Spatial and Spatio-temporal Epidemiology

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.

Abstract: Background: Children born very preterm (VPT) are at elevated risk for adverse neurobehavioral outcomes and are vulnerable to environmental exposures. We used untargeted metabolomics analysis to identify environmentally relevant metabolites associated with childhood behavioral problems and to characterize related endogenous metabolic pathways. Methods: We studied 226 children born <30 weeks gestation in a multi-site cohort study. Urine collected at age 4 was profiled using untargeted ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). Associations between 30 exogenous environmental metabolites and behavioral problems score at age 4 were evaluated cross-sectionally using multivariable linear regression, followed by metabolome-wide association and pathway enrichment analyses. Results: Three exogenous metabolites were nominally associated with child behavior problems. Specifically, 2-(Acetylamino)-3-( henylthiol)propanoic acid was positively associated with overall ({beta}=1.42, p=0.006), externalizing ({beta}=1.50, p=0.006), and internalizing ({beta}=1.34, p=0.021) behavior problems. Diethofencarb was positively associated with overall ({beta}=0.34, p=0.018) and externalizing ({beta}=0.39, p=0.010) behavior problems, while protocatechuic acid was inversely associated with internalizing problems ({beta}=-0.68, p=0.027). No associations remained significant after false discovery rate (FDR) correction. Nevertheless, these metabolites were associated with 151, 131, and 530 endogenous metabolic features, respectively, at FDR<0.05, highlighting perturbations in lipid metabolism, mitochondrial energetics, inflammatory signaling, amino acid metabolism, and neuroactive pathways. Conclusions: Environmental metabolites associated with behavior problems were linked to broad endogenous metabolic differences relevant to neurodevelopment. These findings highlight potentially modifiable environmental influences, including exposures related to combustion-derived pollutants, pesticides, and dietary sources, that may contribute to behavioral vulnerability among children born very preterm

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.

Background: Non-optimal air temperature increases the risk of preterm birth, but how temperature-related risks may translate into future population burden remains uncertain. We aimed to estimate the association between temperature and preterm birth in Sweden and assess how preterm birth burden may change under plausible future temperature conditions. Methods: We conducted a nationwide population-based cohort study of singleton births in Sweden from 1973 to 2018. Weekly mean temperature was assigned at the parish level according to maternal residence. Cox proportional hazards models with a distributed lag nonlinear model were used to estimate nonlinear and delayed associations between temperature and preterm birth. The estimated exposure response relationship and baseline hazards were then incorporated into an individual-based microsimulation of gestational progression under projected temperatures for 2025 to 2055. Future projections were examined across multiple climate models under SSP1-2.6 and SSP3-7.0 scenarios. Outcomes included the annual number and cumulative incidence of preterm births and the temperature-attributable fraction. Results: Among 4,338,825 singleton births, 211,397 (4.9%) were preterm. Temperature preterm birth associations were modest overall. The clearest increase in hazard was observed following exposure to very low temperatures, particularly -10C at short lags. Higher temperatures showed no clear increase in risk. From 2025 to 2055, the annual cumulative incidence of preterm birth and the temperature-attributable fraction was expected to remain broadly stable, with limited differences between emissions scenarios. In contrast, the absolute number of preterm births was expected to over the projection period, primarily reflecting increases in the projected number of pregnancies rather than substantial changes in temperature-associated risk. Conclusions: Very low temperatures were associated with a modest short-term increase in preterm birth risk in Sweden, hot temperatures showed little evidence of increased risk. Applying these associations to future climate conditions suggested limited changes in preterm birth incidence or the proportion attributable to temperature through 2055. However, the absolute burden of preterm birth may increase as the population at risk grows. This highlights the importance of considering demographic change alongside climate projections when assessing future maternal and neonatal health burden.

