Search

In March of 2023, the first National Primary Drinking Water Standards for per- and polyfluoroalkyl substances (PFAS) were announced. The fourth Regulatory Determination that led to this development also included several other contaminants for consideration: 1,4-dioxane (dioxane), 1,2,3-trichloropropane (TCP), and strontium, which faced no determination at this time. In this study, the relative risks associated with these three contaminants and the two regulated PFAS, perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), are analyzed on a subregion level, considering socioeconomic and racial factors in national exposure and risk levels for the U.S. population. Results indicate that PFOS and PFOA represent the greatest risk to the population in the subregions in which they are detected. Considering race and ethnicity, living in a majority-minority community may be a risk factor for exposure to strontium, while minority status did not increase exposure risk for dioxane, TCP, PFOS, and PFOA. Additionally, total cancer and non-cancer relative health indicator (RHI) matrices indicate that majority-minority communities face significantly greater risks from strontium exposure. Regression models also confirm results for strontium but place the risk on racial/ethnic minority populations more specifically in regions with greater Hispanic/Latino community percentages. Finally, while greater poverty in a subregion is associated with significantly higher cancer and non-cancer RHI values for dioxane, strontium, and TCP, after controlling for state-level variations, multi-level models reveal that greater poverty is associated with significantly lower risk from these three contaminants., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study addresses the issue of wrong-way driving (WWD) incidents at partial cloverleaf (parclo) interchange terminals in the United States. These incidents are a safety concern, often attributed to geometric design features and inadequate traffic control devices (TCDs). While previous research has acknowledged the significance of parclo interchanges as common initial entry points for WWD crashes, few studies have comprehensively quantified the impact of TCDs and design features on recurring WWD incidents. In response, this study collected data from 75 parclo interchange terminals spanning 13 states. A subset of 28 ramp terminals exhibiting recurrent WWD incidents, amounting to 410 incidents during the data collection phase, received focused attention. Leveraging modern machine learning methodologies, two techniques: eXtreme Gradient Boosting (XGboost) and Lasso-logistic regression were applied to quantify the influence of distinct TCDs and design features on the probability of WWD incidents occurring. The outcomes of this analysis revealed noteworthy results: the fitted XGboost model displayed an average accuracy of 80%, closely followed by the fitted Lasso-logistic regression model with an average accuracy of 78%. These models were subsequently employed to construct a practical network screening tool. This tool assists in the identification of potential WWD incident locations, predicated on the effects of TCDs and design characteristics. The significance of this study lies in its potential to inform and guide state and local transportation agencies in enhancing the safety of parclo interchange terminals. By discerning the impacts of TCDs and design features, stakeholders can implement improvements that curtail the occurrence of WWD incidents, contributing to enhanced road safety and optimized traffic management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

An analysis was conducted using nationwide survey data to evaluate how material recovery facilities (MRFs) operations vary regionally and with scale. The survey characterized materials, processes, and energy use involved with operations, and revenue for recyclables. This is the first nationwide analysis of MRFs in the US that accounts for mass processed, energy consumed, and revenue. Of a population of 521 MRFs, 48 responses representing MRFs from five US regions were received and analyzed (9.2 % response rate). Responses were analyzed by size according to yearly mass of inbound materials (small: <1,000 Mg/year, medium: 1,000-10,000 Mg/year, and large: >10,000 Mg/year). Most MRFs identify as single-stream; source from residences; utilize tipping floors, picking lines, baling and warehousing; and are powered by electricity. Most revenue and inbound mass (>50 %) came from fiber (cardboard and paper). Glass had little revenue, and plastics were difficult to transition to market. Percent residue ranged from 1-39 %, averaged < 20 %, and increased as the mass of inbound material increased. Large MRFs reported more sources of material, employed advanced sorting technology, had greater plastics revenue (33 % versus 5 % for small MRFs), and had more market access for plastics compared to small MRFs. Large MRFs had two orders of magnitude less annual electricity consumption per Mg recyclables than small MRFs (5-90 kWh/Mg versus ∼ 300-550 kWh/Mg). Results demonstrate environmental and economic benefits of larger-scale MRFs, which could be implemented more broadly in the US through regional hub-and-spoke arrangements for collecting and processing recyclables, lowering energy consumption and increasing revenue for recyclables., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

One application of plastics that grew during the COVID-19 pandemic is for social distancing plastic shields, or protective barriers, made from polymethyl methacrylate (PMMA) such as transparent face guards. Although available for other applications, end-of-life impacts for barriers are currently lacking in the literature, and there is a need to fill in this gap to guide decisions. This study evaluated the end-of-life environmental impacts of PMMA barriers in the United States by using life cycle assessment. We evaluated five strategies including landfilling, waste-to-energy, mechanical recycling, chemical recycling and reuse. Data were sourced from literature and various life cycle inventory databases. The Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI) was used as the life cycle impact assessment method. Landfilling exhibited the highest impact in all indicators and reuse demonstrated optimal results for global warming potential. A scenario analysis was conducted to explore a combination of strategies, revealing that the most promising approach involved a mix of 40% reuse, 20% mechanical recycling and 40% chemical recycling. Circular economy recommendations are proposed for managing these sources of plastic waste in the United States., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Nationwide PM 2.5 exposure models typically rely on regulatory monitoring data as the only ground-level measurements. In this study, we develop a high-resolution spatiotemporal PM 2.5 model for the contiguous United States from 2000 to 2019 with dense monitoring data at both regulatory and residential sites. Specifically, we combine publicly-available data from 1843 regulatory monitors with our own set of multiple 2-week measurements at 939 residential locations. As we show, these additional data enhance the spatiotemporal prediction capabilities of the model. The model can handle varying data densities and regional variations; it predicts two-week average PM 2.5 concentrations at fine spatial scale for the contiguous United States. Cross-validation performance indicates a spatial R 2 of 0.93 and a root mean square error (RMSE) of 1.19 (μg/m 3 ), and a temporal R 2 of 0.85 and RMSE of 2.05 (μg/m 3 ). Regional spatial R 2 ranged from 0.80 (northwest) to 0.93 (northeast and central). Over time, the average PM 2.5 across the United Stats decreased from 7.6 μg/m 3 in 2000 to 4.7 μg/m 3 in 2019. Our model effectively captured local PM 2.5 gradients, highlighting its ability to address fine-scale variations related to local sources and roadways., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Water is crucial for meeting sustainability targets, but its unsustainable use threatens human wellbeing and the environment. Past assessments of water scarcity (i.e., water demand in exceedance of availability) have often been spatially coarse and temporally limited, reducing their utility for targeting interventions. Here we perform a detailed monthly sub-basin assessment of the evolution of blue (i.e., surface and ground) water scarcity (years 1980-2015) for the world's three most populous countries - China, India, and the USA. Disaggregating by specific crops and sectors, we find that blue water demand rose by 60% (China), 71% (India), and 27% (USA), dominated by irrigation for a few key crops (alfalfa, maize, rice, wheat). We also find that unsustainable demand during peak months of use has increased by 101% (China), 82% (India), and 49% (USA) and that 32% (China), 61% (India), and 27% (US) of sub-basins experience at least 4 months of scarcity. These findings demonstrate that rising water demands are disproportionately being met by water resources in already stressed regions and provide a basis for targeting potential solutions that better balance the water needs of humanity and nature., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

There is a need to assess whether ecological resources are being protected on large, federal lands. The aim of this study was to present a methodology which consistently and transparently determines whether two large Department of Energy (U.S. DOE) facilities have protected valuable ecological lands on their sites compared to the surrounding region. The National Land Cover Database (2019) was used to examine the % shrub-scrub (shrub-steppe) and other habitats on the DOE's Hanford Site (HS, Washington) and on the Idaho National Laboratory (INL), compared to a 10-km and 30-km diameter band of land surrounding each site. On both sites, over 95% is in shrub-scrub or grassland, compared to the surrounding region. Approximately 70% of 10 km and 30-km bands around INL, and less than 50% of land surrounding HS is located in these two habitat types. INL has preserved a significantly higher % shrub/scrub habitat than HS, but INL allows grazing on 60% of its land. HS has preserved a significantly higher % grassland than INL but no grazing on site is present. The methodology presented may be used to compare key ecological habitat types such as grasslands, forest, and desert among sites in different parts of the country. This methodology enables managers, resource trustees, and the public to (1) make remediation decisions that protect resources, (2) assess whether landowners and managers have adequately characterized and protected environmental resources on their sites, and (3) whether landowners and managers have protected the integrity of that land as well as its climax vegetation.

