Annals of Epidemiology

Background Alcohol-associated injury is a leading cause of emergency department (ED) utilization in the United States and a clinically important driver of preventable morbidity across the adult lifespan. Prior surveillance research has characterized how the rate and severity of alcohol-associated injury vary by patient age, but whether the seasonal timing of injury risk is equally predictable across age groups (a question directly relevant to the timing of clinical screening intensification and public health intervention) has not been formally tested. Methods We conducted a retrospective surveillance analysis of 45,876 alcohol-associated ED visits among adults aged 18 years and older, identified from the National Electronic Injury Surveillance System (NEISS), 2019-2025 (weighted national estimate: 2,092,319 visits), using the structured Alcohol_Involved indicator introduced into NEISS case abstraction in 2019. Patients were stratified by sex and five age groups (18-24, 25-34, 35-49, 50-64, and [&ge;]65 years). Single-harmonic cosinor (Poisson) regression was used to estimate the seasonal peak day of injury risk (acrophase) for each stratum. To assess reliability, we performed leave-one-year-out jackknife resampling (seven iterations per group), case-resampling bootstrap confidence intervals (1,000 iterations), and likelihood-ratio tests of seasonal-phase interactions. Results Peak injury timing differed significantly across age groups (X^2 [8] = 2356.2, p < .0001). Adults aged 25-64 years showed a highly reproducible early-to-mid-July peak, with jackknife estimates shifting [&le;]14 days when any single study year was excluded. Adults aged [&ge;]65 years showed significant seasonal variation annually (all p < .0001, amplitude comparable to younger groups) but a pooled peak estimate that shifted by up to 100 days across jackknife iterations. Sex-stratified analyses revealed that this instability was driven entirely by females aged [&ge;]65 years (jackknife range: 332 days, peak consistently in late October through early January) rather than males aged [&ge;]65 (jackknife range: 31 days, peak consistently in early August). Hospital admission rates increased monotonically with age from 9.0% (18-24 years) to 31.8% ([&ge;]65 years). Conclusions Alcohol-associated injury follows a reproducible, calendar-stable summer seasonal pattern in adults aged 25-64 years. Among adults [&ge;]65 years, the previously reported temporal instability is concentrated in the female subgroup, whose seasonal injury risk does not converge on a fixed calendar window. These findings suggest that fixed-calendar prevention and screening strategies are well suited to working-age adults and older men, but older women may require a year-round, individually tailored approach. Keywords: Alcohol-related injury; Emergency department; Seasonality; Age factors; Sex differences; Injury surveillance; Cosinor analysis; Older adults

Purpose: This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods: We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings: Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion: Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Importance: Chronic stress may contribute to adverse health outcomes through cumulative physiologic dysregulation. Allostatic load (AL), a composite measure of multisystem physiologic burden, may capture biologic effects of structural, social, and psychosocial stress not reflected by self-reported measures. Objective: To evaluate racial and ethnic differences in AL among women with familial cancer risk and examine how socioeconomic status, psychosocial factors, clinical characteristics, and health behaviors contribute to variations in AL. Design: Cross-sectional study of underrepresented minority participants enrolled in the HERSTORY cohort from October 2023 through September 2025, with comparison participants from the UCLA ATLAS biobank. Setting: UCLA academic health system. Participants: The study included 303 racially and ethnically diverse female HERSTORY participants aged [&ge;]35 years with a family history of cancer and matched non-Hispanic White female ATLAS participants (n=709). Exposures: Race and ethnicity, age, neighborhood deprivation, cancer history and stage, depression, perceived stress, cancer worry, and physical activity. Main Outcomes and Measures: The primary outcome was AL, calculated from cardiometabolic and organ-function measures. A secondary index incorporated race- and ethnicity-specific neutrophil-to-lymphocyte ratio (NLR) derived from 326,826 women in the UCLA Health population. Multivariable regression models evaluated factors associated with elevated AL. Results: Compared with matched non-Hispanic White participants, Black and Asian/Pacific Islander HERSTORY participants had significantly higher AL after adjustment. Hispanic/Latina participants did not have significantly elevated AL. Older age, greater area-level socioeconomic deprivation, and depression were independently associated with higher AL. Prior cancer diagnosis, cancer worry and perceived stress were not significantly associated with AL, whereas regular physical activity was associated with lower AL. Among cancer patients, advanced stage was associated with greater AL. Conclusions and Relevance: This study demonstrates elevated AL among understudied racial/ethnic minority groups with familial cancer risk and identifies associations with neighborhood deprivation, depression, and physical activity. The association between cancer stage and AL suggests that physiologic stress may reflect variation in cancer burden. The lack of association with perceived stress and cancer worry further indicates that physiologic and self-reported psychosocial measures capture distinct dimensions of stress. The development of race/ethnicity-specific NLR thresholds derived from large population samples provide a benchmark for future studies.