Abstract Background Air pollution contributes substantially to morbidity and mortality in low-income countries, where reliance on solid fuels leads to high levels of household exposure. Colonisation of the upper respiratory tract by Streptococcus pneumoniae is a prerequisite for pneumococcal disease, and inhaled air pollutants may influence colonisation through impaired mucociliary clearance. Therefore, we investigated the association between S. pneumoniae colonisation and personal exposure to particulate matter (PM2.5) and carbon monoxide (CO) as well as temperature and relative humidity in older children in The Gambia. Methods We conducted a prospective study of 134 children aged 5-14 years across eight visits in rural Gambia. Personal 24-hour PM2.5, CO, temperature and relative humidity exposures were measured using personal monitors. Concurrently, combined nasopharyngeal/oropharyngeal swabs were collected at each visit, and S. pneumoniae colonisation was determined by microbiological culture. Mixed-effects logistic regression models were used to examine associations between environmental exposures and colonisation. Exposures were additionally decomposed into between-child and within-child components. Models were adjusted for age, season, and household income tertile. Results A total of 554 child visits with paired exposure and microbiological data were analysed. Overall, 24-hour geometric mean PM2.5 and CO were 12.6 {micro}g/m3 (95% CI 12.2-13.1) and 0.16 ppm (95% CI 0.14-0.19) respectively and overall S. pneumoniae colonisation prevalence was 39.7%. In conventional models, PM2.5, CO, temperature, and relative humidity were not significantly associated with S. pneumoniae colonisation after adjustment for confounders. In the within-between decomposition analysis, higher between-child temperature exposure was consistently associated with lower odds of colonisation (mutually adjusted model: OR 0.74, 95% CI 0.56-0.98; p = 0.034). Relative humidity showed an inverse within-child association in crude analysis (OR 0.70, 95% CI 0.52-0.93; p = 0.013), which attenuated after adjustment for season and other confounders. No associations were observed for PM2.5 or CO exposures. Conclusion At the exposure levels observed in this cohort of older children, PM2.5 and CO exposures were not independently associated with S. pneumoniae colonisation. The pattern observed for temperature suggests that longer-term temperature conditions may be more relevant to pneumococcal colonisation than short-term exposure variation in this setting.

PurposeTo examine the association between BMI-for-age z-score (BAZ) and BMI status with refractive error prevalence, incidence, subtypes, and quantitative refraction in Vietnamese schoolchildren. MethodsWe retrospectively analyzed body mass index and refractive error data from annual school health checks in three Vietnamese cities, 2022 to 2024. The main analysis set was restricted to children age 6 and older (49,415 examinations, 31,522 children). Refractive error subtypes and quantitative refraction came from a Hanoi autorefractor sub-cohort (13,059 examinations). We used sex-stratified Poisson models with generalized estimating equations, adjusted for age, city, and year, plus linear mixed models for quantitative outcomes. ResultsAny refractive error followed a U shaped curve across BAZ in both sexes, significant in girls (prevalence ratio 1.01 per 1-SD BAZ, p = 0.027) but not boys (p = 0.099). Obesity was associated with higher any refractive error prevalence in girls (adjusted prevalence ratio 1.05, p = 0.017). Astigmatism was associated with BAZ in both sexes (p < 0.001), anisometropia in boys only (p < 0.001), with no association for myopia or hyperopia. Spherical equivalent shifted slightly toward hyperopia, not myopia, with higher BAZ. A supplementary check over 1 to 2 years found no evidence that prior BAZ predicted new refractive error onset (prevalence ratio 1.02, p > 0.6 in both sexes), and the nonlinear pattern did not reappear. ConclusionsAdiposity relates cross-sectionally to refractive error in a nonlinear, sex specific way concentrated in astigmatism and anisometropia rather than myopia, though this did not hold up short term.

Community-led urban greening may contribute to neighborhood safety, but its relationship with crime remains uncertain. We examined whether Keep Indianapolis Beautiful Project GreenSpaces in Indianapolis were associated with changes in violence and total crime. We used a matched-pair difference-in-differences design comparing funded sites with matched unfunded applicant sites. The primary analysis included 29 matched pairs with two years of pre- and post-grant follow-up. Monthly Part I violent offenses and total crime within 600-m buffers were modeled using Poisson pseudo-maximum likelihood. In the first post-grant year, the violent-crime estimate was lower but imprecise (IRR, 0.903; 95% CI, 0.805-1.014). In the second post-grant year, the relative rate was lower (IRR, 0.830; 95% CI, 0.718-0.961). Total crime estimates showed no clear post-grant change. Additional analyses indicated some sensitivity to spatial scale, but no sustained divergence in pre-grant crime patterns. Analyses of short-term crime dependence showed clear month-to-month persistence in violent crime within sites but limited evidence of stable spatial dependence across nearby sites. Therefore, within the two-year post-grant period examined, Project GreenSpaces was associated most consistently with lower relative violent-crime rates in the second year, while no corresponding decrease was observed for total recorded crime. Longer follow-up is needed to determine whether these patterns persist or change as projects mature.

