted weekly state-level counts from 474 Nigeria Centre for Disease Control and Prevention situation reports (2017-2026). Per a pre-specified plan, years were compared at phase-matched points, year-on-year CFR changes were decomposed into within-state and between-state components, and tipping-point ascertainment shifts calculated. Weekly incident and cumulative published totals were compared post hoc. Findings. Of 11 candidate mechanisms, 2 could be evaluated fully and 5 in part. On weekly incident counts, 2026 did not differ from 2025 at the phase-matched midpoint (+0.3 percentage points, 95% CI -5.0 to 7.6); within-state (-1.1, 95% CI -4.7 to 3.0) and between-state (+0.5, -2.0 to 2.9) components spanned zero. Conversely, the published cumulative CFR was 5.4 to 6.2 percentage points higher because 70 deaths were added retrospectively by week 36 outside weekly reports. Reconciling cumulative figures would require 279 missed survivors (6% of suspected cases not confirmed). Interpretation. The 2026 CFR rise came from deaths added to cumulative totals outside the weekly counts, and published data cannot attribute it to care. Endemic zoonotic CFRs cannot serve as clinical outcome measures unless testing volumes, deaths added late, and post-mortem sampling are published alongside case counts. Funding. US NSF-NIH-NIFA EEID; UK BBSRC; Birgitta Sintring Fellowship (Uppsala University).

Despite recent evidence of the ability of systemic and organ-specific proteomic aging clocks to predict a large range of age-related diseases, their utility in cancer research remains largely underexplored. In this study, we evaluated the predictive ability of systemic and organ-specific proteomic aging clocks for (i) all-cause mortality, (ii) cancer-related mortality, and (iii) cancer incidence in a sample of Finnish twins (N = 401, mean age at baseline 62.3 years) with Olink proteomic data. Participants were followed for a mean of 10.6 years (SD +- 1.6), with estimates from four systemic and 18 organ-specific proteomic aging clocks calculated at baseline. Cox proportional hazards regression models adjusted for sex and age at baseline identified 15 proteomic aging clocks as significant predictors of all-cause mortality (Ncases = 28) after multiple testing correction (FDR < 0.05), with 11 remaining significant after lifestyle adjustment (Ncases = 27). For several clocks, effect sizes were large, with hazard ratios (HR) approximately doubling per one standard deviation (SD) increase in clock estimates. In predicting cancer-related deaths among participants without a prior cancer diagnosis at baseline (Ncases = 9), only the Immune clock showed a significant positive association after multiple testing correction in basic (HR = 2.94, 95% CI: 1.88-4.59) and lifestyle-adjusted models (HR = 3.31, 95% CI: 1.78-6.17). No associations with cancer incidence (Ncases = 34 basic, Ncases = 31 adjusted) survived multiple testing correction, although several nominal associations were observed. In conclusion, our findings suggest that proteomic aging clocks are strong predictors of all-cause and cancer-specific mortality, independent of lifestyle factors. Proteomic aging clocks may further serve as valuable tools for stratifying cancers by mortality risk.

Introduction: HIV and childhood maltreatment (CM) are both chronic stressors that disproportionately affect women, with each contributing to accelerated biological aging. Whether biological aging markers are convergent and associate with HIV and CM is unclear. Methods: We studied 238 women (122 with HIV), characterised for CM severity, and assessed biological aging using absolute telomere length (aTL), mitochondrial DNA copy number (mtDNAcn), magnetic resonance imaging-based brain-predicted age difference (MRI-BPAD), and DNA methylation age (DNAmAge) clocks. CM was measured with the Childhood Trauma Questionnaire-Short Form total score. We examined intercorrelations among biological aging markers to assess convergence and conducted linear regression models to test moderation by HIV status and CM severity. Results: PWH had shorter aTL, lower MRI-BPAD, and higher Horvath age acceleration (HorvathAA), HannumAA, PhenoAA, and extrinsic epigenetic age acceleration (EEAA). CM had limited associations with biological aging markers. Absolute TL correlated weakly with mtDNAcn (p = 0.36), PhenoAA (p = -0.18), and EEAA (p = -0.18), while MRI-BPAD correlated weakly with PhenoAA (r = 0.20). DNAmAge clocks were moderately to strongly intercorrelated (r = 0.35 - 0.93). No robust two- or three-way moderation effects were observed after false discovery rate correction. Conclusion: Our findings support a multidimensional pattern of biological aging, with substantial convergence among epigenetic aging measures but limited relationships across different markers, largely independent of HIV status and CM severity. Longitudinal approaches are needed to clarify how distinct biological aging markers relate to one another and to health outcomes over time in vulnerable populations.