Background: Population-based biomonitoring of contemporary-use pesticides remains limited in the United States, particularly in rural agricultural regions, and few studies have repeated measurements within the same individuals over time. Methods: We analyzed 28 urinary pesticide-related biomarkers among 600 adults from the population-based Survey of the Health of Wisconsin with archived urine collected during 2008-2016; 296 participants provided repeat urine and updated exposure information in 2025. Detection frequencies, co-detection, and within-person detection patterns were characterized. Generalized estimating equations were used for stacked, repeated-measures analyses of factors associated with detection of aminomethylphosphonic acid (AMPA), glyphosate, 2,4-dichlorophenoxyacetic acid (2,4-D), and any of these three. Prospective-only analyses evaluated more detailed agricultural and recent exposure measures. Results: Glyphosate, AMPA, and 2,4-D were detected in 7.7%, 6.2%, and 4.3% of retrospective specimens and 5.4%, 3.1%, and 4.1% of prospective specimens, respectively. Co-detection and persistent detection across the 9 to 17-year interval was rare. In repeated-measures models, greater fruit and vegetable intake, older age, and male sex were associated with higher 2,4-D detection. Lower household income was associated with lower AMPA detection, while afternoon/evening collection was associated with higher AMPA detection. In prospective analyses, working on field-crop agricultural land showed the strongest agricultural associations, particularly for 2,4-D and detection of any of the three pesticides. Associations were not seen with self-reported conventional versus organic produce consumption. Conclusions: Urinary pesticide detections were generally infrequent in this Wisconsin population. Diet and direct agricultural activities may be more informative exposure pathways than residing near cropland or private well drinking-water characteristics.

Background: Cardiovascular disease (CVD) disproportionately burdens underserved communities, where social determinants of health (SDOH) perpetuate persistent disparities. Family-based interventions leveraging social support represent a promising yet understudied approach. We describe the rationale, design, and methods of the Skills-based Educational strategies for the Reduction of Vascular Events in Orange County (SERVE OC) RCT and present baseline characteristics of enrolled families. Methods: SERVE OC is a 2-arm RCT of 190 Latino and Vietnamese families (486 individuals) randomized to the family-based intervention or individual self-management. The intervention was grounded in social network theory while employing community engaged strategies. Primary outcomes include achieving ideal cardiovascular health (CVH) defined by AHA Life's Essential 8 (LE8) and systolic blood pressure reduction at 12, 24, and 36 months. Baseline assessments include demographics, LE8, psychosocial factors, food security, and SDOH. Descriptive statistics and regression analyses examined cohort characteristics and associations between SDOH, food security, and LE8. Results: Over 83% of participants had suboptimal LE8 scores. Average adult total LE8 scores were 66.61 {plus minus}11.96, with physical activity as the weakest domain, compared to an average of 76.52{plus minus}10.15 in children. Greater SDOH burden and food security were associated with significantly lower odds of ideal CVH and lower LE8 scores respectively. Conclusions: SERVE OC demonstrates the feasibility of enrolling families in community-engaged RCT targeting CVD disparities in underserved population. Baseline findings confirm substantial CVD risk and SDOH burden underscoring the need for multi-level, culturally tailored interventions. Trials results will inform scalable, family-focused strategies for CVD prevention across the life course. Clinical Trial Registration: URL: https://www.clinicaltrials.gov/; Unique Identifier: NCT05641519.