Stormwater capture and use (SCU) projects have the potential to provide a significant portion of municipal water demand. However, uncertainty about the degree of microbial contamination in stormwater and the required treatment is a barrier for implementation of SCU projects. Stormwater runoff could become contaminated with human fecal matter in areas with deteriorating infrastructure where raw wastewater exfiltrates from sewer networks to stormwater collection networks, homeless encampments exist, or sanitary sewer overflows (SSOs) occur. Estimation of human fecal contamination can inform selection of stormwater treatment targets. This study investigates stormwater microbial contamination originating from human fecal matter using observed detections and concentrations of human microbial source tracking (MST) markers and potentially human-infectious pathogens (PHIPs). First, a systematic review complied measurements of human MST markers in wet and dry weather stormwater flows and influent wastewater. In addition, measurements of viral pathogens (e.g., adenoviruses, norovirus GI+GII, and enteroviruses) and protozoan pathogens (e.g., Giardia lamblia and Cryptosporidium parvum) in wet weather flows and influent wastewater were assessed. Human MST marker and PHIP data were statistically analyzed and applied to estimate a human fecal contamination analog (HFCA) which is an estimate of the amount of human fecal matter based on relative concentrations of microbial contaminants in stormwater compared to municipal wastewater. Human MST-based HFCAs in wet and dry weather flows ranged from <10 -7.0 to 10 -1.5 (median = 10 -4.5 ) and 10 -12 to 10 -2.6 (median = 10 -7.0 ), respectively. PHIP-based HFCAs in wet weather flows ranged from ∼10 -8 to 10 -0.14 . Estimates of human MST-based HFCAs are more reliable than PHIP-based HFCAs because the current PHIP datasets are generally limited by the number of data points, percent detection, variability observed within the statistical distributions, and the geographical span of sampling locations. The use of human MST-based HFCAs is recommended to guide the selection of stormwater treatment process trains that are protective of public health based on the intended end use. Application of HFCA 10 -1 (i.e., sewage dilution 10 -1 ) remains a reasonable conservative estimate of human fecal contamination in stormwater to inform selection of pathogen log reduction targets based on the data presently available., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Objectives: To build on the success of wastewater surveillance during the COVID-19 pandemic, jurisdictions funded under the Centers for Disease Control and Prevention National Wastewater Surveillance System are looking to expand their wastewater programs to detect more pathogens. However, many public health agencies do not know how to use the collected wastewater data to formulate public health responses, underscoring a need for guidance. To address this knowledge gap, the Houston Health Department (HHD) developed a novel response framework that outlines an internal action plan that is tailored by pathogen type after detection of various pathogens in wastewater., Materials and Methods: In July 2023, HHD met with subject matter experts (eg, bureau chiefs, program managers) in internal departments, including epidemiology, immunization, and health education, to discuss the general outline of the response framework and each department's anticipated role after pathogen detection., Results: The internal framework established a flow for notifications and the actions to be taken by departments in HHD, with the goals of (1) ensuring timely and efficient responses to pathogen detections, (2) creating accountability within departments for taking their assigned actions, and (3) making certain that HHD was prepared for intervention implementation when a new pathogen was detected., Practice Implications: As more public health agencies expand their wastewater surveillance programs to target additional pathogens, development of internal action plans tailored to departmental capacity and programs is an important step for public health agencies. The information compiled in this response framework can be a model for other public health agencies to adopt when expanding the scope of their wastewater monitoring systems., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Endocrine-disrupting chemicals (EDCs) are widely used in consumer products and have been associated with adverse public health outcomes and significant economic costs. We developed a rapid chamber method for measuring EDC emissions from consumer products, significantly reducing the time to reach steady state from weeks or months to minutes or hours. Using this method, we quantified EDC emissions from a wide range of products, determined the emission-control parameters, and established their relationship with the EDC content ( W ) and physicochemical properties. By incorporating f data from consumer product databases and applying stochastic models, we systematically estimated emissions for 400 EDC-product combinations and assessed the associated exposure and disease burden for the U.S. population. Our results suggest that more than 60% of these combinations could result in carcinogenic disability-adjusted life years (DALYs) above the acceptable threshold. The overall disease burden caused by EDCs in consumer products can be substantial, with DALYs exceeding those associated with other pollutants, such as particulate matter, in a worst-case scenario. This study provides a valuable tool for prioritizing hazardous EDCs in consumer products, evaluating safer alternatives, and formulating effective intervention strategies, thereby supporting policymakers and manufacturers in making informed, sustainable decisions.W f data from consumer product databases and applying stochastic models, we systematically estimated emissions for 400 EDC-product combinations and assessed the associated exposure and disease burden for the U.S. population. Our results suggest that more than 60% of these combinations could result in carcinogenic disability-adjusted life years (DALYs) above the acceptable threshold. The overall disease burden caused by EDCs in consumer products can be substantial, with DALYs exceeding those associated with other pollutants, such as particulate matter, in a worst-case scenario. This study provides a valuable tool for prioritizing hazardous EDCs in consumer products, evaluating safer alternatives, and formulating effective intervention strategies, thereby supporting policymakers and manufacturers in making informed, sustainable decisions.

The Vision Zero-Safe Systems Approach prioritizes fast access to Emergency Medical Services (EMS) to improve the survivability of road users in transportation crashes, especially concerning the recent increase in pedestrian-involved crashes. Pedestrian crashes resulting in immediate or early death are considerably more severe than those taking longer. The time gap between injury and fatality is known as survival time, and it heavily relies on EMS response time. The characteristics of the crash location may be associated with EMS response and survival time. A US Department of Transportation initiative identifies communities often facing challenges. Six disadvantaged community (DAC) indicators, including economy, environment, equity, health, resilience, and transportation access, enable an analysis of how survival and EMS response times vary across DACs and non-DACs. To this end, this study created a unique and comprehensive database by linking DACs data with 2017-2021 pedestrian-involved fatal crashes. This study utilizes two-stage residual inclusion models with segmentation for DACs and non-DACs accounting for the endogenous relationship between EMS response and pedestrian survival time. The results indicate that EMS response time is higher and pedestrian survival time is lower in DACs than in non-DACs. A delayed EMS response time is associated with a greater reduction in survival time in DACs compared to non-DACs. Factors, e.g., nighttime and interstate crashes, contribute to higher EMS response time, while pedestrian drugs, driver speeding, and hit-and-run behaviors are associated with a greater reduction in survival time in DACs than non-DACs. The implications of the findings are discussed in the paper., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In 2022, the US Centers for Disease Control and Prevention commissioned the National Academies of Sciences, Engineering, and Medicine to assess the role of community-level wastewater-based epidemiology (WBE) beyond COVID-19. WBE is recognized as a promising mechanism for promptly identifying infectious diseases, including COVID-19 and other novel pathogens. An important conclusion from this initiative is the critical importance of maintaining equity and expanding access to fully realize the benefits of wastewater surveillance for marginalized communities. To address this need, we propose an optimization framework that strategically allocates wastewater monitoring resources at the wastewater treatment plant (WWTP) level, ensuring more effective and equitable distribution of surveillance efforts to serve underserved populations. The purpose of the framework is to obtain a balanced spatial distribution, inclusive population coverage, and efficient representation of disadvantaged groups in the allocation of resources for WBE. Furthermore, the framework concentrates on areas with high population density and gives priority to vulnerable regions, as well as identifying signals that display significant variations from other monitored sources. The optimization objective is to maximize a weighted combination of these critical factors. This problem is formulated as an integer optimization problem and solved using simulated annealing. We evaluate various scenarios, considering different weighting factors, to optimize the allocation of WWTPs with monitoring systems. This optimization framework provides an opportunity to enhance WBE by providing customized monitoring strategies created to address specific priorities and situations, thus enhancing the decision-making processes in public health responses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The loss of phosphorous (P) from the land to aquatic systems has polluted waters and threatened food production worldwide. Systematic trend analysis of P, a nonrenewable resource, has been challenging, primarily due to sparse and inconsistent historical data. Here, we leveraged intensive hydrometeorological data and the recent renaissance of deep learning approaches to fill data gaps and reconstruct temporal trends. We trained a multitask long short-term memory model for total P (TP) using data from 430 rivers across the contiguous United States (CONUS). Trend analysis of reconstructed daily records (1980-2019) shows widespread decline in concentrations, with declining, increasing, and insignificantly changing trends in 60%, 28%, and 12% of the rivers, respectively. Concentrations in urban rivers have declined the most despite rising urban population in the past decades; concentrations in agricultural rivers however have mostly increased, suggesting not-as-effective controls of nonpoint sources in agriculture lands compared to point sources in cities. TP loss, calculated as fluxes by multiplying concentration and discharge, however exhibited an overall increasing rate of 6.5% per decade at the CONUS scale over the past 40 y, largely due to increasing river discharge. Results highlight the challenge of reducing TP loss that is complicated by changing river discharge in a warming climate., Competing Interests: Competing interests statement:The authors declare no competing interest.