Background: Cardiovascular disease is an important competing cause of death in men with metastatic prostate cancer, and ambient air pollution may increase cardiovascular vulnerability. We evaluated associations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) with all-cause, cardiovascular, and prostate cancer-specific mortality, including joint associations with androgen deprivation therapy (ADT). Methods: We analyzed 33,384 men from 11 US state registries diagnosed with metastatic prostate cancer during 2000-2015 and followed through 2018. Residential PM2.5 and NO2 concentrations at diagnosis were assigned using 1-km exposure models. Multivariable Cox models estimated all-cause mortality, and inverse-probability-weighted Cox models assessed cause-specific mortality. Results: Each interquartile-range increase in PM2.5 was associated with higher cardiovascular mortality (HR 1.04, 95% CI 1.02-1.07; p-trend=0.008). Cardiovascular mortality was also higher in the fourth and fifth PM2.5 quintiles versus the first (HR 1.18 and 1.21, respectively). Higher NO2 was associated with prostate cancer-specific mortality in the highest quintile (HR 1.07, 95% CI 1.01-1.13). In joint analyses, ADT-treated men with high versus low PM2.5 exposure had higher cardiovascular mortality (HR 1.19, 95% CI 1.05-1.34), without clear evidence of effect modification (p-interaction=0.051). Conclusions: In men with metastatic prostate cancer, higher PM2.5 exposure was associated with cardiovascular mortality, particularly among ADT-treated patients, supporting further study of environmental exposures and systemic therapy in cardio-oncology.

OBJECTIVE To assess associations of ambient UV with cardiovascular and cancer mortality across US Health Service Areas (HSAs), prioritise outcomes by signal and attributable burden, assess racial and ethnic variation, with UK Biobank corroboration. DESIGN Ecological analysis of HSAs using linear regression of crude mortality on ambient UV and social vulnerability, with correction for multiple comparisons. SETTING US HSAs and UK Biobank. DATA SOURCES Publicly available US data and UK Biobank data accessed under Application 82526. PARTICIPANTS 704 808 annual cardiovascular deaths (aged [&ge;]65) and 565 287 annual cancer deaths (aged [&ge;]50) from populations of 52.8 and 115.2 million; UK Biobank analyses included 412 665 individuals. MAIN OUTCOME MEASURES Cardiovascular, all-cancer, and body-site-specific cancer mortality; regression slope per interquartile-range increase in UV ({beta} UV/IQR), modelled attributable burden for US data, and hazard ratios for the UK Biobank data. RESULTS Higher UV was associated with lower cardiovascular ({beta}UV/IQR -68.3 deaths/100 000; P<0.001) and all-cancer mortality (-43.2; P<0.001), corresponding to 36 043 (5.1%) and 49 789 (8.8%) fewer US deaths annually, respectively. Associations varied by race and ethnicity. Cardiovascular findings were directionally consistent between US and UK datasets. All-cancer mortality and 10 of 18 cancers were inversely associated with UV in the US; UK analyses found inverse associations for all-cancer and two individual body-site-specific cancers. Twelve cancers showed directionally concordant associations across the datasets, of which ten were inverse. Lung cancer showed the strongest inverse association in each dataset. CONCLUSIONS Higher UV was associated with lower cardiovascular and cancer mortality across US HSAs, with modelled attributable burdens exceeding 5%; UK Biobank findings provided partial corroboration. Twelve of 18 site-specific cancers were directionally concordant between datasets. US race-stratified heterogeneity did not follow a skin-colour gradient, suggesting residual confounding.