Background. The imprecision of current metrics to capture the complex genetic admixture and racial identity among Hispanic/Latino individuals in the United States [US] is a concern. We examined the relationship of self-reported race and genetic ancestry with hypertension [HTN] among Hispanics/Latinos. Methods. Cross-sectional study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), including 10,586 Hispanic/Latino unrelated adults. Genetic ancestry: West African [AA], Amerindian [AI], and European [EA]. Self-reported race: White, Black, Native American, or Multiple/Missing (More than one race or Unknown/Not reported/Refused). HTN: systolic (SBP) [&ge;]130 mmHg, diastolic blood pressure (DBP) [&ge;]80 mmHg, and/or use of HTN medications. Age- and sex adjusted models were used. Results. Self-reported race was White (38{middle dot}6%), Black (3{middle dot}6%), Native American (4{middle dot}1%), and Multiple/Missing (53{middle dot}7%), with Unknown/Not reported/Refused representing 32{middle dot}7%. Black and White Hispanics/Latinos had the greatest AA (55{middle dot}7%) and EA (69{middle dot}3%) ancestries, respectively. Each 10% AA increase was associated with OR 1{middle dot}15, SBP beta +0{middle dot}9 mmHg, and DBP beta +0{middle dot}7 mmHg. Conversely, each 10% AI increase was associated with OR 0{middle dot}83, SBP beta -0{middle dot}4 mmHg, and DBP beta -0{middle dot}6 mmHg. HTN prevalence was highest among those with Black race or in the highest AA quantile (45{middle dot}6% and 48{middle dot}0%, respectively), and lowest among those with Native American race or in the highest AI quantile (37{middle dot}6% and 26{middle dot}7%, respectively). Conclusion. One-third of Hispanics/Latinos did not self-report race. Black or White self-reporting race did somewhat relate to AA or EA ancestry, respectively. HTN profiles were related to self-reported race and genetic ancestry in this admixed population.

Background Little evidence is available on the epidemiology of different knee injuries at a whole-of-population level. The objective of this article is to provide accurate estimates of knee injury incidence by harnessing the unique comprehensive, population-wide data of New Zealand's universal no-fault injury insurance provider, the Accident Compensation Corporation (ACC). Methods We obtained insurance claims data from ACC covering all knee injury insurance claims approved between 2015 and 2024. We calculated the number of injuries and the incidence rate per 100 000 population, by injury type, year, sex, ethnicity, and age. Results The total number of injuries increased from 184 710 (4 067 per 100 000 population) in 2015 to 244 155 (4 701 per 100 000) in 2024. The most common injuries were other/unspecified ligament sprains, contusions, and collateral ligament sprains. Ligament and cartilage injuries were more common for males than for females, while contusions were more common for females. Ligament tears and dislocations were more common in younger people (15 to 35 years of age), while cartilage injuries were more common at older ages (40 to 65 years). Discussion and Conclusions The rate of knee injuries observed in this study was higher than previously reported in other settings, probably due to broader coverage of injuries treated in primary and community care settings. A broad range of injuries were common, including those that have received less attention in the epidemiological literature to date. More research is needed on the prevention, burden, and outcomes of different knee injuries, beyond a narrow focus on cruciate ligament injuries.