Wastewater-based epidemiology, which seeks to assess disease occurrence in communities through measurements of infectious disease biomarkers in wastewater, may represent a valuable tool for understanding the occurrence of hepatitis A infections in communities. In this study, we measured concentrations of Hepatovirus A (HAV) RNA, in samples from 191 wastewater treatment plants spanning 40 US states and the District of Columbia from September 2023 to June 2024 and compared the measurements with traditional measures of disease occurrence. Nationally, 13.76% of the 21,079 wastewater samples were positive for HAV RNA, and both concentrations and positivity rates were associated with NNDSS hepatitis A case data nationally (Kendall rank correlation coefficient = 0.20, concentrations; and 0.33, positivity rate; both P < 0.05). We further demonstrated that higher rates of wastewater HAV detection were positively associated with socioeconomic indicators of vulnerability including homelessness and drug overdose deaths (both P < 0.0001). Areas with above average levels of homelessness were 48% more likely to have HAV wastewater detections, while areas with above average levels of drug overdose deaths were 14% more likely to have HAV wastewater detections. Using more granular case data, we present a case study in the state of Maine that reinforces these results and suggests a potential lead time for wastewater over clinical case detection and exposure events. The ability to detect HAV RNA in wastewater before clinical cases emerge could allow public health officials to implement targeted interventions like vaccination campaigns.IMPORTANCEDespite the existence of a highly effective vaccine for hepatitis A, outbreaks in vulnerable populations remain common. The disease can be asymptomatic or subclinical, and disproportionately impacts populations with inadequate access to healthcare, leading to a severe underestimation of the occurrence of this viral infection. This study investigates the potential for wastewater measurements of biomarkers of the causative agent of hepatitis A (HAV RNA) to provide insights into disease occurrence. Results highlight the potential for wastewater-based epidemiology to be a complementary tool to traditional surveillance for monitoring and controlling HAV transmission., Competing Interests: The authors declare no conflict of interest.

Groundwater hydrographs contain a rich set of information on the dynamics of aquifer systems and the processes and properties that influence them. While the importance of seasonal cycles in hydrologic and environmental state variables is widely recognized there has yet to be a comprehensive analysis of the seasonal dynamics of groundwater across the United States. Here we use time series of groundwater level measurements from 997 wells from the National Groundwater Monitoring Network to identify and describe groundwater seasonal cycles in unconfined aquifers across the United States. We use functional data analysis to obtain a functional form fit for each site and apply an unsupervised clustering algorithm to identify a set of five distinct seasonal cycles regimes. Each seasonal cycle regime has a distinctive shape and distinct timing of its annual minimum and maximum water level. There are clear spatial patterns in the occurrence of each seasonal cycle regime, with the relative occurrence of each regime strongly influenced by the geologic setting (aquifer system), climate, and topography. Our findings provide a comprehensive characterization of groundwater seasonal cycles across much of the United States and present both a methodology and results useful for assessing and understanding unconfined groundwater systems., (© 2024 National Ground Water Association.)

Objectives: Military training centers and seagoing vessels are often environments at high risk for the spread of COVID-19 and other contagious diseases, because military trainees and personnel arrive after traveling from many parts of the country and live in congregate settings. We examined whether levels of SARS-CoV-2 genetic material in wastewater correlated with SARS-CoV-2 infections among military personnel living in communal barracks and vessels at US Coast Guard training centers in the United States., Methods: The Coast Guard developed and established 3 laboratories with wastewater testing capability at Coast Guard training centers from March 2021 through August 2022. We analyzed wastewater from barracks housing trainees and from 4 Coast Guard vessels for the presence of SARS-CoV-2 genes N and E and quantified the results relative to levels of a fecal indicator virus, pepper mild mottle virus. We compared quantified data with the timing of medically diagnosed COVID-19 infection among (1) military personnel who had presented with symptoms or had been discovered through contact tracing and had medical tests and (2) military personnel who had been discovered through routine surveillance by positive SARS-CoV-2 antigen or polymerase chain reaction test results., Results: Levels of viral genes in wastewater at Coast Guard locations were best correlated with diagnosed COVID-19 cases when wastewater testing was performed twice weekly with passive samplers deployed for the entire week; such testing detected ≥1 COVID-19 case 69.8% of the time and ≥3 cases 88.3% of the time. Wastewater assessment in vessels did not continue because of logistical constraints., Conclusion: Wastewater testing is an effective tool for measuring the presence and patterns of SARS-CoV-2 infections among military populations. Success with wastewater testing for SARS-CoV-2 infections suggests that other diseases may be assessed with similar approaches., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Importance: Limited access to healthy foods, resulting from residence in neighborhoods with low food access, is a public health concern. The contribution of this exposure in early life to child obesity remains uncertain., Objective: To examine associations of neighborhood food access during pregnancy or early childhood with child body mass index (BMI) and obesity risk., Design, Setting, and Participants: Data from cohorts participating in the US nationwide Environmental Influences on Child Health Outcomes consortium between January 1, 1994, and March 31, 2023, were used. Participant inclusion required a geocoded residential address in pregnancy (mean 32.4 gestational weeks) or early childhood (mean 4.3 years) and information on child BMI., Exposures: Residence in low-income, low-food access neighborhoods, defined as low-income neighborhoods where the nearest supermarket is more than 0.5 miles for urban areas or more than 10 miles for rural areas., Main Outcomes and Measures: BMI z score, obesity (age- and sex-specific BMI ≥95th percentile), and severe obesity (age- and sex-specific BMI ≥120% of the 95th percentile) from age 0 to 15 years., Results: Of 28 359 children (55 cohorts; 14 657 [51.7%] male and 13 702 [48.3%] female; 590 [2.2%] American Indian, Alaska Native, Native Hawaiian, or Other Pacific Islander; 1430 [5.4%] Asian; 4034 [15.3%] Black; 17 730 [67.2%] White; and 2592 [9.8%] other [unspecified] or more than 1 race; 5754 [20.9%] Hispanic and 21 838 [79.1%] non-Hispanic) with neighborhood food access data, 23.2% resided in low-income, low-food access neighborhoods in pregnancy and 24.4% in early childhood. After adjusting for individual sociodemographic characteristics, residence in low-income, low-food access (vs non-low-income, low-food access) neighborhoods in pregnancy was associated with higher BMI z scores at ages 5 years (β, 0.07; 95% CI, 0.03-0.11), 10 years (β, 0.11; 95% CI, 0.06-0.17), and 15 years (β, 0.16; 95% CI, 0.07-0.24); higher obesity risk at 5 years (risk ratio [RR], 1.37; 95% CI, 1.21-1.55), 10 years (RR, 1.71; 95% CI, 1.37-2.12), and 15 years (RR, 2.08; 95% CI, 1.53-2.83); and higher severe obesity risk at 5 years (RR, 1.21; 95% CI, 0.95-1.53), 10 years (RR, 1.54; 95% CI, 1.20-1.99), and 15 years (RR, 1.92; 95% CI, 1.32-2.80). Findings were similar for residence in low-income, low-food access neighborhoods in early childhood. These associations were robust to alternative definitions of low income and low food access and additional adjustment for prenatal characteristics associated with child obesity., Conclusions: Residence in low-income, low-food access neighborhoods in early life was associated with higher subsequent child BMI and higher risk of obesity and severe obesity. We encourage future studies to examine whether investments in neighborhood resources to improve food access in early life would prevent child obesity.

