Spatial and Spatio-temporal Epidemiology

Introduction Louisiana ranks last in the United States of America in terms of maternal health outcomes. Previous works have highlighted the impact of some social determinants of health on the incidence of adverse birth outcomes. These works have subjectively selected specific social determinants of health from larger datasets. Here, we attempt to replicate their results with objective variable selection techniques. Methods By deriving principal components from the Agency of Healthcare Research and Quality's parish-level social determinants of health dataset, we were able to objectively find social determinants of health associations instead of the conventional subjective variable selection approach. Then, we applied Bayesian linear mixed-effects models to calculate more conservative parameter estimates about the effects of social determinants of health on adverse birth outcome incidence. Then, we used local Moran's I to identify clusters of spatially autocorrelated parishes. Finally, we combined the results of these two methods and inspected the relationship between important predictors and clusters of spatial autocorrelation. Results We identified several significant effects on the incidence of adverse birth outcomes, including populational composition and economic attainment, and several clusters of high and low incidences of adverse birth outcomes in Louisiana. There was also a concordant relationship between important predictors from our predictive models and the cluster assignments of Local Moran's I. Conclusion Our results validate previous works in the subject area and hold implications for precision development of maternal health interventions in Louisiana.

Background. Young sexual and gender minorities of color face compound health risks shaped by interlocking systems of racism, cisgenderism, and class inequality. Spatial health research documents that place shapes health, but existing methods cannot specify the mechanisms through which spatial configurations produce different health outcomes for differently positioned people. This gap prevents targeted intervention. ObjectiveTo develop and pilot test the Spatial Intersectionality Health Framework (SIHF), which specifies three mechanisms through which space produces intersectional health inequities: Layered (multiple oppressive systems activating simultaneously), Positional (the same space producing different health pathways by intersectional position), and Conditional (nominally protective spaces carrying hidden costs for specific positions). We also introduce and validate Intersectional Geographically-Explicit Ecological Momentary Assessment (IGEMA) as the methodology operationalizing SIHF across three data levels. MethodsThe GeoSense study enrolled 32 young sexual and gender minorities of color (ages 18-29) in New York City. IGEMA was implemented across three integrated levels: (1) GPS mobility tracking via participants personal smartphones, linked to census tract structural exposure indices across n=19 participants; (2) ecological momentary assessment of intersectional discrimination with multilevel modeling of mood, stress, and sleep outcomes; and (3) map-guided qualitative interviews with SIHF mechanism coding and intercoder reliability assessment across 92 coded records from 18 participants. This study was conducted as the pilot for NIH R01HL169503. ResultsAll three SIHF mechanisms were empirically detectable. A compound structural gendered racism index outperformed every single-axis alternative in predicting daily mood (b=-0.048, p=.001) and stress (b=0.121, p<.001). The Positional mechanism accounted for 71% of coded harm experiences. Intercoder reliability for mechanism assignment reached kappa=0.824 at Stage 2 reconciliation. Daily intersectional discrimination predicted greater sleep disturbance (b=1.308, p=.004). ConclusionsSIHF and IGEMA together provide an empirically testable framework for specifying how space produces intersectional health inequities. Mechanism specification, not spatial location alone, is the condition for designing research and intervention that reaches the source of harm for multiply marginalized populations.