Vegetation plays a critical role in shaping fine-scale tick density by structuring local microclimates, habitat resources, and host interactions that largely determine tick survival and activity, with implications for tick-borne disease transmission. Tick burden in the United States continues to increase, with annual reported tick-borne disease cases more than doubling from 2004 through 2019. These trends call for a broader scope of tick-mitigation strategies that go beyond traditional prevention measures that focus on personal protection; and there is an opportunity to inform habitat-level interventions. Here, we quantify fine-scale vegetation structure across 48 subplots at tick surveillance sites in Western Massachusetts to assess local habitat features associated with Ixodes scapularis density and potential for human-tick contact risk. In assessing understory and overstory vegetation attributes, this study identified life stage-specific differences in predicted tick density, with higher adult densities in areas with deeper leaf litter and presence of invasive plant species and nymphs associated with high presence of ferns. Both adult and nymphal Ix. scapularis were predicted at higher densities in relatively low basal area forests (18.9 to 26.9 m2/hectare). This study design provides a simple, low-cost framework for organizations looking to incorporate tick-informed forest measurement ecology into their public health tick surveillance protocols with minimal training.

Background: Previous studies indicated that regional fluctuations in COVID-19 impact were associated with socioeconomic, demographic and environmental factors early in the pandemic. It is unclear whether factors associated with regional COVID-19 mortality and SARS-CoV-2 infections changed over the course of the pandemic. Methods: We evaluated the association of ecological factors with municipality-specific COVID-19 mortality in the national population of Austria between January 2020 and June 2023. Analyses were conducted separately per calendar year and pooled across years via random-effects meta-analysis. Outcomes were analysed using univariable and multivariable zero-inflated negative binomial (ZINB) regression, including annually averaged environmental exposome exposure (including air pollution and UV radiation), socioeconomic, demographic and infection dissemination predictors with significance threshold set to p<0.005. Secondary analysis modelled SARS-CoV-2 infections using of negative-binomial model (NB). Two additional approaches for smaller predictor set selection were applied as sensitivity analyses. Results: Within the entire observation period 18,430 COVID-19 deaths were reported. In univariable analyses (pooled RR (99.5% CI)), COVID-19 mortality was significantly associated with the proportion of commuters (0.79 (0.73-0.86)), residents aged 75-84 (1.18 (1.01-1.37)) and [&ge;]85 years (1.29 (1.04-1.60)), residents with at most compulsory education (1.15 (1.02-1.29)), employed residents aged 15-64 (0.89 (0.85-0.93)), and homeowners (0.91 (0.83-0.99)), as well as with precipitation (0.94 (0.89-0.99)) and the average time with a mean temperature of 5-15 C (0.95 (0.90-0.99)). In multivariable analyses the share of population aged 85 or older (1.30 (1.09-1.54)) and home ownership (0.92 (0.87-0.98)) were independently significant. Mortality predictor estimates were relatively stable across pandemic years. Across 5,963,882 documented SARS-CoV-2 infections share of employed in 15- to 64-year-olds (1.01 (1.01-1.02)), part-time employment rate (1.01 (1.00-1.02)) and district level nursing care allowance recipiency (0.97 (0.95-0.98)) were associated with detected infections. Overnight stays, population 85 or older, income, compulsory education or less and air pollution all had multiple significant estimates with opposite directionality, leading to non-significant overall associations. Sensitivity analyses outcomes mirrored main analyses outcomes. Conclusions: Throughout the pandemic in Austria, demographic and socioeconomic factors were associated with COVID-19 mortality and infections, but many associations, especially for infections, were unstable over time. These findings underscore the importance of structural vulnerabilities in epidemic impact.

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.

Abstract Many women experience menopausal symptoms after stopping hormone replacement therapy (HRT). An evidence gap remains regarding how women and healthcare professionals (HCPs) make decisions about discontinuing and restarting HRT. Aim To explore experiences of HCPs that support women when they discontinue and restart HRT. Design and setting Qualitative study with HCPs working in NHS primary care. Method Semi-structured interviews with HCPs (n = 15) conducted between October 2025 and March 2026. A preliminary coding template was created using the discussion guide as a framework. Each interview was then coded inductively against the template which developed iteratively. Team based discussion helped refine codes into themes and sub-themes, and a subsequent conceptual model was created. Results The model describes HCPs experiences of supporting women to discontinue HRT as an iterative process characterised by uncertainty. Discussions about discontinuation were commonly prompted by changes in clinical risk or annual HRT review, but decisions about whether and when to stop also depended on womens symptoms, side effects, life stage and readiness. HCPs described agreeing an individualised discontinuation strategy, providing support during the process, and reviewing women after discontinuation to consider alternative treatments or, where appropriate, restarting HRT. Conclusion HCPs recognise the importance of readiness to discontinue and that decision making should be woman led, with HCP support, clear practice guidance and opportunities to revisit treatment. Further research is needed to support women weigh up their personalised risk and benefit of continuing/discontinuing and identify discontinuation strategies that limit resurgent symptoms.