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

Researchers must often rely on observational data to draw conclusions about the causal relationship between an exposure and an outcome. This is common in environmental epidemiology research, where the assignment to an exposure can be unethical or impossible. Consider a setting in which we seek to estimate excess mortality during heat waves, but are unable to randomize individuals to moderate or extreme heat. We propose to follow a causal framework for non-randomized time series that uses what we call historical time series matching to construct hypothetical randomized experiments, in which background covariates are balanced. We applied this framework and assessed the following causal question: Are daily mortality counts among elderly Americans higher during hot versus warm summer time periods? We addressed this causal question by drawing frequentist, Fisherian, and Bayesian inferences for five American cities. We estimated the average treatment effect of heat on three-day mortality with 95% Fisherian intervals to be 0.5 [-3.6, 4.4] deaths in Pittsburgh, 3.7 [0.7, 6.6] deaths in Seattle, 12.5 [6.1, 18.9] deaths in Chicago, 8.5 [1.4, 15.6] deaths in Los Angeles, and 20.3 [11.2, 29.5] deaths in New York.

Background: The incidence of early-onset colorectal cancer (EOCRC), defined as CRC diagnosed age <50, is rising in the United States and is the leading cause of cancer death in among those with early-onset cancer. Epigenetic exposure signatures based on methylation risk scores (MRS) offer a novel approach to identify long-term exposures that may contribute to EOCRC risk. We sought to replicate findings from a recent study in a racially and geographically diverse CRC cohort. Methods: We computed weighted MRS across lifestyle, air pollution, and pesticide exposome traits in 146 participants from the Disparities and Cancer Epidemiology (DANCE) cohort, a diverse population-based CRC study, applying the Maas et al. (2026) framework to tumor tissue. Associations between MRS and age at CRC onset (EOCRC, n=29; intermediate-onset (IOCRC) 50-64 years, n=69; late-onset, [&ge;]65 years, n=48) were evaluated using linear and polytomous regression, with adjustment and stratification for race, geography, Area Deprivation Index (ADI), and Multi-Environmental Exposure Index (MEEI). Spearman correlations were calculated between MRSes and observed exposures. Results: EOCRC cases were predominately Black (65.5% vs. 31.3% among LOCRC) and resided in higher-deprivation neighborhoods. We found higher odds of EOCRC associated with epigenetic exposure signatures for 2,4-D herbicide, heptachlor, coarse particulate matter (PM), Mediterranean Diet Score, and smoking, and borderline associations for fine PM and nitrogen dioxide. IOCRC was associated with signatures for 2,4-D, lindane, and obesity. Heterogeneity was observed by race and area-level factors, though associations were largely consistent across strata. ADI and MEEI were correlated with multiple pesticide and pollutant epigenetic signatures. Conclusions: In a diverse US cohort, epigenetic exposure signatures distinguish CRC cohorts, particularly EOCRC from later-onset disease, with associations consistent with but not identical to previous research. EOCRC in DANCE was characterized by higher epigenetic exposure signatures for air pollution, smoking, and distinct pesticide exposure profiles. IOCRC had overlapping characteristics with early- and late-onset and were the only group with a significant obesity signature. These findings support the hypothesis that exposome-driven epigenetic changes contribute to EOCRC risk and highlight the importance of studying diverse populations to characterize the full spectrum of environmental risk factors.

Background Staying physically active is essential for healthy ageing. Exposure to high levels of air pollutants such as particulate matter (PM) is associated with less active, more sedentary lifestyles in older adults. Whether results extend to typical fluctuations in daily PM exposure is unclear. We examined associations of higher-than-usual personal exposure to PM (PM2.5 and PM10) with next-day movement behaviour in older adults, assessed using concurrently worn personal air quality monitors and accelerometers. Methods The present study used 304 days of data from 67 adults aged 50-85 years living in the UK. For five days, participants wore accelerometers 24-hours per day and personal air quality monitors during waking hours. Average daily time spent in movement behaviours (moderate-to-vigorous physical activity [MVPA], light physical activity [LPA], sedentary behaviour [SB]) and step count was extracted from accelerometers, and average daily exposure to PM2.5 from personal air quality monitors. PM10 was examined in secondary exploratory analyses. We used linear mixed models to examine within-person associations of deviation from usual PM exposure with next-day movement outcomes, with estimates presented for 'usual' (individual mean) and 'higher-than-usual' (+1 interquartile range, equivalent to 2.6 g/m3 beyond individual mean PM2.5 exposure and 2.8 g/m3 beyond individual mean PM10 exposure) exposure. Analyses were repeated using area-based PM estimates. Results Compared with usual exposure, higher-than-usual PM2.5 was associated with 8 minutes less LPA (95% CI=-14 to -2) and 483 fewer steps (-855 to -82) on the following day. Exposure to higher than usual PM10 was associated with 8 minutes less LPA (-13 to -3), 8 minutes more SB (0 to 15), and 412 fewer steps (-739 to -85) on the following day. There was no association with MVPA, and no associations when area-level PM estimates were used as opposed to estimates from personal air quality monitors. Conclusions Typical daily variability in PM exposure in a setting with relatively low overall PM levels was associated with modest next-day differences in movement behaviour in older adults. Higher-than-usual PM exposure was associated with less next-day activity and more sedentary time. Personal monitoring may be important for capturing short-term exposure-behaviour associations. Trial registration N/A