Sylvatic Yellow Fever (YF) is an infectious mosquito-borne disease with significant epidemiological relevance due to its widespread distribution and high lethality for human and non-human primates, particularly in tropical regions of the planet such as in Brazil. Identifying regions and periods of high environmental suitability for the occurrence of YF is essential for preventing or mitigating its burden, as it enables the efficient allocation of surveillance efforts, prevention, and implementation of control measures. Environmental modeling of YF occurrence has proven to be an effective approach toward this goal; however, its effectiveness strongly depends on the modeling framework's capabilities as well as the spatial and temporal precision of all associated data. We propose a fine-scale geospatial modeling of YF environmental suitability that is based on a generative machine-learning ensemble method built on a large set of high-resolution environmental covariates. First, we take the spatiotemporal statistical description of the environment of each of the 545 YF cases from 2019--2024 up to 30 m/monthly resolution at three buffer scales: 100 m, 500 m, and 1000 m ratios. Then, we perform a feature selection and train hundreds of One-Class Support Vector Machine submodels to form a robust ensemble model, whose predictions are projected to a 1x1 km resolution grid of Brazil under several metrics, exceeding seven million ensemble evaluations. The predictions ranked the Southern Brazil region with the highest mean suitability for YF, with a level of 0.64; Southeast comes next with 0.46, followed closely by Central-West region (0.44), North (0.39), and finally Northeast (0.28). The model exhibited high uncertainty for the North region, indicating that data collection efforts are much needed in this region. As for the environmental covariates, a feature analysis pointed out that Land use and cover accounts for the largest influence in the model output.

Recognizing the challenges faced by primary caregivers regarding the health of children with congenital craniofacial anomalies (CCAs) contributes to strengthening healthcare programs according to patient[s] and families differential needs. This qualitative study presents the experiences of 25 caregivers of children with CCAs from Bogota and Cali, Colombia, identified from care registries and consultation statistics provideed from public high-complexity healthcare institutions. Grounded in Giorgis descriptive phenomenology and employing thematic analysis, this research utilized semi-structured interviews and focus groups to explore the diagnostic process and its impact, experiences with healthcare services, and the caregivers role and daily care activities. Data were analyzed using MAXQDA(R) qualitative software. Findings highlighted the emotional complexity of caring for childre[n]s health. Challenges included late diagnoses, pessimistic views of the children with CCAs condition by healthcare team members; lack of effective support, information, and guidance from health staff; absence of clear care and referral protocols, and limited access to specific adaptations and timely specialized care for children with CCAs. There were also reduced therapeutic services, and a pronounced gendered caregiving burden when responsibilities fall almost exclusively on mothers. System fragmentation, reflected in deficiencies in communication and a lack of clear, coordinated, and timely pathways of care, as well as the absence of adequate psychosocial support for families, emerged as common structural problems in healthcare services in both geographic settings where this research has been conducted. Gender-sensitive strategies focused on alleviating emotional concerns and the burden of caregiving from diagnosis onward within a patient and family-centered care model are decisive. Improving comprehensive CCAs training for healthcare personnel and making adjustments to care pathways are suggested to contribute to the implementation of inclusive health programs that address the diverse needs of children and their families.

As climate change intensifies, health risks from extreme heat are rising. Accurate assessment of heat vulnerability at high spatial resolution is crucial for developing effective adaptation strategies, particularly in socioeconomically heterogeneous urban settings. However, the identification of key indicators underlying heat vulnerability remains challenging. Using Chicago, Illinois (USA) as a case study, we systematically compare different variable selection strategies in community-level heat vulnerability assessments. We take the conventional unsupervised principal component analysis (PCA)-based Heat Vulnerability Index (HVI) as a baseline, and compare it with supervised approaches that incorporate variable selection, including machine learning algorithms (Lasso regression, Random Forest, and XGBoost) as well as traditional statistical methods (simple linear regression and polynomial regression). Using the vulnerability indicator subsets identified by each variable selection method, we construct multiple HVIs and evaluate their performance against heat-related excess mortality. Our work indicates that supervised variable selection improves the performance of HVIs in capturing heat-related health risks. Among all methods, the Random Forest-based variable selection algorithm achieves the best overall results, highlighting the potential of machine learning to enhance heat vulnerability assessment tools. Our results demonstrate that poverty rate, lack of air conditioning, and proportion of residents aged 65 and above are robust determinants of heat vulnerability in Chicago.