Organisms that are associated with feces ("fecal indicator organisms") are monitored to assess the potential for fecal contamination of surface water bodies in the United States. However, the effect of the complex mixtures of chemicals and the natural microbial community within surface water ("particles") on fecal indicator organism persistence is not well characterized. We aimed to better understand how particles, including biological (e.g., potential grazers) and inert (e.g., minerals) types, affect the fecal indicator organisms Escherichia coli K-12 (" E. coli ") and bacteriophage MS2 in surface waters. A gradient of particles captured by a 0.2-µm-pore-size filter ("large particles") was generated, and the additional particles and dissolved constituents that passed through the filter were deemed "small particles." We measured the ratio of MS2 and E. coli that survived over a 24-h incubation period for each condition (0%-1,000% large-particle concentration in raw water) and completed a linear regression that included large- and small-particle coefficients. Particles were characterized by quantifying plankton, total bacterial cells, and total solids. E. coli and MS2 persistence was not significantly affected by large particles, but small particles had an effect in most waters. Small particles in higher-salinity waters had the largest, negative effect on E. coli and MS2 survival ratios: Significant small-particle coefficients ranged from -1.7 to -5.5 day -1 in the marine waters and -0.89 to -3.2 day -1 in the fresh and estuarine waters. This work will inform remediation efforts for impaired surface water bodies.IMPORTANCEMany surface water bodies in the United States have organisms associated with fecal contamination that exceed regulatory standards and prevent safe recreation. The process to remediate impaired water bodies is complicated because these fecal indicator organisms are affected by the local environmental conditions. For example, the effect of particles in surface water on fecal indicator concentrations are difficult to quantify in a way that is comparable between studies and water bodies. We applied a method that overcomes this limitation to assess the effects of large particles, including natural plankton that could consume the seeded fecal indicator organisms. Even in environmental water samples with diverse communities of plankton present, no effect of large particles on fecal indicator concentrations was observed. These findings have implications for the interpretation and design of future studies, including that particle characterization of surface water may be necessary to assess the fate of fecal indicators., Competing Interests: The authors declare no conflict of interest.

Identifying factors that significantly affect drivers that are repeatedly involved in traffic violations or non-fatal crashes (defined here as recidivist drivers) is very important in highway safety studies. This study sought to understand the relationship between a set of variables related to previous driving violations and the duration between a previous non-fatal crash and a subsequent fatal crash, taking into account the age and gender of the driver. By identifying the characteristics of this unique driver population and the factors that influence the duration between their crash events strategies can be put in place to prevent the occurrence of future and potentially fatal crashes. To do this, a five-year (2015-2019) historical fatal crash data from the United States was used for this study. Out of 15,956 fatal crashes involving recidivist drivers obtained, preliminary analysis revealed an overrepresentation of males (about 75%). It was also found that the average duration between the two crash events was about a year and a half, with only an average of one month difference between male and female drivers. Using hazard-based duration models, factors such as number of previous crashes, previous traffic violations, primary contributing factors and some driver demographic characteristics were found to significantly be associated with the duration between the two crash events. The duration between the two events increased with driver's age for drivers who were involved in only one previous crash and the duration was shorter for those that were previously involved in multiple crashes. Previous DUI violations, license suspensions, and previous speeding violations were found to be associated with shorter durations, at varying degrees depending on the driver's age and gender. The duration was also observed to be longer if the fatal crash involved alcohol or drug use among younger drivers but shorter among middle-aged male drivers. These findings reveal interesting dynamics that may be linked to recidivist tendencies among some drivers involved in fatal crashes. The factors identified from this study could help identify crash countermeasures and programs that will help to reform such driver behaviors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Introduction: Lane departure collisions account for many roadway fatalities across the United States. Many of these crashes occur on horizontal curves or ramps and are due to speeding. This research investigates factors that impact the odds of speeding on Interstate horizontal curves and ramps., Method: We collected and combined two unique sources of data. The first database involves comprehensive curve and ramp characteristics collected by an automatic road analyzer (ARAN) vehicle; the second database includes volume, average speed, and speed distribution gathered from probe data provided by StreetLight Insight®. We evaluated the impacts of level of service (LOS), which reflects traffic density or level of congestion, time of the day (morning, evening, and off-peak hours), time of the week (weekdays and weekends), and month of the year (Jan-Dec), and various information about geometric characteristics, such as curve radius, arc angle, and superelevation, on odds of speeding., Results: The results show that the odds of speeding increases at horizontal curves with improved levels of service, as well as those with larger radii and superelevation. The odds of speeding decreases on curves with larger arc angles and during the winter months of the year. The findings indicate a reduction in odds of speeding at diagonal/loop ramps with larger arc angles and narrower lane widths., Conclusion: The results show the importance of using speed enforcement and other countermeasures to reduce speeding on curves with low traffic volumes, high speed limits, and large radius and superelevation, especially for those in rural areas., Practical Application: The results could be used to prioritize locations for the installation of speed countermeasures or dispatch enforcement resources to high-priority locations and times., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 National Safety Council and Elsevier Ltd. All rights reserved.)

Air pollution is arguably the most pressing human health concern today, accounting for approximately 7-9 million premature deaths worldwide. In the United States, more than 40% of early deaths caused by air pollution are assessed to be caused by emissions produced by neighboring states. This article examines one of the governance mechanisms used by the U.S. to address this issue: section 126 of the Clean Air Act. Critical factors including case length, evidence used, and case outcome are compiled for the population of section 126 petitions submitted from 2000-2022. This evidence is assessed using comparative case analysis. The findings reinforce two issues with the petition process already identified in the literature-the use of cost as a proxy for significance and the excessive and unclear burden of proof placed on downwind states-adding texture to the latter issue by examining the modeling techniques used by downwind states. This analysis identifies lengthy response timelines as an additional issue and calls to attention the infrequency with which the EPA has formally accepted petitions. Collectively, these issues increase the cost, complexity, and unpredictability of filing a section 126 petition., (© 2024. The Author(s).)

Candida auris is an emerging, multidrug-resistant fungal pathogen that poses a significant public health threat in healthcare settings. Despite yearly clinical cases rapidly increasing from 77 to 8,131 in the last decade, surveillance data on its distribution and prevalence remain limited. We implemented a novel assay for C. auris detection on a nationwide scale prospectively from September 2023 to March 2024, analyzing a total of 13,842 samples from 190 wastewater treatment plants across 41 U.S. states. Assays were extensively validated through comparison to other known assays and internal controls. Of these 190 wastewater treatment plants, C. auris was detected in the wastewater solids of 65 of them (34.2%) with 1.45% of all samples having detectable levels of C. auris nucleic-acids. Detections varied seasonally, with 2.00% of samples positive in autumn vs 1.01% in winter ( P < 0.0001). The frequency of detection in wastewater was significantly associated with states having older populations ( P < 0.001), sewersheds containing more hospitals ( P < 0.0001), and sewersheds containing more nursing homes ( P < 0.001). These associations are in agreement with known C. auris epidemiology. This nationwide study demonstrates the viability of wastewater surveillance for C. auris surveillance and further highlights the value of wastewater surveillance when clinical testing is constrained., Importance: This study highlights the viability of wastewater surveillance when dealing with emerging pathogens. By leveraging an existing framework of wastewater surveillance, we reveal the widespread presence of C. auris in the United States. We further demonstrate that these wastewater detections are consistent with demographic factors relevant to C. auris epidemiology like age and number of hospitals or nursing homes. As C. auris and other pathogens continue to emerge, the low-cost and rapid nature of wastewater surveillance will provide public health officials with the information necessary to enact targeted prevention and control strategies., Competing Interests: D.D., X.-R.S.X., B.J.W., and B.S. are employees of Verily Life Sciences.

Background: Widespread use of e-cigarette (EC) or vaping products causes respiratory disorders including the nationwide outbreak of e-cigarette or vaping product use-associated lung injury (EVALI) in 2019. Chronic adverse health effects are now being reported as well. To address this important public health issue, an innovative approach of epidemic control and epidemiologic study is required. We aimed to assess the association between short-term and long-term use of EC products and respiratory health in adults using smartphone app data., Methods: A population-based, repeated measures, longitudinal smartphone app study that performed 8-day survey participation over 60 days for each participant from August 2020 to March 2021, including 306 participants aged 21 years and older in the US. The participants were asked to complete the respiratory health questionnaire daily, weekly, and monthly on their smartphone app. We analyzed the association between vaping habits and respiratory health using generalized linear mixed models (GLMMs)., Results: EC use in the previous 7 days was associated with frequent cough (OR: 5.15, 95% CI: 2.18, 12.21), chronic cough (OR: 3.92, 95% CI: 1.62, 9.45), frequent phlegm (OR: 3.99, 95% CI: 1.44, 11.10), chronic phlegm (OR: 3.55, 95% CI: 1.41, 8.96), episodes of cough and phlegm (OR: 4.68, 95% CI: 1.94, 11.28), mMRC grade 3-4 dyspnea (OR: 3.32, 95% CI: 1.35 to 8.13), chest cold (OR: 3.07, 95% CI: 1.29, 7.33), eye irritation (OR: 2.94, 95% CI: 1.34, 6.47) and nose irritation (OR : 2.02, 95% CI: 0.95, 4.30). Relatively long-term effects of the past 90 days EC use was associated with an increased risk of wheeze (OR: 3.04, 95% CI: 1.31, 7.03), wheeze attack (OR: 2.78, 95% CI: 1.07, 7.24), mMRC grade 3-4 dyspnea (OR: 2.54, 9% CI: 1.05 to 6.18), eye irritation (OR: 3.16, 95% CI: 1.49, 6.68), and eye irritation during the past month (OR: 3.50, 95% CI: 1.52, 8.04)., Conclusions: In this smartphone app-based repeated measures study, short-term and relatively long-term use of EC increased the risk of respiratory symptoms., (© 2024. The Author(s).)

