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Abstract This study explores the outcomes and impacts of sanitary sewer overflows (SSOs) and basement backups in underserved communities in Baltimore, Maryland. The larger effort is an environmental and community-driven mixed-methods project, however, the research in this manuscript focuses on the household survey portion with residents who have experienced SSOs or sewage backups. Based on the snowball sampling method applied, the resulting residents engaged are predominantly African-American individuals, females, homeowners, and residents between the ages of 50 and 69. Strikingly, 70% of respondents reported that their frequency of SSOs is between moderate to frequent. The findings reveal that SSOs are a pervasive issue affecting residents’ physical and mental health and overall quality of life. Despite residents’ perceptions that their household infrastructure is in good condition, the recurring nature of SSOs highlights systemic problems within the city’s aging sewer systems, urging a deeper understanding of the social and structural vulnerabilities involved. This research calls attention to the importance of comprehensive interventions, including effective risk communication strategies and substantial investment in infrastructure rehabilitation, to mitigate the risks posed by SSOs and promote long-term resilience in urban environments. Additionally, it emphasizes the importance of community-driven research in addressing engineering, urban planning, and public health challenges with particular support for the most affected populations. 

Abstract Rapid urbanization and escalating climate change impacts have heightened stormwater-related concerns (e.g., pluvial flooding) in cities. Understanding catchment dynamics and characteristics, including precise catchment mapping, is essential to accurate surface water monitoring and management. Traditionally, topography is the primary data set used to model surface water flow dynamics in undisturbed natural landscapes. However, urban systems also contain stormwater drainage infrastructure, which can alter catchment boundaries and runoff behavior. Acknowledging both natural and built environmental influences, this study introduces three GIS-based approaches to enhance urban catchment mapping: (1) Modifying DEM elevations at inlet locations; (2) Adjusting DEM elevations along pipeline paths; (3) Applying the QGRASS plug-in to systematically incorporate infrastructure data. Our evaluation using the geographical Friedman test (p > 0.05) and Dice Similarity Coefficient (DSC = 0.80) confirms the statistical and spatial consistency among the studying methods. Coupled with onsite flow direction validation, these results support the feasibility and reliability of integrating elements of nature and built infrastructure in urban catchment mapping. The refined mapping approaches explored in this study offer improved and more accurate and efficient urban drainage catchment zoning, beyond using elevation and topographic data alone. Likewise, these methods bolster predictive stormwater management at catchment scales, ultimately strengthening urban stormwater and flooding resilience. 

Abstract In Cameroon, dietary staples are frequently contaminated with diverse toxic fungal metabolites, known as mycotoxins. Aflatoxins and fumonisins are a public health concern, particularly concerning cancer and/or early life stunting. Mycotoxin mixtures are predicted from food measures; and this study reports the levels and frequencies of urinary mycotoxin biomarkers in Cameroonian adults. A single first void urine sample was collected from 89 adults from Yaoundé, Cameroon. Urine samples were tested for eight distinct mycotoxins using measures of both parent compounds and/or their metabolites by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Altogether, seven distinct mycotoxins, aflatoxin, fumonisin, deoxynivalenol, zearalenone, nivalenol, ochratoxin A, and citrinin, (or their metabolites) were observed in urine samples. At least one mycotoxin was detected in all of the urine samples, 87 (98%) of which were above the limit of quantitation. Aflatoxin M₁was detected in 42% (n.d.-0.21 μg/l) of samples of which about a quarter additionally contained fumonisin B₁. Of the remaining toxins deoxynivalenol (78%), zearalenone (99%), ochratoxin A (95%), nivalenol (53%), and citrinin (87%) were present in the samples. Alternariol was not detected in any sample. Mixtures of mycotoxins in the samples were frequently observed with 64 samples (72%) containing more than five mycotoxin exposure biomarkers. Estimates of intake exceeded the TDIs for fumonisin B₁(n = 4), deoxynivalenol (n = 1) and zearalenone (n = 2), no TDI is set for aflatoxin. This study reveals frequent co-exposure of Cameroonian individuals to a complex mixture of toxic and carcinogenic mycotoxins, with mixtures of aflatoxin and fumonisin being a particular priority from a public health standpoint. 

Abstract Untreated sewage discharges leading to environmental contamination are increasingly common in communities across the globe. The cause of these discharges ranges from sewer lines in disrepair, blockages, and in the era of more extreme wet weather events, the infiltration of stormwater into the system during heavy downpours. Regardless of the driver of these events, the aftermath results in raw sewage spilling into local waterways, city streets, and commercial and residential structures. Historical research in public health has thoroughly documented the connection between exposure to untreated sewage and waterborne disease. Recent research has detected antibiotic-resistant bacteria at wastewater treatment facilities at a time when deaths by antibiotic-resistant infections are on the rise. However, no research has explored the exposure pathways of antibiotic-resistant bacteria during sanitary sewer overflows and household-level sewage backups. In this commentary, we aim to introduce this new frontier of environmental health risks and disasters. To do this, we describe the history of modern sanitation and sewer infrastructure with a particular focus on wastewater infrastructure in the U.S. We also explore emerging risks and current methods for identifying antibiotic-resistant bacteria in the environment. We end with future directions for interdisciplinary scholarship at the nexus of urban planning, engineering, and public health by introducing the Water Emergency Team (WET) Project. WET is a community-based multi-method effort to identify environmental risks in the aftermath of household backups through (1) residential surveys, (2) indoor visual inspections, (3) environmental sampling, and (4) laboratory processing and reporting. Our hope is that by introducing this comprehensive approach to environmental risks analysis, other scholars will join us in this effort and ultimately towards addressing this grand challenge of our time. 