BackgroundThe rapid growth of the worlds urban population has contributed to the expansion of informal urban settlements in many cities across the world. In these settings, lack of safe sanitation combined with high population density and poverty contributes to heightened health risks for often vulnerable populations. The aim of this study was to evaluate the effect of a shared, onsite sanitation intervention on the nutritional status of children in Maputo, Mozambique. MethodsThe Maputo Sanitation (MapSan) trial was a controlled before-and-after study to evaluate the effect of a shared, onsite sanitation intervention on child health in Maputo, Mozambique. Here, we report the effects on childhood stunting, wasting and underweight, and height-for-age, weight-for-height and weight-for-age z-scores. Children were enrolled aged 1-48 months at baseline and outcomes were measured before and 12 and 24 months after the intervention, with concurrent measurement among children in a comparable control arm. The primary analysis was intention-to-treat. The trial was registered at ClinicalTrials.gov, number NCT02362932. ResultsWe enrolled 757 and 852 children in the intervention and control groups respectively. There was no evidence for an effect of the intervention on any outcome at 12 or 24 months of follow-up except for wasting where there was very weak evidence for an effect (adjusted prevalence ratio: 0.497; 95% CI: 0.22-1.11; p=0.09). In two exploratory analyses - one including only those children born into compounds post-intervention and a second excluding children in control compounds which had independently improved their sanitation facilities during follow-up - we found that stunting increased in the intervention group whilst wasting decreased. ConclusionsThis study contributes to the growing evidence on the role of sanitation in shaping child health outcomes in informal urban settlements. We found no evidence for an effect on stunting and weak evidence for an effect on wasting. More research is needed to understand how sanitation can reduce childhood undernutrition in complex urban environments.

Introduction Nontyphoidal Salmonella enterica (NTS) is a major zoonotic enteric pathogen. Animal contact-related NTS outbreaks have increased in the United States of America (U.S.) over the last decade. Geospatial analysis can identify locations with elevated risk of NTS outbreaks where public health authorities can focus their NTS prevention and intervention efforts. Methods We analyzed NTS outbreak data reported from individual states to the Centers for Disease Control via the National Outbreak Reporting System between 2009 and 2022 across the continental contiguous U.S. A geospatial analytical framework that included disease mapping, spatial interpolation, and global and local clustering methods was applied to identify regions with high NTS outbreak rates. Results A total of 104 NTS single-state outbreaks were reported to the National Outbreak Reporting System (NORS) during the study period. The mean annual incidence rate was 0.02 NTS outbreaks per million person-years. The primary animal contact categories associated with these outbreaks were mammals (cattle, pigs, sheep, and horses), birds (backyard chickens, ducklings, and turkeys), and reptiles (turtles and lizards). Exposure settings included farms, fairgrounds, agricultural feed stores, veterinary clinics, dairy/agricultural settings, and residential settings. The local cluster detection methods consistently identified areas with significantly high NTS animal contact-related outbreak rates in the Mountain West, Midwest, and Northeast of the US. Conclusion NTS animal contact-related single-state outbreaks revealed distinct spatial clustering across the United States, with potentially higher risks in the Mountain West, Midwest, and Northeast. Diversity of animal-contact sources and exposure settings depicted complex transmission dynamics of NTS. Focused prevention and control programs in these areas are needed to mitigate the burden of NTS outbreaks.

Introduction The aim of this study was to determine the annual age- and sex-specific prevalence of gender-affirming hormone and puberty blocker use among young people with a gender incongruence (GI) diagnosis in Norway. Methods We integrated data from multiple Norwegian national registers to perform a nationwide register-based study of individuals with known sex assigned at birth who were born in the period 1975-2017 and resident in Norway for all or part of the period 2008-2022. We first calculated the annual age- and sex-specific incidence of GI diagnoses in the population. Then, we calculated the annual age- and sex-specific prevalence of androgen, estrogen, and puberty blocker use among individuals with a GI diagnosis who were under age 25 (for androgens and estrogens) or 18 (for puberty blockers) in the year that they collected the prescription. Results The incidence of GI diagnoses has increased among youth in Norway, most notably since 2015 and with the largest increase among teens assigned female at birth. The prevalence of feminizing and masculinizing hormone therapy has increased in this period as well, but mainly among the oldest teens and young adults. The prevalence of puberty suppression is mostly low but has also increased since 2015, especially in recent years among teens assigned male at birth. Conclusion The prevalence of gender-affirming hormone and puberty blocker use has increased among transgender youth in Norway, concurrently with an increase in the incidence of GI diagnoses.