Importance: Maternal vaccination and long-acting monoclonal antibodies are now available in the U.S. to prevent RSV. Long-acting monoclonal antibody administration in the U.S. commonly occurs after hospital discharge in outpatient settings, leaving some infants unprotected early in life when severe RSV risk is highest. Comparative effectiveness between the two interventions and whether delays affect effectiveness estimates have not been quantified. Objective: To evaluate the effectiveness of infant long-acting monoclonal antibody strategies and a maternal vaccination strategy, each compared to no intervention, and the comparative effectiveness of intervention strategies when accounting for real-world delays in monoclonal antibody receipt. Design: Cohort study using target trial emulation to compare four strategies for prevention of RSV-related outcomes. Setting: The U.S. between 2023 and 2025 using a nationwide database of employer-sponsored commercial insurance claims. Participants: 120,586 commercially insured mother-infants, whose infants were born in the U.S. during the 2023-2024 or 2024-2025 RSV season. Infants who could not be paired with their mother's record, did not enroll in commercial insurance within 75 days from birth, received palivizumab, and had an implausible birth date were excluded. Interventions: Comparison of four RSV prevention strategies: (i) maternal RSVpreF; (ii) long-acting monoclonal antibody given within the first week of life (mAb as intended); (iii) long-acting monoclonal antibody given within a six-month grace period from birth (mAb within grace period); and (iv) a control. Main outcomes and measures: Effectiveness against first RSV-associated hospitalization and medically-attended RSV illness was summarized using adjusted hazard ratios (aHR) and estimated using an inverse propensity weighting approach, with weights accounting for maternal age, maternal comorbidities affecting pregnancy, obstetric and newborn complications, season, region, and birth timing relative to October 1. A weighted Kaplan Meier estimator was used to estimate strategy-specific cumulative incidence of RSV outcomes over time. Results: In the first five weeks of life, the mAb within grace period strategy doubled the hazard of RSV hospitalization (aHR: 2.0 [95% CI: 1.0-4.9]) and increased the hazard of medically-attended RSV (aHR: 1.6 [95% CI: 1.0-2.7]) compared to the maternal RSVpreF strategy. The hazard for RSV hospitalization was similar for the mAb as intended strategy compared to the maternal RSVpreF strategy (aHR = 0.9 [95% CI: 0.3-1.9]). Conclusions and relevance: RSVpreF and monoclonal antibodies were similarly effective when monoclonal antibodies were administered close to birth, but when accounting for real-world delays in monoclonal antibody receipt, the maternal RSVpreF strategy was more effective than the mAb within grace period strategy.

Introduction Guatemala is the most populous country in Central America and a setting with unique opportunities for aging research. Approximately 40% of Guatemala's population is Indigenous Maya, who together speak 22 Mayan languages. Currently, there is no population-based aging study in Guatemala and few aging studies in Latin America among Indigenous populations. The Longitudinal Study of Aging in Guatemala (ELEGUA) aims to address these gaps by developing a nationally representative, population-based, longitudinal aging study modeled on the Health and Retirement Study and the Harmonized Cognitive Assessment Protocol, adapted to the cultural and linguistic context of Guatemala. The objective of this protocol is to describe the rationale and design of the ELEGUA pilot survey. Methods and analysis The ELEGUA pilot was a cross-sectional household survey of adults aged 40 years or older in Tecpan, Guatemala. Tecpan was chosen because its diverse population facilitated testing of study procedures in both Spanish and Kaqchikel, a common Mayan language. The survey included up to 600 households sampled using a multistage stratified cluster design. Within each household, one individual aged 40 years or older was selected, with oversampling of adults aged 55 years or older. This respondent completed a comprehensive questionnaire, including detailed cognitive tests, and provided physical measurements and a venous blood sample. Household respondents provided information on household economics and family structure, and an informant reported on the individual respondent's cognitive function. Data were collected using a computer-assisted personal interviewing system. Planned analyses include survey-weighted descriptive statistics and psychometric evaluation of the cognitive assessments. Ethics and dissemination Ethics approval was obtained from the ethics committees of the Institute of Nutrition of Central America and Panama, Maya Health Alliance, and the University of Michigan. Results will be disseminated through publications in peer-reviewed journals and presentations to local, national, and international audiences.