Background: Birthing people in the United States face numerous challenges when accessing adequate prenatal care (PNC), with transportation being a significant obstacle. Nevertheless, previous studies that relied solely on the distance to the nearest provider cannot differentiate the effects of travel burden on provider selection and care utilization. These may exaggerate the degree of inequality in access and fail to capture perceived travel burden. This study investigated whether travel distances to the initially visited provider, to the predominant PNC provider, and perceived travel burden (measured by the travel disadvantage index (TDI)) are associated with PNC utilization., Methods: A retrospective cohort of people with live births were identified from South Carolina Medicaid claims files in 2015-2018. Travel distances were calculated using Google Maps. The estimated TDI was derived from local pilot survey data. PNC utilization was measured by PNC initiation and frequency. Repeated measure logistic regression test was utilized for categorical variables and one-way repeated measures ANOVA for continuous variables. Unadjusted and adjusted ordinal logistic regressions with repeated measure were utilized to examine the association of travel burdens with PNC usage., Results: For 25,801 pregnancies among those continuously enrolled in Medicaid, birthing people traveled an average of 24.9 and 24.2 miles to their initial and predominant provider, respectively, with an average TDI of -11.4 (SD, 8.5). Of these pregnancies, 60% initiated PNC in the first trimester, with an average of 8 total visits. Compared to the specialties of initial providers, predominant providers were more likely to be OBGYN-related specialists (81.6% vs. 87.9%, p < .001) and midwives (3.5% vs. 4.3%, p < .001). Multiple regression analysis revealed that every doubling of travel distance was associated with less likelihood to initiate timely PNC (OR: 0.95, p < .001) and a lower visit frequency (OR: 0.85, p < .001), and every doubling of TDI was associated with less likelihood to initiate timely PNC (OR: 0.94, p = .04)., Conclusions: Findings suggest that the association between travel burden and PNC utilization was statistically significant but of limited practical significance., (© 2024. The Author(s).)

Environmental impacts associated with shale gas exploitation have been historically underestimated due to neglecting to account for the production or the release of end-of-pipe organic pollutants. Here, we assessed the environmental impacts of shale gas production in China and the United States using life cycle assessment. Through data mining, we compiled literature information on organic pollutants in flowback and produced water (FPW), followed by assessments using USEtox to evaluate end-of-pipe risks. Results were incorporated to reveal the life cycle risks associated with shale gas exploitation in both countries. China exhibited higher environmental impacts than the US during the production phase. Substantially different types of organic compounds were observed in the FPW between two countries. Human carcinogenic and ecological toxicity attributed to organics in FPW was 3 orders of magnitude higher than that during the production phase in the US. Conversely, in China, end-of-pipe organics accounted for approximately 52%, 1%, and 47% of the overall human carcinogenic, noncarcinogenic, and ecological impacts, respectively. This may be partially limited by the quantitative data available. While uncertainties exist associated with data availability, our study highlights the significance of integrating impacts from shale gas production to end-of-pipe pollution for comprehensive environmental risk assessments.

Objective: We sought to evaluate the impact of the coronavirus disease 2019 (COVID-19) pandemic on perinatal outcomes while accounting for maternal depression or perceived stress and to describe COVID-specific stressors, including changes in prenatal care, across specific time periods of the pandemic., Study Design: Data of dyads from 41 cohorts from the National Institutes of Health Environmental influences on Child Health Outcomes Program ( N  = 2,983) were used to compare birth outcomes before and during the pandemic ( n  = 2,355), and a partially overlapping sample ( n  = 1,490) responded to a COVID-19 questionnaire. Psychosocial stress was defined using prenatal screening for depression and perceived stress. Propensity-score matching and general estimating equations with robust variance estimation were used to estimate the pandemic's effect on birth outcomes., Results: Symptoms of depression and perceived stress during pregnancy were similar prior to and during the pandemic, with nearly 40% of participants reporting mild to severe stress, and 24% reporting mild depression to severe depression. Gestations were shorter during the pandemic ( B  =  - 0.33 weeks, p  = 0.025), and depression was significantly associated with shortened gestation ( B  =  - 0.02 weeks, p  = 0.015) after adjustment. Birth weights were similar ( B  =  - 28.14 g, p  = 0.568), but infants born during the pandemic had slightly larger birth weights for gestational age at delivery than those born before the pandemic ( B  = 0.15 z-score units, p  = 0.041). More women who gave birth early in the pandemic reported being moderately or extremely distressed about changes to their prenatal care and delivery (45%) compared with those who delivered later in the pandemic. A majority (72%) reported somewhat to extremely negative views of the impact of COVID-19 on their life., Conclusion: In this national cohort, we detected no effect of COVID-19 on prenatal depression or perceived stress. However, experiencing the COVID-19 pandemic in pregnancy was associated with decreases in gestational age at birth, as well as distress about changes in prenatal care early in the pandemic., Key Points: · COVID-19 was associated with shortened gestations.. · Depression was associated with shortened gestations.. · However, stress during the pandemic remained unchanged.. · Most women reported negative impacts of the pandemic.., Competing Interests: C.M. served as Chair of the Data Safety Monitoring Board (DSMB) for an Aerogen-supported trial: A Partially-Blind, Randomized, Controlled, Parallel-Group Dose Ranging Study to Determine the Efficacy, Safety and Tolerability of AeroFactTM (SF-RI 1 surfactant for inhalation combined with a dedicated drug delivery system) in Preterm Infants at Risk for Worsening Respiratory Distress Syndrome; Chair of the DSMB for the NIH RCT evaluating Sildenafil in Preterm Infants with Pulmonary Hypertension. J.N. served on the Advisory Board for the Twin Life Study (Germany); received royalties or licenses from Macmillan and consulting fees from the University of Southern California. J.H. served on the New York State Drinking Water Quality Council. The other authors have no conflicts of interest to disclose., (Thieme. All rights reserved.)

In the United States, assistance from the Department of Housing and Urban Development (HUD) plays an essential role in supporting the postdisaster recovery of states with unmet housing needs. HUD requires data on unmet needs to appropriate recovery funds. Ground truth data are not available for months after a disaster, however, so HUD uses a simplified approach to estimate unmet housing needs. State authorities argue that HUD's simplified approach underestimates the state's needs. This article presents a methodology to estimate postdisaster unmet housing needs that is accurate and relies only on data obtained shortly after a disaster. Data on the number of damaged buildings are combined with models for expected repair costs. Statistical models for aid distributed by the Federal Emergency Management Agency (FEMA) and the Small Business Administration (SBA) are then developed and used to forecast funding provided by those agencies. With these forecasts, the unmet need to be funded by HUD is estimated. The approach can be used for multiple states and hazard types. As validation, the proposed methodology is used to estimate the unmet housing needs following disasters that struck California in 2017. California authorities suggest that HUD's methodology underestimated the state's needs by a factor of 20. Conversely, the proposed methodology can replicate the estimates by the state authorities and provide accounts of losses, the amount of funding from FEMA and SBA, and the total unmet housing needs without requiring data unavailable shortly after a disaster. Thus, the proposed methodology can help improve HUD's funding appropriation without delays., (© 2023 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

Objectives: The COVID-19 pandemic changed the setting of education for many children in the U.S. Understanding COVID-19 vaccination coverage by educational setting is important for developing targeted messages, increasing parents' confidence in COVID-19 vaccines, and protecting all children from severe effects of COVID-19 infection., Study Design/methods: Using data from the Household Pulse Survey (n = 25,173) collected from December 9-19, 2022, January 4-16, 2023, and February 1-13, 2023, this study assessed factors associated with COVID-19 vaccination and reasons for non-vaccination among school-aged children 5-11 and adolescents 12-17 by educational setting., Results: Among children 5-11 years, COVID-19 vaccination coverage was higher among those who received in-person instruction (53.7%) compared to those who were homeschooled (32.5%). Furthermore, among adolescents 12-17 years, COVID-19 vaccination coverage was higher among those who received in-person instruction (73.5%) or virtual/online instruction (70.1%) compared to those who were homeschooled (51.0%). Children and adolescents were more likely to be vaccinated if the parental respondent had been vaccinated compared to those who had not. Among children and adolescents who were homeschooled, main reasons for non-vaccination were concern about side effects (45.4-51.6%), lack of trust in COVID-19 vaccines (45.0-50.9%), and lack of trust in the government (32.7-39.2%)., Conclusions: Children and adolescents who were home-schooled during the pandemic had lower vaccination coverage than those who attended school in person, and adolescents who were home-schooled had lower vaccination coverage than those who received virtual instruction. Based on the reasons for non-vaccination identified in this study, increasing parental confidence in vaccines, and reducing barriers to access are important for supporting COVID-19 vaccination for school-age children., (Copyright © 2024 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