Scorpionism is a public health concern in warm regions, particularly affecting children under 10 years old. Timely treatment with antivenom, provided free by the Brazilian Unified Health System, at strategic care points (PEs) is crucial to prevent avoidable deaths. Our study focused on the Sao Paulo state (SP), which has the largest population in Brazil. The objectives were to adapt a network analysis method suited to SPs context; to assess the efficiency of the SP PE network coverage, considering the 90-minute response time; and to determine the ideal number of vials to be stored at each PE. After adapting the healthcare network analysis, we applied spatial coverage models to evaluate the adequacy of PE response times. We also estimated the demand for antivenom vials at each PE based on Notifiable Diseases Information System data from 2021 to 2023, which is currently limited to the state level. We identified 12 areas lacking coverage, of which only one was suitable for a new PE. The estimated serum requirements aligned with SP's current distributions. However, the estimation carried out according to the PEs has the advantage of reducing the risk of antivenom shortages, especially in emergencies, thus ensuring timely care to prevent avoidable deaths. Our adapted method and PE serum estimates can enhance the scorpion sting care system by supporting geographic planning and optimizing resource allocation. Moreover, these findings and methodologies have potential applicability to other Brazilian regions and warm countries facing similar challenges, contributing to improved access and outcomes for scorpionism victims.

Pulmonary embolism (PE) is a sudden blockage of lung arteries, usually caused by a blood clot that travels from the deep veins of the legs. As the world becomes more sedentary and lifestyle diseases emerge, deaths from PE are expected to rise in the next 20 years. For instance, the United States records annual deaths of 60 per 100,000 people. The degree to which these deaths are affected by demographic, socioeconomic and environmental predisposing factors as well as how they vary across time and space remains an open science question. In this paper, we conduct a detailed statistical and spatial-temporal study PE mortality counts across US counties from 2005 to 2022. Our study shows that study shows that PE mortality is not randomly distributed in space and time but concentrated in most counties in Arkansas, Mississippi, Kansas, Missouri, Oklahoma, Louisiana, Nebraska, Tennessee, and Texas. We also established that age is a statistically significant predictor (mean coefficient of 0.52) of PE mortality especially in counties of Mississippi, Kansas, Missouri, Tennessee, Illinois, Kentucky, Texas and Virginia. Our results thus provide empirical support for prioritizing regionally targeted PE prevention policies. Furthermore, the adopted county-level analysis uncovered granular geographic patterns that are usually obscured in state or national level analysis. Our study thus provides actionable evidence to support geographically tailored strategies aimed at reducing mortality by pinpointing counties with consistently elevated PE mortality risk at different timescales.