Background: Low-dose computed tomography (LDCT) screening reduces lung cancer mortality but is limited by low uptake and associated with high rates of false-positives and indeterminate-nodules. Breath volatile organic compound (VOC) analysis is a non-invasive candidate biomarker approach that could complement LDCT, but prior work has relied on laboratory-based high-resolution mass spectrometry (HRMS), limiting point-of-care deployment. Methods: In this pilot study, breath samples were collected from 40 patients with treatment-naive, pathologically confirmed non-small cell lung cancer (NSCLC) and 25 lung-cancer-screening-eligible healthy controls. Paired samples were analyzed via a compact point-of-care GC-MS platform (CLARION) and a laboratory HRMS reference. Diagnostic classification models were built independently for each platform using elastic net logistic regression with leave-one-out cross-validation, and performance was evaluated by area under the receiver operating characteristic curve (AUC). Results: CLARION identified 103 VOCs across breath specimens, compared to over 900 identified by HRMS. Despite this difference in panel size, CLARION achieved diagnostic performance nearly identical to HRMS for distinguishing NSCLC cases from controls (AUC 0.864 vs. 0.863). Compared to controls, performance statistics were similar for early-stage NSCLC (AUC 0.854 vs. 0.841) and adenocarcinoma (AUC 0.770 vs. 0.787). VOCs of interest include p-cymene, phenol, propylbenzene, tetradecane, {beta}-ocimene, 2,3-dihydro-indole, and 1-methylthio-(Z)-1-propene. Conclusion: A compact, point-of-care breath GC-MS platform achieved diagnostic performance for NSCLC detection comparable to a laboratory HRMS reference despite a substantially smaller detected VOC panel. These findings support continued development of point-of-care breath VOC testing as a non-invasive, field-deployable complement to LDCT-based lung cancer screening.

Background Severe acute respiratory infections (SARI) strain healthcare systems. Sentinel surveillance remains central to SARI monitoring, but routinely collected hospital discharge data offer a scalable, population-wide complement. In Finland, national registers now enable register-based surveillance, yet SARI case definitions remain unevaluated. Aim To evaluate whether routinely collected electronic health records can support register-based SARI surveillance and establish a national case definition. Methods We conducted a retrospective register-based study linking inpatient discharge data from the Finnish Care Register for Health Care (Hilmo) and laboratory-confirmed pathogen notifications from the National Infectious Diseases Register (NIDR). Admissions were aggregated into hospitalisation episodes using generic and pathogen-specific respiratory ICD-10 codes and linked to laboratory-confirmed respiratory pathogens within an admission-centred window. We assessed the impact of diagnostic coding position, laboratory linkage windows and alternative case definitions on age distribution, seasonality and epidemic trend detection. Results We included 145,435 respiratory hospitalisation episodes. Laboratory confirmations clustered around admission, and a -7-to-+3-day window was selected; 51,498 (35.4%) had a linked laboratory confirmation. Specific primary-position diagnoses preserved clear seasonality and age distributions consistent with SARI epidemiology, whereas secondary-position diagnoses showed attenuated seasonality. A combined case definition incorporating specific primary diagnoses and laboratory-supported syndromic episodes produced stable epidemic curves while improving sensitivity over laboratory confirmation alone. Conclusion National discharge and laboratory registers can support robust SARI surveillance in Finland when case definitions are carefully designed. A combined register-based definition balances specificity, sensitivity and feasibility, complementing sentinel surveillance and integrated respiratory monitoring. Keywords Severe acute respiratory infection (SARI); surveillance; electronic health records; ICD-10; case definition; Finland

Objectives To analyse the long-term effects of a cruciate ligament (CL) injury on health and socioeconomic outcomes. Methods We used a comprehensive national injury insurance database to identify CL injuries occurring in New Zealand between 2009 and 2022, and employed a doubly robust staggered difference-in-differences research design to identify the effects of these injuries on outcomes up to 10 years after injury. The outcomes of interest were healthcare use (hospitalisations, emergency department visits, medications, knee replacement surgery for osteoarthritis), associated healthcare costs, and labour market outcomes (employment rates, income, and government benefit payments). Results We identified 61 344 CL injuries for inclusion in the analysis. Over 10-year follow-up, a CL injury resulted in increased healthcare use (0.6 more hospitalizations [95%CI 0.4 to 0.7], 1.7 more days spent in hospital [95%CI 1.3 to 2.1], 0.4 more emergency department visits [95%CI 0.3 to 0.6], 2.5 more outpatient visits [95%CI 1.8 to 3.2], and 4.7 more medications dispensed [95%CI -1.8 to 11.2]) and public healthcare costs ($7 537; 95%CI 5 888 to 9 186), reduced income (-$6 060; 95%CI -11 644 to -475), and increased benefit payments ($1 152; 95%CI 542 to 1 761). Conclusion CL injuries have long-term impacts on healthcare use and socioeconomic outcomes. Strategies to reduce the incidence of CL injuries have the potential to realise large health and economic benefits.