Future climate change can cause more days with poor air quality. This could trigger more alerts telling people to stay inside to protect themselves, with potential consequences for health and health equity. Here, we study the change in US air quality alerts over this century due to fine particulate matter (PM 2.5 ), who they may affect, and how they may respond. We find air quality alerts increase by over 1 mo per year in the eastern United States by 2100 and quadruple on average. They predominantly affect areas with high Black populations and leakier homes, exacerbating existing inequalities and impacting those less able to adapt. Reducing emissions can offer significant annual health benefits ($5,400 per person) by mitigating the effect of climate change on air pollution and its associated risks of early death. Relying on people to adapt, instead, would require them to stay inside, with doors and windows closed, for an extra 142 d per year, at an average cost of $11,000 per person. It appears likelier, however, that people will achieve minimal protection without policy to increase adaptation rates. Boosting adaptation can offer net benefits, even alongside deep emission cuts. New adaptation policies could, for example: reduce adaptation costs; reduce infiltration and improve indoor air quality; increase awareness of alerts and adaptation; and provide measures for those working or living outdoors. Reducing emissions, conversely, lowers everyone's need to adapt, and protects those who cannot adapt. Equitably protecting human health from air pollution under climate change requires both mitigation and adaptation., Competing Interests: Competing interests statement:The authors declare no competing interest.

While human mobility plays a crucial role in determining ambient air pollution exposures and health risks, research to date has assessed risks on the basis of almost solely residential location. Here, we leveraged a database of ∼128-144 million workers in the United States and published ambient PM 2.5 data between 2011 and 2018 to explore how incorporating information on both workplace and residential location changes our understanding of disparities in air pollution exposure. In general, we observed higher workplace exposures relative to home exposures, as well as increased exposures for nonwhite and less educated workers relative to the national average. Workplace exposure disparities were higher among racial and ethnic groups and job types than by income, education, age, and sex. Not considering workplace exposures can lead to systematic underestimations in disparities in exposure among these subpopulations. We also quantified the error in assigning workers home instead of a weighted home-and-work exposure. We observed that biases in associations between PM 2.5 and health impacts by using home instead of home-and-work exposure were the highest among urban, younger populations.

Electrifying freight trucks will be key to alleviating air pollution burdens on disadvantaged communities and mitigating climate change. The United States plans to pursue this aim by adding vehicle charging infrastructure along specific freight corridors. This study explores the coevolution of the electricity grid and freight trucking landscape using an integrated assessment framework to identify when each interstate and drayage corridor becomes advantageous to electrify from a climate and human health standpoint. Nearly all corridors achieve greenhouse gas emission reductions if electrified now. Most can reduce health impacts from air pollution if electrified by 2040 although some corridors in the Midwest, South, and Mid-Atlantic regions remain unfavorable to electrify from a human health standpoint, absent policy support. Recent policy, namely, the Inflation Reduction Act, accelerates this timeline to 2030 for most corridors and results in net human health benefits on all corridors by 2050, suggesting that near-term investments in truck electrification, particularly drayage corridors, can meaningfully reduce climate and health burdens.

Objective: Crashes involving golf carts (GCs) have been on an increasing trend in recent years, particularly in the United States. This study focuses on analyzing GC crashes in the Florida community known as The Villages, one of the largest GC-oriented communities in the nation and worldwide. The objective was to evaluate the injury severity of crashes involving GCs in a retirement community where GCs are a common mode of transportation., Methods: The ordinal logistic regression (OLR) and Decision Tree Ensemble (DTE) models were used to analyze the injury severity of 616 GC-related crashes. Models' accuracy parameters were used to check their reliability., Results: The analysis revealed that GC crash severity is influenced by various factors. Factors found to be significant by the OLR model in determining injury severity include ejection of one or more occupants from the GC, the extent of damage to the GC, GC speed prior to the crash, roadway characteristics (including divided roadways, traffic control devices, paved shoulders, and T-intersections), and roll-over incidents. The OLR model demonstrated an overall accuracy of approximately 71% in predicting injury severity. The DTE model performed better, with an overall accuracy of 78%. The OLR model's findings were supported by the DTE model, which identified estimated GC speed, occupant(s) ejection from the GC, estimated GC vehicle damage, intersection type, and type of shoulder as the most important factors influencing GC crash severity., Conclusions: Understanding these factors is vital for transportation agencies to develop effective strategies to reduce the severity of GC crashes, ensuring the safety of GC users. This study provides recommendations to transportation agencies on measures to improve the safety of GCs.

Water table depth (WTD) has a substantial impact on the connection between groundwater dynamics and land surface processes. Due to the scarcity of WTD observations, physically-based groundwater models are growing in their ability to map WTD at large scales; however, they are still challenged to represent simulated WTD compared to well observations. In this study, we develop a purely data-driven approach to estimating WTD at continental scale. We apply a random forest (RF) model to estimate WTD over most of the contiguous United States (CONUS) based on available WTD observations. The estimated WTD are in good agreement with well observations, with a Pearson correlation coefficient (r) of 0.96 (0.81 during testing), a Nash-Sutcliffe efficiency (NSE) of 0.93 (0.65 during testing), and a root mean square error (RMSE) of 6.87 m (15.31 m during testing). The location of each grid cell is rated as the most important feature in estimating WTD over most of the CONUS, which might be a surrogate for spatial information. In addition, the uncertainty of the RF model is quantified using quantile regression forests. High uncertainties are generally associated with locations having a shallow WTD. Our study demonstrates that the RF model can produce reasonable WTD estimates over most of the CONUS, providing an alternative to physics-based modeling for modeling large-scale freshwater resources. Since the CONUS covers many different hydrologic regimes, the RF model trained for the CONUS may be transferrable to other regions with a similar hydrologic regime and limited observations., (© 2023 The Authors. Groundwater published by Wiley Periodicals LLC on behalf of National Ground Water Association.)

Recent efforts to identify disadvantaged communities (DACs) on a census tract level have evoked possibilities of attaining transportation justice and vision zero goals in these areas. To identify DACs, the United States Department of Transportation (USDOT) has developed six comprehensive indicators: economy, environment, equity, health, resilience, and transportation access. The indicators are used to explore the associations between DACs (in 71,728 census tracts) and five years of fatal crashes, providing a comprehensive understanding of safety risks. Specifically, using data on DACs and linking it with census and crash data, this study aims to understand the complex connections between safety (captured through fatal crashes) and disadvantages that communities confront due to a convergence of multiple challenges and burdens using Zero-Hurdle Negative Binomial models. The results reveal that health, resilience, and transportation-disadvantaged tracts are associated with more fatal crashes. The study also found the presence of a higher percentage of the population with bachelor's degrees and increased use of public transportation are correlated with fewer fatal crashes. Also, a higher fatal crash rate is observed in disadvantaged census tracts where a high proportion of the Hawaiian or other Pacific Islander, and American Indian or Alaska Native populations live. This implies that targeted interventions can be explored further in tracts that show high correlations with fatal crashes. The findings contribute to traffic safety by highlighting the risks in DACs, which can help design and implement traffic safety interventions. The insights gained from this study can inform decision-making and help to guide the development of more equitable traffic safety programs in disadvantaged communities., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Within coastal communities, sea level rise (SLR) will result in widespread intermittent flooding and long-term inundation. Inundation effects will be evident, but isolation that arises from the loss of accessibility to critical services due to inundation of transportation networks may be less obvious. We examine who is most at risk of isolation due to SLR, which can inform community adaptation plans and help ensure that existing social vulnerabilities are not exacerbated. Combining socio-demographic data with an isolation metric, we identify social and economic disparities in risk of isolation under different SLR scenarios (1-10 ft) for the coastal U.S. We show that Black and Hispanic populations face a disproportionate risk of isolation at intermediate levels of SLR (4 ft and greater). Further, census tracts with higher rates of renters and older adults consistently face higher risk of isolation. These insights point to significant inequity in the burdens associated with SLR., (© 2023. The Author(s).)