Tick-borne disease risk reflects the combined influence of vector abundance, pathogen prevalence, human exposure, and seasonal activity, yet these components are rarely integrated at the county level. We developed species-specific ecological risk scores for three medically important tick species (Acari: Ixodidae): Amblyomma americanum (L.), Dermacentor variabilis (Say), and Ixodes scapularis Say, across all 102 Illinois counties using data from 2019 to 2022. County-level predicted tick abundance and pathogen prevalence were scaled and combined using equal weights to generate primary vector-level risk scores. Robustness to the equal-weight assumption was evaluated by systematically varying the relative weights assigned to abundance and pathogen prevalence, while a separate sensitivity analysis incorporated reported tick-bite incidence where available. Associations with human disease were evaluated using negative binomial regression of tick-borne disease case counts on the corresponding risk scores, with county population included as an offset. Monthly phenology indicators were constructed by integrating human disease cases, reported tick bites, and sampled tick abundance and were evaluated in relation to temperature and precipitation. Seasonal risk was estimated by combining county-level vector risk with species-specific monthly phenology, generating monthly risk surfaces that were deployed through an interactive R Shiny application. Higher risk scores were significantly associated with greater disease case rates for each tick species. County rankings were highly stable under moderate changes in abundance and prevalence weighting. Seasonal activity differed among species, with A. americanum and D. variabilis showing concentrated warm-season risk and I. scapularis exhibiting a broader seasonal profile. These county-level seasonal risk maps identify where and when relative tick-borne disease risk is elevated in Illinois, supporting targeted prevention, surveillance, and clinical awareness.

Nitrogen dioxide (NO2) is a widespread air pollutant associated with the risk and prevalence of various respiratory infectious diseases. Epidemiological studies have reported associations between NO2 exposure and COVID-19 incidence, and biological evidence indicates that NO2 exposure increases vulnerability to infection. Motivated by these findings and by the scarcity of mechanistic epidemic models that incorporate air pollutant data, here we introduce an NO2- and mobility-informed metapopulation model and study the first COVID-19 wave in Oklahoma. County-level NO2 concentrations enter the infection rates through a first-order parameterization, alongside high-resolution mobility patterns capturing heterogeneous inter-county connectivity. Using numerical simulations, we demonstrate that higher environmental sensitivity produces earlier and more synchronized outbreaks across counties, while lower sensitivity yields delayed, asynchronous trajectories. When fitted to county-level COVID-19 incidence data, our model outperformed the classic SIR model (fitted independently in each county) in over 75% of counties in Oklahoma across all standard error metrics. The improvements were even more pronounced in forecasting tasks across epidemic stages, with county-level win rates against the SIR model of 59.74% (surge), 87.01% (peak), 80.52% (post-peak), and 88.31% (decline) by nRMSE. To isolate the contribution of NO2, we compared our model against a mobility-only model with NO2 removed and homogeneous infection rates across counties. The NO2 term improved county-level forecasts during the surge (94.81% of counties by nRMSE), post-peak (88.31%), and peak (62.34%) stages, though not during the early and decline stages, suggesting that NO2 information can generate better forecasts than mobility alone during periods of high incidence. Our results demonstrate that environmental exposure can enter the transmission structure of a mechanistic epidemic model directly and that doing so yields measurable forecasting gains.