Urban air pollution remains a significant public health concern, contributing to premature deaths and adverse health outcomes. However, there is little causal research evaluating the effectiveness of policies designed to improve air quality. This study assesses the impact of all three stages of London's Ultra Low Emission Zone (ULEZ) on air pollution, via PM2.5 levels, and respiratory health, via prescription records for bronchodilator and respiratory corticosteroid medications. Analyses are at general practice level, using a generalised synthetic control method to estimate causal impacts. Stage 1 was associated with a statistically significant but negligible 0.77% reduction in PM2.5 levels, with no corresponding change in prescribing. Stage 2 produced a paradoxical 2.69% increase in PM2.5, alongside a 4.44% decrease in inhaled corticosteroid quantity but a 12.51% increase in average daily quantity (ADQ) usage, suggesting a worsening of disease severity among existing patients. Stage 3 yielded a 2.69% PM2.5 reduction and a modest 2.18% decrease in bronchodilator ADQ usage. Spillover effects beyond the ULEZ boundary were statistically significant, but negligible. We find overall that the ULEZ had minimal effects on both air quality and respiratory prescribing across all three stages. These findings provide new insights into the effectiveness of ULEZ policies in reducing air pollution and its associated health impacts, suggesting the zone's effects are considerably smaller than previously reported, and that integration with broader policy measures may be necessary to achieve meaningful public health gains.

Wastewater-based epidemiology (WBE) has emerged as a powerful population-level surveillance tool, but its coverage is structurally concentrated in in-network urban areas, potentially leaving rural populations underrepresented. Routine human movement between sewered (in-network) and unsewered (off-network) areas may, however, cause wastewater treatment plant (WWTP) measurements to reflect infectious disease dynamics beyond sewer boundaries. We evaluated this hypothesis using daily clinical COVID-19 testing data (January 2021-April 2022) across New York State excluding New York City (NYC). We disaggregated weekly cases and tests into in-network (WWTP catchment area) and off-network (outside WWTP catchment area) components applied to two geographic frameworks: administrative counties (N = 53 mixed-coverage) and mobility-defined communities identified through Walktrap community detection applied to census tract-level movement networks (N = 32 mixed-coverage). In/off-network COVID-19 trends were strongly correlated under both frameworks. County-level statewide aggregate correlations were high (incidence r = 0.994, positivity r = 0.996), as were individual county correlations (median r = 0.909 and 0.932, respectively). Mobility-defined community-level statewide correlations were similarly strong (r = 0.990 and 0.992), with comparable unit-level medians (r = 0.877 and 0.894). The mobility-defined community framework provided better population balance between in-network and off-network strata (87.5% vs. 69.8% in balanced range) and a higher floor on representativeness (minimum r = 0.440 vs. 0.177). Population size was the dominant predictor of in-network/off-network alignment at both scales; wastewater infrastructure density and off-network signal variability provided additional explanatory power at the mobility-defined community level. WWTPs broadly represent COVID-19 dynamics in surrounding off-network populations, supporting their use as sentinel surveillance sites. Representativeness weakens in smaller, more rural communities, and mobility-defined communities provide a complementary framework for identifying where this occurs.

Forecasting influenza hospitalizations informs public health preparedness, yet questions remain about which types of forecasts best guide action. We evaluate categorical trend forecasts, which communicate probabilities of upcoming increases or decreases in epidemic trajectories, submitted to CDC's FluSight Forecasting Challenge between Fall-2024 and Spring-2026. Teams submitted probability distributions over five categories describing direction and magnitude of week-over-week changes in laboratory-confirmed influenza hospital admissions. We assessed performance using Ranked Probability Skill Score, Brier Skill Score, and measures of forecast-observation agreement. Most models outperformed an equal-probability baseline; the FluSight ensemble ranked among the top three in the 2024-25 and 2025-26 seasons. Forecasts were most accurate during stable periods and least during periods of rapid change, with most models underestimating observed trends. Conclusions were robust to choice of scoring metric and reference model. These results support categorical trend ensembles as an approach to communicating infectious disease forecasts that may inform public health decision-making.