Background: In the United States, disparities in gestational age at birth by maternal race, ethnicity, and geography are theorized to be related, in part, to differences in individual- and neighborhood-level socioeconomic status (SES). Yet, few studies have examined their combined effects or whether associations vary by maternal race and ethnicity and United States Census region., Methods: We assembled data from 34 cohorts in the Environmental influences on Child Health Outcomes (ECHO) program representing 10,304 participants who delivered a liveborn, singleton infant from 2000 through 2019. We investigated the combined associations of maternal education level, neighborhood deprivation index (NDI), and Index of Concentration at the Extremes for racial residential segregation (ICE Race ) on gestational weeks at birth using linear regression and on gestational age at birth categories (preterm, early term, post-late term relative to full term) using multinomial logistic regression., Results: After adjustment for NDI and ICE Race , gestational weeks at birth was significantly lower among those with a high school diploma or less (-0.31 weeks, 95% CI: -0.44, -0.18), and some college (-0.30 weeks, 95% CI: -0.42, -0.18) relative to a master's degree or higher. Those with a high school diploma or less also had an increased odds of preterm (aOR 1.59, 95% CI: 1.20, 2.10) and early term birth (aOR 1.26, 95% CI: 1.05, 1.51). In adjusted models, NDI quartile and ICE Race quartile were not associated with gestational weeks at birth. However, higher NDI quartile (most deprived) associated with an increased odds of early term and late term birth, and lower ICE Race quartile (least racially privileged) associated with a decreased odds of late or post-term birth. When stratifying by region, gestational weeks at birth was lower among those with a high school education or less and some college only among those living in the Northeast or Midwest. When stratifying by race and ethnicity, gestational weeks at birth was lower among those with a high school education or less only for the non-Hispanic White category., Conclusion: In this study, maternal education was consistently associated with shorter duration of pregnancy and increased odds of preterm birth, including in models adjusted for NDI and ICE Race ., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Dunlop, Burjak, Dean, Alshawabkeh, Avalos, Aschner, Breton, Charifson, Cordero, Dabelea, D’Sa, Duarte, Elliott, Eick, Ferrara, Fichorova, Ganiban, Gern, Hedderson, Herbstman, Hipwell, Huddleston, Karagas, Karr, Kerver, Koinis-Mitchell, Lyall, Madan, Marsit, McEvoy, Meeker, Oken, O’Shea, Padula, Sathyanarayana, Schantz, Schmidt, Snowden, Stanford, Weiss, Wright, Wright, Zhang and McGrath.)

Due to the complexity of the automobile manufacturing process, some flexible and delicate assembly work relies on manual operations. However, high-frequency and high-load repetitive operations make assembly workers prone to physical fatigue. This study proposes a method for evaluating human physical fatigue for the manual assembly of automobiles with methods: NIOSH (National Institute for Occupational Safety and Health), OWAS (Ovako Working Posture Analysis System) and RULA (Rapid Upper Limb Assessment). The cerebral oxygenation signal is selected as an objective physiological index reflecting the human fatigue level to verify the proposed physical fatigue evaluation method. Taking auto seat assembly and automobile manual assembly as an example, 18 group experiments were carried out with the ARE platform (Augmented Reality-based Ergonomic Platform). Furthermore, predictions of metabolic energy expenditure were performed for experiments in Tecnomatix Jack. Finally, it is concluded that the proposed physical fatigue evaluation method can reflect the human physical fatigue level and is more accurate than the evaluation of metabolic energy consumption in Tecnomatix Jack because of the immersion that comes with the AR devices and the precision that comes with motion capture devices.

To assess the public health impact of the COVID-19 pandemic on mental health, investigators from the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) research program developed the Pandemic-Related Traumatic Stress Scale (PTSS). Based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) acute stress disorder symptom criteria, the PTSS is designed for adolescent (13-21 years) and adult self-report and caregiver-report on 3-12-year-olds. To evaluate psychometric properties, we used PTSS data collected between April 2020 and August 2021 from non-pregnant adult caregivers ( n = 11,483), pregnant/postpartum individuals ( n = 1,656), adolescents ( n = 1,795), and caregivers reporting on 3-12-year-olds ( n = 2,896). We used Mokken scale analysis to examine unidimensionality and reliability, Pearson correlations to evaluate relationships with other relevant variables, and analyses of variance to identify regional, age, and sex differences. Mokken analysis resulted in a moderately strong, unidimensional scale that retained nine of the original 10 items. We detected small to moderate positive associations with depression, anxiety, and general stress, and negative associations with life satisfaction. Adult caregivers had the highest PTSS scores, followed by adolescents, pregnant/postpartum individuals, and children. Caregivers of younger children, females, and older youth had higher PTSS scores compared to caregivers of older children, males, and younger youth, respectively. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The ninth American Society for Microbiology Conference on Biofilms was convened in-person on 13-17 November 2022 in Charlotte, NC. As the first of these conferences since prior to the start of the COVID-19 pandemic, the energy among the participants of the conference was clear, and the meeting was a tremendous success. The mixture of >330 oral and poster presentations resoundingly embodied the vitality of biofilm research across a wide range of topics and multiple scientific disciplines. Special activities, including a pre-conference symposium for early career researchers, further enhanced the attendee experience. As a general theme, the conference was deliberately structured to provide high levels of participation and engagement among early career scientists., Competing Interests: The authors declare no conflict of interest.

Alaska is one of the most seismically active regions of the world. Coincidentally, the state has also experienced dramatic impacts of climate change as it is warming at twice the rate of the rest of the United States. Through mechanisms such as permafrost thaw, water table fluctuation, and melting of sea ice and glaciers, climatic-driven changes to the natural and built-environment influence the seismic response of infrastructure systems. This paper discusses the challenges and needs posed by earthquake hazards and climate change to Alaska's infrastructure and built environment, drawing on the contributions of researchers and decision-makers in interviews and a workshop. It outlines policy, mitigation, and adaptation areas meriting further attention to improve the seismic resilience of Alaska's built environment from the perspectives of engineering and complementary coupled human-environmental systems., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Turner et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Identifying sources of pollutants in watersheds is critical to accurately predicting stormwater quality. Many existing software used to model stormwater quality rely on decades-old data sets which may not represent current runoff quality in the United States. Because of environmental regulations promulgated at the federal level over previous decades, there is a need to understand long-term trends (and potential shifts) in runoff quality to better parameterize models. Pollutant event mean concentrations (EMCs) from the National Stormwater Quality Database (NSQD) were combined with those from recent sources to understand if untreated stormwater quality has changed over the past 40 years. A significant decreasing monotonic trend (i.e., continually decreasing in a nonuniform fashion) was observed for total suspended solids (TSS), total phosphorus (TP), total Kjeldahl nitrogen (TKN), total copper (Cu), total lead (Pb), and total zinc (Zn) in the resultant database, suggesting that runoff quality has become less polluted with time. Median EMCs decreased from 99.2 to 42 mg/L, 0.34 to 0.26 mg/L, 1.27 to 1.03 mg/L, 40 to 6.8 µg/L, 110 to 3.7 µg/L, and 375 to 53.3 µg/L for TSS, TP, TN, Cu, Pb, and Zn, respectively, from the 1980s to the 2010s. These significant reductions often aligned temporally with advancements in clean manufacturing, amendments of the Clean Air Act, and other source control efforts which impact pollutant bioavailability and atmospheric deposition. Results suggest environmental regulations not specifically targeting stormwater management have had a positive impact on stormwater quality and that temporal fluctuations should be considered in modeling., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

We assessed COVID-19 booster vaccination coverage and reasons for non-receipt using a large, nationally representative survey (June - August, 2022). Booster vaccination coverage was 71.7% among adults, 36.8% among children, and 51.6% among adolescents. Reasons for non-receipt included the belief that it was not necessary and lack of time for vaccination. All eligible individuals should receive the updated booster vaccines as soon as possible to protect against new variants of COVID-19., (Copyright © 2023 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Deployment of clinical testing on a massive scale was an essential control measure for curtailing the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the magnitude of the COVID-19 (coronavirus disease 2019) pandemic during its waves. As the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementation of vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 antigen tests reduced the demand for mass SARS-CoV-2 testing. Unfortunately, reductions in testing and test reporting rates also reduced the availability of public health data to support decision-making. This paper proposes a sequential Bayesian approach to estimate the COVID-19 test positivity rate (TPR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. The proposed modeling framework was applied to WW surveillance data from two WW treatment plants in California; the City of Davis and the University of California, Davis campus. TPR estimates are used to compute thresholds for WW data using the Centers for Disease Control and Prevention thresholds for low (<5% TPR), moderate (5%-8% TPR), substantial (8%-10% TPR), and high (>10% TPR) transmission. The effective reproductive number estimates are calculated using TPR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. IMPORTANCE We propose a statistical model to correlate WW with TPR to monitor COVID-19 trends and to help overcome the limitations of relying only on clinical case detection. We pose an adaptive scheme to model the nonautonomous nature of the prolonged COVID-19 pandemic. The TPR is modeled through a Bayesian sequential approach with a beta regression model using SARS-CoV-2 RNA concentrations measured in WW as a covariable. The resulting model allows us to compute TPR based on WW measurements and incorporates changes in viral transmission dynamics through an adaptive scheme., Competing Interests: The authors declare no conflict of interest.