Dengue transmission is strongly influenced by climatic conditions that affect mosquito population dynamics and virus circulation. In Southern Brazil, where dengue historically occurred at low levels, recent climatic anomalies may be contributing to the expansion of Aedes vectors and an increase in local dengue incidence. This study investigated the spatiotemporal association between climatic variables, Aedes mosquito infestation and dengue cases in Porto Alegre (Southern Brazil, 2018 to 2025). Entomological, surveillance and climatic data were analyzed using Morans I and LISA for spatial association, Kendall correlation, polynomial regression and LASSO to identify relevant drivers and develop predictive models of mosquito infestation and dengue incidence. A strong spatial association between Aedes aegypti and Aedes albopictus was observed, with persistent local clusters detected across all years. Annual climatic variables were associated with mosquito abundance in several districts. Overall, rainfall frequency had a stronger effect on Aedes aegypti abundance than accumulated rainfall. Temperature and lagged infestation indices showed strong association with both species and dengue incidence, with effects observed up to four weeks prior. Predictive models demonstrated good agreement between observed and predicted values, particularly within low to moderate infestation levels. Lagged variables were consistently retained in both mosquito infestation abundance and dengue incidence models, highlighting the importance of temporal predictors for anticipating vector dynamics and dengue risk. This approach is generally applicable for predicting Aedes infestation and disease incidence and emphasizes the importance of integrating entomological and climatic surveillance data to improve anticipation and detection of dengue risk periods and support more effective public health interventions.

Detailed agent-based simulations are increasingly used to support policy decisions, but their computational cost and complex uncertainty structure make systematic scenario analysis challenging. We present a data-driven, uncertainty-aware decision support (DDUADS) workflow for using stochastic simulation models as decision-support tools under limited computational budgets. The approach combines several established techniques-sensitivity screening, Bayesian calibration using simulation-based inference, and multi-surrogate model integration for translational efficiency-into a coherent pipeline that enables uncertainty-aware policy analysis. Rather than producing a single baseline, the calibration stage yields a posterior distribution over plausible model parameterizations, allowing flexible, uncertainty-aware forward projections. We demonstrate the DDUADS workflow on the INFORM-HIV agent-based model of HIV transmission in Chicago to evaluate potential disruptions in antiretroviral therapy (ART) and pre-exposure prophylaxis (PrEP) use. While the specific application is HIV modeling, the challenges and techniques described here arise in other simulation studies and can be applied to decision support in other domains.

Markerless motion capture has emerged as a potential substitute for traditional marker-based systems, offering scalable, non-invasive acquisition of human movement. Despite increasing adoption in research and sports applications, its clinical utility for children with complex gait patterns remains an open question. To address this gap, simultaneous marker-based and markerless data were collected in 202 pediatric children (12.1 {+/-} 3.9 years). Marker-based kinematics were processed using the Shriners Children's Gait Model (SCGM), while markerless outputs were computed using Theia3D with identical Cardan sequences. Agreement between systems was evaluated using statistical parametric mapping (SPM), root-mean-square error (RMSE), and a gait pattern classification based on the plantarflexor-knee extension index. Markerless output systematically underestimated pelvic tilt, hip rotation, and knee rotation and demonstrated reduced between-subject variance in the transverse plane. SPM revealed widespread waveform differences, although most were of negligible effect, especially in the sagittal plane. Mean sagittal-plane RMSEs were < 5{degrees} for the knee and ankle and < 8{degrees} for the pelvis and hip. Coronal-plane deviations were < 7{degrees}, whereas transverse-plane errors exceeded 10{degrees}. RMSE increased significantly with body mass index and use of a walker (p < 0.001). Agreement in sagittal-plane gait classification was moderate between systems ({kappa} = 0.60; 67% overall concordance). These results indicate that markerless motion capture is suitable for analyses emphasizing sagittal deviations but remains limited for applications requiring precise axial or frontal-plane estimation. Future work should address algorithmic underestimation of transverse motion and evaluate markerless performance across increasing severity of gait deviation.