Background Under-five mortality remains a major public health challenge in Zambia despite substantial reductions over recent decades. Demographic and Health Survey (DHS) data are commonly analysed using Cox proportional hazards models; however, violations of the proportional hazards assumption and unobserved cluster-level heterogeneity may compromise inference. This study compared advanced survival modelling approaches to determine the most appropriate framework for analysing under-five mortality using pooled Zambia DHS data. Methods We conducted a pooled secondary analysis of the 2018 and 2024 Zambia Demographic and Health Survey child recode datasets. The analysis included 9,982 children, among whom 266 died before their fifth birthday. A survey-weighted Cox proportional hazards model was fitted as the reference model and assessed using Schoenfeld residual diagnostics. To address identified methodological limitations, an extended Cox model, a shared-frailty model, and a Bayesian survival model were subsequently fitted. Model performance, assumptions, and the consistency of adjusted hazard ratio estimates were compared across modelling approaches. Results The global Schoenfeld test indicated violation of the proportional hazards assumption ({chi}2=51.26, p=0.002). In the adjusted extended Cox model, male children had higher mortality risk than females (aHR 1.95, 95% CI 1.40-2.73), while children with gestation [&ge;]9 months had lower mortality risk than those with shorter gestation (aHR 0.21, 95% CI 0.14-0.32). Average and large birth size were associated with lower mortality compared with small birth size (aHR 0.47, 95% CI 0.34-0.66 and aHR 0.57, 95% CI 0.39-0.84, respectively). Newborn health checks before discharge were associated with lower mortality (aHR 0.50, 95% CI 0.38-0.66), as was any antenatal care (aHR 0.25, 95% CI 0.09-0.75). A high-risk fertility pattern involving fourth or higher births with an interval [&ge;]24 months was also associated with lower mortality (aHR 0.57, 95% CI 0.41-0.80). The shared-frailty model produced similar estimates, including increased mortality among male children (aHR 1.39, 95% CI 1.08-1.78) and twins or multiple births (aHR 2.74, 95% CI 1.36-5.53). Bayesian estimates were broadly consistent with the extended Cox model. Conclusions Advanced survival models provided a more robust analytical framework than the conventional Cox model for evaluating under-five mortality in nationally representative DHS data. While the extended Cox model accommodated time-varying effects, the shared-frailty model captured unobserved cluster-level heterogeneity, and the Bayesian model confirmed the stability of parameter estimates. Incorporating these complementary approaches can improve the validity of survival analyses and strengthen evidence for child survival research and policy in low- and middle-income settings.

Background Short-term weather conditions can trigger paediatric hospital admissions, but evidence remains limited on the health relevance of intraday temperature variability, humidity, and precipitation, and generally on which subgroups are most susceptible. Methods We conducted a nationwide case time-series study of Swedish children and adolescents aged 6-18 years using linked register data. Associations between daily mean temperature, intraday temperature variability, relative humidity, and precipitation and inpatient hospitalisations were estimated with Poisson regression (individual fixed effects) combined with distributed lag non-linear models over lags 0-21 days. Outcomes included all-cause hospitalisation and cause-specific admissions. Effect modification was examined by sex, age group, socioeconomic indicators, region, and calendar periods. Findings Among 4,638,247 children and adolescents in the cohort, 1,070,702 (23.1%) experienced at least one inpatient hospitalisation, contributing 1,736,169 hospitalisation events. All-cause hospitalisation increased with higher mean temperature, with risk highest at hot extremes. Intraday temperature variability showed a U-shaped association, with higher rates at both lowest and highest exposure levels. Relative humidity showed no association with hospitalisation risk. Higher precipitation was associated with increased hospitalisation risk, but estimates at high rainfall levels were imprecise. Stratified analyses indicated modest differences by sex and socioeconomic indicators, but clearer heterogeneity by age and region, with the highest risks among younger children and in East Sweden; associations varied across calendar periods and were imprecise for most cause-specific outcomes. Sensitivity analyses mostly showed that the main curve shapes were robust. Interpretation Short-term exposure to hot temperatures, both low and high intraday temperature variability, and higher levels of precipitation were associated with an increased risk of all-cause hospitalisation among children in Sweden, with clearer variation by age group and region than by sex or socioeconomic position. These findings support targeting paediatric climate-health preparedness and early-warning systems toward younger children and higher-risk regions such as eastern Sweden and extending such systems beyond mean temperature to include intraday temperature variability, a distinct, currently overlooked driver of risk that heat-focused systems are not designed to capture. Fundings This research was funded by Formas the Swedish Research Council for Sustainable Development (grant no. 2023-01774 and 2022-01845) and the Swedish Research Council (2025-02804 and 2022-06599).