Background Global labor migration from LMIC to higher-income destinations has expanded rapidly, placing increasing pressure on destination-country health. Existing research on cross-border migrant workers has focused largely on occupational health, general healthcare utilization, and disease-specific risks, while there is considerably less evidence on their sexual and reproductive health. This study contributes to this understudied field by examining the policy and health-system factors that shape the sexual and reproductive health services for migrant workers in Taiwan. Methods A qualitative study was conducted in Taiwan between November 2025 and August 2026. 22 stakeholders were purposively recruited from academia, healthcare, nongovernmental organizations, government, labor brokerage, and employers. Data were collected through semi-structured interviews and small focus groups. Interviews were conducted in Mandarin Chinese, transcribed verbatim, and translated into English. Data were analyzed using framework analysis combining deductive coding based on the AAAQ framework with inductive coding of implementation and contextual themes. Results Gaps were identified across all four AAAQ dimensions. Participants described limited migrant-responsive SRH programming; physical, financial, administrative, social, and information barriers; shortcomings in linguistic and cultural responsiveness; and weaknesses in interpretation, coordination, and continuity of care, despite generally favorable views of Taiwan's clinical quality. Conclusions Our findings show that broad insurance coverage and strong clinical capacity do not by themselves ensure the realization of migrant workers' SRHR. In Taiwan, rights were mediated through labor brokerage, gendered live-in work arrangements, and fragmented governance across health, labor, immigration, and social-welfare systems. Improving migrant SRHR therefore requires stronger implementation of existing protections, reduced dependence on informal intermediaries, and more integrated institutional responsibility for cross-sector migrant health needs.

Background: Vitamin K prophylaxis is universally recommended for newborns to prevent life threatening vitamin K deficiency bleeding. Although not on the immunization schedule, vitamin K prophylaxis is often coadministered with hepatitis B birth dose and erythromycin ophthalmic ointment, and rising hesitancy around vaccines/preventive care may spill over into vitamin K administration. Methods: We conducted a retrospective cohort study using Truveta electronic health record data with linked mother-child dyads. Live births to mothers aged 15-49 from January 1, 2019 through June 30, 2026 were included. Vitamin K administration was defined as documentation on the birth date or following day. Logistic regression assessed sociodemographic predictors of non-receipt, and interrupted time series analysis evaluated changes after January 2026. Results: Among 1,026,375 infants, 995,628 (96.97%) had documented vitamin K administration. Non-receipt increased from an average of 2.1% during 2019-2022 to 4.3% in 2025 and 6.1% in 2026, reaching 8.10% in June 2026. Older maternal age, non-Hispanic or Latino ethnicity, Medicaid or unknown insurance, and year of delivery were associated with greater odds of non-receipt. After January 2026, there was no immediate step change, but the odds of vitamin K receipt declined an additional 10% per month (OR: 0.90; 95% CI, 0.88-0.91). Conclusions: Vitamin K non-receipt increased over the study period and accelerated after January 2026. Because vitamin K recommendations were not changed by the January vaccine schedule, this association may reflect broader impacts to confidence in newborn preventive care. Future studies should examine causal mechanisms, parental decision-making, and associated clinical outcomes.

Background: Respiratory syncytial virus (RSV) remains a leading cause of hospitalization in infancy, with severe outcomes influenced by both contact patterns and passive immunity. Non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic suppressed RSV circulation and reduced opportunities for maternal immune boosting, potentially altering protection among newborns. We evaluated whether incorporating time-varying maternal immunity improves the ability of an age-structured transmission model to predict post-pandemic RSV hospitalization patterns in infants. Methods: We analyzed population-based RSV hospitalizations among Ontario (Canada) infants (<1 year) from July 2, 2017 to June 25, 2024, using linked administrative databases. A deterministic compartmental model across seven age classes was calibrated against pre-pandemic data using Latin Hypercube Sampling. We compared a model incorporating time-varying contact rates alone against a specification that additionally included time-varying maternal immunity. Results: Both specifications accurately reproduced pre-pandemic seasonality and macro-level post-pandemic resurgence features. The constant maternal immunity model showed slightly better accuracy in capturing the 2021/22 peak compared to the time-varying maternal immunity specification. However, both qualitatively captured the continued near-absence of RSV and the observed peak was captured within the 95% credible intervals. While both models precisely captured the timing and overwhelming surge of admissions that occurred in 2022/23, they failed to capture the premature peak timing and magnitude in 2023/24. Conclusions: Incorporating time-varying maternal immunity did not improve model accuracy post-pandemic. While maternal protection is essential for evaluating infant immunizations, population-level contact shifts primarily shaped post-pandemic RSV seasonality, indicating that models must account for these mechanisms of RSV transmission dynamics.