Background: Beaches are popular summertime destinations in Canada. However, they can be affected by specific fecal pollution sources, increasing the risk of recreational water illness. Objectives: This study was conducted to determine the risks of acute gastrointestinal illness (AGI) among Canadian beachgoers and to evaluate the influence of different fecal indicator bacteria (FIB) and other water quality measures on assessing these risks. Methods: In a prospective cohort design, beachgoers were recruited at sites across Canada from 2023 to 2025. Sociodemographic characteristics and exposures were determined through an on-site survey, with a 7-day follow-up survey to determine risks of AGI. Bayesian mixed-effects logistic regression models were fitted to evaluate the effects of an ordinal water contact variable (no contact, minimal contact, body immersion, and swallowed water) on the incident risk of AGI, with an interaction included for water quality indicators. The levels of six FIB and water quality measures were assessed: Escherichia coli, enterococci DNA, three microbial source tracking DNA markers (human HF183/BacR287, human mitochondria, seagull Gull4), and turbidity. Results: A total of 4085 participants were recruited, with 67.6% completing the follow-up survey. The overall incident risk of AGI was 2.6%. Both swallowing water and body immersion increased AGI risks compared to no water contact: median of 20 excess cases (95% Credible Interval [CrI]: 4, 64) and 5 excess cases (95% CrI: 1, 19) of AGI predicted per 1000 beachgoers, respectively. Escherichia coli and seagull DNA marker levels were associated with AGI among those who had water contact, particularly among those who reported swallowing water. Discussion: While the overall burden of AGI due to beach water contact in Canada was low, increased risks are associated with E. coli levels particularly among those who swallow water. This could be related to fecal contamination from seagulls. However, there is substantial uncertainty in the predicted effect sizes.

Introduction Understanding provider preferences for the design of HIV treatment packages could enhance the implementation of programs to support the adoption of long-acting injectable antiretroviral therapy (LAI ART) by people living with HIV who are interested in initiating this treatment modality. Methods We recruited providers from New York City (NYC), Rockland, Putman, and Westchester County Ryan White Part A Medical Case Management (MCM) programs to complete a discrete choice experiment (DCE) containing twelve tasks with two alternatives and an opt-out option, with additional survey questions about implementation readiness and choice motivations. The alternatives included four attributes--Type of ART Medication (monthly or bimonthly LAI ART), Service Location and Mode, Support for Clients, and Rewards for Clients--with 2-4 levels each. We ran latent class multinomial logit analyses (LCA) with 1-5 classes to estimate preferences and explore hypothesis-free preference heterogeneity. We estimated attribute influence using relative importances and preferences using zero-centered part-worth utilities for each level. Results One hundred seventy-seven providers completed the survey (July 2022-January 2023). About half (52%) were 40-59 years old, 72% identified as women, and the plurality (41%) identified as Latino/a. We chose the two-group LCA solution. Bimonthly LAI ART was preferred over monthly LAI ART overall and in both groups. Group 1 (n=45) preferred more traditional adherence supports (e.g., injections at the clinic by appointment, injection appointment reminders) whereas Group 2 (n=132) preferred more client-centered supports (e.g., injections at home by appointment, free transportation to injection appointments if at a clinic). Both groups preferred higher monetary value gift cards for clients for every on-time injection. The top-ranking motivations indicated that participants prioritized patient convenience over job satisfaction and administrative or financial feasibility for the agency. The scores for all implementation measures indicate readiness to implement LAI ART in both groups. Conclusions Our implementation science-focused study suggests that providers of MCM services in NYC and surrounding counties are motivated to offer services to support clients' access and adherence to LAI ART. More work is needed to understand how programs have, in fact, integrated supports for LAI ART into their services.