Objective: Environmental pollutants are increasingly recognized as potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet the effects of mixed exposures and underlying mechanisms remain unclear. We evaluated associations between environmental chemical mixtures and MASLD and the mediating role of inflammation-related biomarkers. Methods: We analyzed 60 environmental chemicals across six categories among 39,061 U.S. adults from the National Health and Nutrition Examination Survey (NHANES) 1999-2020. Principal Component Pursuit with Principal Component Analysis (PCP-PCA) identified latent exposure patterns. MASLD was identified using multisociety Delphi consensus criteria and the Hepatic Steatosis Index (HSI [&ge;] 36). Logistic regression, restricted cubic spline models, and mediation analysis were applied. Results: PCP-PCA generated 5-17 dimensions per chemical category, with first-dimension variance contributions ranging from 30.70% to 98.88%. Six dimensions from four categories were retained, with phthalate esters (PAEs) and organophosphate flame retardants (OPFRs) showing the most consistent associations with MASLD. PAEs Dim.1, explaining 90.71% of variance, showed a significant non-linear dose-response association (P-nonlinear = 0.0001). Significant associations were identified for mono-isobutyl phthalate (MiBP; OR 1.12, 95% CI 1.07-1.19), mono(carboxyoctyl) phthalate (MCOP; OR 1.08, 95% CI 1.02-1.14), mono(carboxynonyl) phthalate (MCNP; OR 1.12, 95% CI 1.03-1.21), and bis(1,3-dichloro-2-propyl) phosphate (BDCP; OR 1.15, 95% CI 1.08-1.23). C-reactive protein (CRP) and red cell distribution width (RDW) were the primary mediators, accounting for 32.42% and 19.62% of the MiBP-MASLD association, respectively (both p < 0.0001). Conclusion: Environmental co-exposure, particularly to PAEs and OPFRs, was associated with higher MASLD risk, with systemic inflammation potentially contributing to these associations.

Objective: to estimate reconsultation risk and trajectories after a new episode of musculoskeletal pain in children and young people (CYP), and to determine routinely recorded prognostic factors associated with reconsultation. Design: Population based retrospective cohort study. Setting: Clinical Practice Research Datalink (CPRD) Aurum, 2005-2021. Participants: CYP aged 8-18 years consulting primary care for a new musculoskeletal pain episode (no musculoskeletal consultation in prior 12-months). Main Outcome Measures: Musculoskeletal pain reconsultation within 12-months, and 3-year musculoskeletal reconsultation trajectories derived using latent class growth analysis. Prognostic factors selected from a literature search and two-year symptom histories (sample prevalence >1%) were examined using regression models (conditional logistic; multinomial). Results: Among 313,830 CYP with >12 months' follow-up, 32% reconsulted for musculoskeletal pain within 12 months. Among 240,384 CYP with >3 years' follow-up, three trajectories were observed: single episode (62%), early reconsultation (18%), and persistent reconsultation (20%). Older age; female gender; hip, knee, multisite and back pain on index; previous headache; previous abdominal pain; and analgesic prescribing were associated with higher reconsultation risk. Asian or Black ethnicity, and residing in more deprived areas, were associated with lower recorded reconsultation. Conclusion: Most CYP had no further recorded consultation, but 38% followed early or persistent reconsultation trajectories. Routinely recorded prognostic factors, particularly index pain side and prior pain/symptom history, may differentiate groups who could benefit from proactive follow-up. Lower recorded reconsultation among Asian and Black individuals, and living in more deprived areas, should not imply lower need and warrants equity-sensitive monitoring of access, health-seeking, and coding.

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.