Communities exposed to flooding can experience markedly different mental health outcomes, yet conventional resilience indicators capture only part of the social and contextual conditions that may explain this variation. This study develops a multilevel and predictive framework for examining community resilience and depressive symptoms following flood exposure in Indonesia. Data were drawn from 20,303 respondents aged 15 years and older nested within 312 communities in the Indonesia Family Life Survey (IFLS-5). Depressive symptoms were assessed using the 10-item Centre for Epidemiologic Studies Depression Scale (CES-D-10), with Rasch Partial Credit Model calibration used to examine measurement properties. Bayesian multilevel models quantified between-community heterogeneity and assessed how far observable structural resources accounted for this variation. Community resilience was represented through two complementary constructs: structural resilience, based on observable socioeconomic and social-capital resources, and Latent Community Protective Capacity (LCPC), a model-derived proxy for residual contextual variation in depressive-symptom risk. Approximately 6 percent of variation was attributable to between-community differences, while observable structural resources explained only part of this heterogeneity. Structural resilience and LCPC were weakly correlated (r = 0.155). Moderation analyses provided no clear evidence that structural resilience altered the flood-depression association, while LCPC showed a directionally consistent but uncertain buffering pattern. Predictive models incorporating community-level information improved discrimination, with the best-performing model reaching an ROC-AUC of approximately 0.71. The findings suggest that observable resource-based indices provide an incomplete account of community-level mental health vulnerability and that residual contextual measures may provide complementary information, while requiring cautious interpretation and independent validation.

Background Rural-urban disparities in SARS-CoV-2 infection epidemiology remain poorly quantified and understood in Zambia despite differences in healthcare access, services and preventive interventions. This study examined the geographical distribution and associated factors of SARS-CoV-2 cases across selected rural and urban districts of Zambia. Methods A convergent mixed-methods study comprised of quantitative survey and qualitative interviews was conducted in; Ndola (Urban), Kafue (Peri-urban) and Lufwanyama (Rural). The proximate determinant framework guided variable selection and interpretation. Quantitative combined (Hospital-surveillance data with community survey), while qualitative included In-depth interviews. Participants were sampled using multistage sampling technique. Quantitative data were analysed using STATA version 17, while qualitative data were analysed thematically. Findings were integrated through triangulation. Results A total of 528 participants were included, with a median age 31 years (15-71). Overall SARS-CoV-2 positivity was 12.6%, varying across rural (16.5%), peri-urban (14.9%), and urban (9.9%) settings, though residence was not associated with infection (P<0.132). Participants aged [&ge;]49 years had significantly higher odds of infection (aOR=8.78; 95% CI:1.15-66.99), whereas secondary education (aOR=0.37; 95% CI:0.16-0.86) and hospital-based testing (aOR=0.37; 95% CI:0.15-0.92) were associated with lower odds of infection. Vaccine uptake was highest in urban areas but was not independently associated with infection. Qualitative findings revealed marked rural-urban differences in perceived susceptibility, testing access, vaccine decision-making, and adherence to preventive measures, explaining several quantitative observations. Conclusion SARS-CoV-2 infection across rural and urban settings in Zambia was influenced by demographic, behavioral, and health-system factors rather than geographic residence alone. These findings highlight the need for context-specific prevention strategies, equitable access to testing, strengthened community surveillance, and targeted risk communication to improve preparedness and response for future respiratory disease outbreaks.