Background: Preterm births contribute to approximately 35% of neonatal deaths globally, with an estimated 13.4 million infants born prematurely each year. Despite this substantial burden, limited evidence exists on time to discharge and its determinants among preterm neonates admitted to Neonatal Intensive Care Units (NICUs), particularly in rural Ugandan settings. This study aimed to investigate time to discharge and associated factors among preterm neonates admitted to Kiwoko Hospital in Nakaseke District, Uganda. Methods: A retrospective cohort study was conducted using secondary data from Kiwoko Hospital on preterm neonates admitted to the Neonatal Intensive Care Unit (NICU) between 2020 and 2021 (n = 847). The cumulative incidence function was used to estimate the probability of discharge within 28 days of admission, accounting for competing events. A Fine and Gray sub-distribution hazard regression model was fitted to identify factors associated with time to discharge. Results: Of the 847 preterm admissions, 70.1% were discharged alive within 28 days. The median time to discharge was 14 days. The cumulative incidence of discharge by 28 days was 68%, accounting for competing events. During follow-up, 165 neonates did not complete the 28-day period, including 88 deaths. Factors significantly associated with time to discharge included place of delivery (SHR: 0.62; 95% CI: 0.53-0.73; p<0.001), maternal residence in other districts (SHR: 0.69; 95% CI: 0.48-0.99; p=0.044), extreme preterm (SHR: 0.05; 95% CI: 0.03-0.09; p<0.001), very preterm (SHR: 0.18; 95% CI: 0.14-0.25; p<0.001), moderate preterm (SHR: 0.59; 95% CI: 0.46-0.76; p<0.001), triplet births (SHR: 0.40; 95% CI: 0.23-0.68; p=0.001), 2-4 ANC visits (SHR: 0.70; 95% CI: 0.56-0.87; p=0.002), <=1 ANC visit (SHR: 0.64; 95% CI: 0.49-0.85; p=0.002), respiratory distress syndrome (SHR: 0.64; 95% CI: 0.48-0.74; p<0.001), and birth trauma (SHR: 2.62; 95% CI: 1.60-4.29; p<0.001). Conclusions: Respiratory distress syndrome, fewer antenatal care visits, out-of-district residence, and higher degrees of prematurity were associated with prolonged time to discharge among preterm neonates. Strengthening antenatal care utilization and improving access to quality neonatal care in underserved areas may enhance discharge outcomes.

Background: Household insecticides are widely used for domestic pest control, yet exposure patterns in traditionally underserved populations remain poorly characterized. In the Brazilian Amazon, data on use patterns among older adults living in riverine communities are particularly scarce. Objective: To describe the prevalence, frequency, duration, application practices, and types of household insecticides used by older adults living in near-urban riverine insular communities in the Brazilian Amazon. Methods: Cross-sectional, population-based door-to-door survey conducted from August 2022 to July 2025 in four islands (Cotijuba, Mosqueiro, Outeiro, and Combu) in the city of Belem, Brazil. All residents aged 60 years or more registered in the primary care system were invited to participate. Trained interviewers administered an in-person standardized questionnaire to participants on current household insecticide use, frequency, duration, self-application, protective equipment, insecticide types, and product brands. Results: Among 1,101 screened individuals, 1,084 were included (median age at evaluation: 68 years). Overall, 78.4% reported current use of household insecticides. Weekly or more frequent use was reported by 58.9%, and 33.4% reported use for more than 5 years. Self-application was common (57.5%), whereas use of protective equipment was rare (8.2%). Aerosol sprays were the most frequently reported type (39.4%). Commonly recalled aerosols contained pyrethroid mixtures including cypermethrin, imiprothrin, prallethrin, and transfluthrin. A substantial proportion of participants reported using unregulated products and veterinary-only insecticides for household purposes. Conclusions: Household insecticide use is highly prevalent and frequent in Amazonian riverine communities, with minimal use of protective equipment and substantial irregular practices, underscoring the need for targeted risk communication and surveillance.

Urban informal settlements (referred to as favelas in Brazil), reflect longstanding socioeconomic and racial inequalities and are home to a workforce frequently exposed to precarious employment conditions. This study describes the socio-occupational characteristic and estimates the prevalence of common mental disorders (CMDs) among workers residing in five urban informal communities in Salvador, Bahia, Brazil. A cross-sectional epidemiological study (n=587) was conducted with formal and informal workers aged 18-70 years. The outcome was measured using the Self-Reporting Questionnaire-SRQ-20, and associations were evaluated using Poisson Regression, with analysis stratified by employment type. Data analysis was performed using R 3.6.0+ software. The overall prevalence of CMD was 14.0%, increasing to 22.7% among informal workers. In the adjusted analysis of the overall sample, informal employment and persistent fear of job loss were associated with a higher prevalence of mental health problems, whereas the 40-49 age groups showed a lower prevalence of CMD compared with younger workers. In stratified analyses, female sex and job insecurity were associated with CMD among formal workers, while lower monthly income (<$181) was an important among informal workers. This pioneering study highlights the role of precarious employment conditions in the social determination of mental health distress among residents of urban informal communities.