Molecular biology methods and technologies have advanced substantially over the past decade. These new molecular methods should be incorporated among the standard tools of planetary protection (PP) and could be validated for incorporation by 2026. To address the feasibility of applying modern molecular techniques to such an application, NASA conducted a technology workshop with private industry partners, academics, and government agency stakeholders, along with NASA staff and contractors. The technical discussions and presentations of the Multi-Mission Metagenomics Technology Development Workshop focused on modernizing and supplementing the current PP assays. The goals of the workshop were to assess the state of metagenomics and other advanced molecular techniques in the context of providing a validated framework to supplement the bacterial endospore-based NASA Standard Assay and to identify knowledge and technology gaps. In particular, workshop participants were tasked with discussing metagenomics as a stand-alone technology to provide rapid and comprehensive analysis of total nucleic acids and viable microorganisms on spacecraft surfaces, thereby allowing for the development of tailored and cost-effective microbial reduction plans for each hardware item on a spacecraft. Workshop participants recommended metagenomics approaches as the only data source that can adequately feed into quantitative microbial risk assessment models for evaluating the risk of forward (exploring extraterrestrial planet) and back (Earth harmful biological) contamination. Participants were unanimous that a metagenomics workflow, in tandem with rapid targeted quantitative (digital) PCR, represents a revolutionary advance over existing methods for the assessment of microbial bioburden on spacecraft surfaces. The workshop highlighted low biomass sampling, reagent contamination, and inconsistent bioinformatics data analysis as key areas for technology development. Finally, it was concluded that implementing metagenomics as an additional workflow for addressing concerns of NASA's robotic mission will represent a dramatic improvement in technology advancement for PP and will benefit future missions where mission success is affected by backward and forward contamination.

Data chronicling the geo-locations of all 61,589 pharmacies in the U.S. (from the Homeland Infrastructure Foundation-Level Data (HIFLD) Open Data interface, updated on April 2018) across 215,836 census block groups were combined with Medically Underserved Areas (MUAs) information, and the Centers for Disease Control and Prevention's Social Vulnerability Index (CDC-SVI). Geospatial techniques were applied to calculate the distance between the center of each census block and the nearest pharmacy. We then modeled the expected additional travel distance if the nearest pharmacy to the center of a census block closed and estimated additional travel costs, CO2 emissions, and lost labor productivity costs associated with the additional travel. Our findings revealed that MUA residents have almost two times greater travel distances to pharmacies than non-MUAs (4,269 m (2.65 mi) vs. 2,388 m (1.48 mi)), and this disparity is exaggerated with pharmacy closures (107% increase in travel distance in MUAs vs. 75% increase in travel distance in non-MUAs). Similarly, individuals living in MUAs experience significantly greater average annual economic costs than non-MUAs ($34,834 ± $668 vs. $22,720 ± $326). Our findings suggest the need for additional regulations to ensure populations are not disproportionately affected by these closures and that there is a significant throughput with community stakeholders before any pharmacy decides to close., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Introduction: The COVID-19 pandemic affected the lives of military members and their families, with over 400,000 cases among U.S. military members since the start of the pandemic. The objective of this study is to examine and compare COVID-19 vaccination coverage of military members (active duty and Reserve/National Guard) and their family members (spouses, children, and adolescents) to that of their civilian counterparts using a large, nationally representative study., Methods: Data from March 2 to May 9, 2022, of the Household Pulse Survey were analyzed for this study (n = 207,758). COVID-19 vaccination status (≥1 dose) was assessed for military members and their spouses, civilians, and children (aged 5 to 11 and 12 to 17 years) from both military and civilian families. Differences between military members, spouses, and their children compared to civilian adults and children were assessed using chi-squared and t-tests. Multivariable logistic regression was used to examine the association between military status and COVID-19 vaccination after controlling for sociodemographic characteristics. Reasons for not getting vaccinated for adults and children from military and civilian families were assessed., Results: Compared to civilian adults and adjusted for sociodemographic characteristics, military members were more likely to be vaccinated (adjusted prevalence ratio = 1.07, 95% CI: 1.01-1.13). Vaccination coverage between active duty and civilian adults differed by subgroups. For example, among military members, COVID-19 vaccination coverage decreased with increasing age, from 87.5% among those aged 18 to 39 years to 56.0% among those aged ≥55 years. In contrast, among civilian adults, vaccination coverage increased with increasing age, from 78.5% among those aged 18 to 39 years to 91.2% among those aged ≥55 years. Military members were also less likely to be vaccinated than their civilian counterparts if they were Hispanic (68.5% vs. 85.2%), had a Bachelor's degree or higher (87.5% vs. 93.8%), or had $100,000 or more in annual household income (76.7% vs. 92.6%). Military members who had anxiety or depression (70.1%) were less likely to be vaccinated compared to civilian adults (84.4%). Military spouses (74.4%) were less likely to be vaccinated than civilian adults (84.7%). Children and adolescents who were homeschooled (35.1%) or had no preventive checkups in the past year (32.4%) were less likely to be vaccinated than their respective counterparts (52.5% and 54.0%, respectively). Military adults compared to civilian adults were more likely to report lack of trust in the government (47.5% vs. 35.2%) and, for children/adolescents, the belief that the vaccine is not needed (42.1% vs. 28.1%) as reasons for non-vaccination., Conclusions: Despite vaccine mandates and the high vaccination coverage found among the majority of military members, disparities exist in some subgroups. Educational interventions and increased communication from trusted leaders, such as medical providers and commanders, could increase confidence in vaccines among military families. Ensuring access to vaccines, empowering healthcare providers to recommend vaccines, and reminding parents of missed vaccinations or preventive checkups can help improve vaccination coverage. Achieving high vaccination among military members and their families is essential in protecting those in the forefront of the pandemic response and promoting the safety and security of the nation., (© The Association of Military Surgeons of the United States 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

New tools can guide US policies to better target and reduce racial and socioeconomic disparities in air pollution exposure.

The coronavirus disease 2019, or COVID-19, has impacted countless aspects of everyday life since it was declared a global pandemic by the World Health Organization in March of 2020. From societal to economic impacts, COVID-19 and its variants will leave a lasting impact on our society and the world. During the height of the pandemic, it became increasingly evident that indices, such as the Center for Disease Control's (CDC) Social Vulnerability Index (SVI), were instrumental in predicting vulnerabilities within a community. The CDC's SVI provides important estimates on which communities will be more susceptible to 'hazard events' by compiling a variety of data from the U.S. Census and the American Community Survey. The CDC's SVI does not directly consider the susceptibility of a community to a global pandemic, such as the COVID-19 pandemic, due to the four themes and 15 factors that contribute to the index. Thus, the objective of this research is to develop a COVID-19 Vulnerability Index, or CVI, to evaluate a community's susceptibility to future pandemics. With 15 factors considered for CDC's SVI, 26 other factors were also considered for the development of the CVI that covered themes such as socioeconomic status, environmental factors, healthcare capacity, epidemiological factors, and disability. All factors were equally weighted to calculate the CVI based on New Jersey. The CVI was validated by comparing index results to real-world COVID-19 data from New Jersey's 21 counties and CDC's SVI. The results present a stronger positive linear relationship between the CVI and the New Jersey COVID-19 mortality/population and infection/population than there is with the SVI. The results of this study indicate that Essex County has the highest CVI, and Hunterdon County has the lowest CVI. This is due to factors such as disparity in wealth, population density, minority status, and housing conditions, as well as other factors that were used to compose the CVI. The implications of this research will provide a critical tool for decision makers to utilize in allocating resources should another global pandemic occur. This CVI, developed through this research, can be used at the county, state, and global levels to help measure the vulnerability to future pandemics.