BackgroundDrowning remains a major global public health challenge. This study examined whether the timing and trajectories of urbanisation--beyond the current built environment--are associated with subnational drowning mortality. MethodsWe linked satellite-derived measures of built-environment change (GHSL), population crowding (WorldPop), surface water exposure (JRC Global Surface Water), and infrastructure proxies (VIIRS/DMSP nighttime lights) to GBD 2021 drowning mortality estimates across 203 ADM1 regions in 12 countries (2006-2021; 3,248 region-year observations). Temporal predictors captured recent expansion, development "newness" ([&le;]10-year built share), acceleration/volatility, and a crowdingxgrowth interaction. We screened predictors using LASSO (10-fold cross-validation) and fitted mixed-effects models with region random intercepts. Distributed-lag models tested temporal precedence and development age, and income-stratified models assessed heterogeneity. ResultsAdding temporal predictors improved fit beyond contemporaneous built-environment measures ({Delta}AIC=177; {Delta}BIC=147). In adjusted models, crowdingxgrowth was strongly positively associated with drowning mortality, and a higher share of recent development was associated with higher mortality. Lag models showed a development age gradient: older built environment was most protective. Associations differed by income group, with several key coefficients reversing sign across strata. DiscussionDrowning mortality appears shaped by development histories as well as present-day conditions, with risk concentrated in rapidly changing, dense settings and the newest built environments. Cross-context heterogeneity suggests mechanisms and prevention priorities are unlikely to be uniform. ConclusionsDevelopment timing and trajectories help explain subnational drowning mortality beyond current built form alone. Prevention and planning should prioritise transition-period safety strategies in newly developing and rapidly densifying areas.

Objectives: Quantify hazardous alcohol consumption prevalence among individuals at risk of acquiring HIV infection and its association with high-risk sexual behaviors and incident HIV in 11 Eastern and Southern African countries. Design: Secondary analysis of 16 nationally-representative household surveys (2015-2023). Methods: The study included sexually active individuals aged [&ge;]15 years. Alcohol use patterns were classified using the AUDIT-C (non-drinkers/low-risk drinkers/hazardous non-binge drinkers/hazardous binge drinkers). Outcomes included high-risk sexual behaviors, recent HIV infection, and undiagnosed HIV infection. Survey-weighted alcohol use prevalence and logistic regression were estimated by gender, adjusting for sociodemographic covariates. Model outputs were used to estimate change in incident infections when removing excess risks associated with alcohol use patterns. Results: Analyses included 251,931 participants. Across countries, 5.8%-21.1% reported hazardous binge drinking, and 3.7%-15.7% reported hazardous non-binge drinking, with large gender differences. Sexual risk behaviors increased with drinking severity among men and women. Compared with non-drinkers, alcohol use was associated with higher odds of undiagnosed HIV infection; adjusted odds ratios ranged from 1.32 (1.16-1.50) for low-risk drinkers to 1.52 (1.34-1.72) for hazardous binge drinkers among men, and 1.28 (1.13-1.46) to 1.55 (1.31-1.82) among women. Simulated removal of alcohol-associated excess risk reduced undiagnosed HIV by 15.1% (10.9%-19.4%) among men and 5.8% (4.0%-7.9%) among women. Estimates for recent HIV infection followed a similar pattern but with larger uncertainty. Conclusions: Hazardous alcohol use was associated with sexual risk and HIV infection in Eastern and Southern Africa. Reaching individuals who use alcohol with effective HIV prevention may reduce HIV acquisition risk across the region.