Abstract Ongoing climate variability and change are increasing the burden of diarrhoeal disease worldwide. Meaningful early warning systems with adequate lead times (weeks to months) are needed to guide public health decision–making and enhance community resilience against health threats posed by climate change. Toward this goal, we trained various machine-learning models to predict diarrhoeal disease rates in Nepal (2002–2014), Taiwan (2008–2019), and Vietnam (2000–2015) using temperature, precipitation, previous disease rates, and El Niño Southern Oscillation phases. We also compared the performance of shallow time-series neural network (NN), Random Forest Regressor, artificial nn, gradient boosting regressor, and long short-term memory–based methods for their effectiveness in predicting diarrhoeal disease burden across multiple countries. We evaluated model performance using a test dataset and assessed the accuracy of predicted diarrhoeal disease incidence rates for the last year of available data in each district. Our results suggest that even in the absence of the most recent disease surveillance data, a likely scenario in most low- and middle-income countries, our NN-based early warning system using historical data performs reasonably well. However, future studies are needed to perform prospective evaluations of such early warning systems in real-world settings. 

ABSTRACT Antibiotics are often used to treat severeVibrioinfections, with third-generation cephalosporins and tetracyclines combined or fluoroquinolones alone being recommended by the US Centers for Disease Control and Prevention. Increases in antibiotic resistance of both environmental and clinical vibrios are of concern; however, limited longitudinal data have been generated among environmental isolates to inform how resistance patterns may be changing over time. Hence, we evaluated long-term trends in antibiotic resistance of vibrios isolated from Chesapeake Bay waters (Maryland) across two 3-year sampling periods (2009–2012 and 2019–2022).Vibrio parahaemolyticus(n= 134) andVibrio vulnificus(n= 94) toxR-confirmed isolates were randomly selected from both sampling periods and tested for antimicrobial susceptibility against eight antibiotics using the Kirby-Bauer disk diffusion method. A high percentage (94%–96%) ofV. parahaemolyticusisolates from both sampling periods were resistant to ampicillin and only 2%–6% of these isolates expressed intermediate resistance or resistance to third-generation cephalosporins, amikacin, tetracycline, and trimethoprim-sulfamethoxazole. Even lower percentages of resistantV. vulnificusisolates were observed and those were mostly recovered from 2009 to 2012, however, the presence of multiple virulence factors was observed. The frequency of multi-drug resistance was relatively low (6%–8%) but included resistance against antibiotics used to treat severe vibriosis in adults and children. All isolates were susceptible to ciprofloxacin, a fluoroquinolone, indicating its sustained efficacy as a first-line agent in the treatment of severe vibriosis. Overall, our data indicate that antibiotic resistance patterns amongV. parahaemolyticusandV. vulnificusrecovered from the lower Chesapeake Bay have remained relatively stable since 2009.IMPORTANCEVibriospp. have historically been susceptible to most clinically relevant antibiotics; however, resistance and intermediate-resistance have been increasingly recorded in both environmental and clinical isolates. Our data showed that while the percentage of multi-drug resistance and resistance to antibiotics was relatively low and stable across time, someVibrioisolates displayed resistance and intermediate resistance to antibiotics typically used to treat severe vibriosis (e.g., third-generation cephalosporins, tetracyclines, sulfamethoxazole-trimethoprim, and aminoglycosides). Also, given the high case fatality rates observed withVibrio vulnificusinfections, the presence of multiple virulence factors in the tested isolates is concerning. Nevertheless, the continued susceptibility of all tested isolates against ciprofloxacin, a fluoroquinolone, is indicative of its use as an effective first-line treatment of severeVibriospp. infections stemming from exposure to Chesapeake Bay waters or contaminated seafood ingestion. 

ABSTRACT Alternative irrigation waters (rivers, ponds, and reclaimed water) can harbor bacterial foodborne pathogens likeSalmonella entericaandListeria monocytogenes, potentially contaminating fruit and vegetable commodities. Detecting foodborne pathogens using qPCR-based methods may accelerate testing methods and procedures compared to culture-based methods. This study compared detectionof S. enterica and L. monocytogenesby qPCR (real-time PCR) and culture methods in irrigation waters to determine the influence of water type (river, pond, and reclaimed water), season (winter, spring, summer, and fall), or volume (0.1, 1, and 10 L) on sensitivity, accuracy, specificity, and positive (PPV), and negative (NPV) predictive values of these methods. Water samples were collected by filtration through modified Moore swabs (MMS) over a 2-year period at 11 sites in the Mid-Atlantic U.S. on a bi-weekly or monthly schedule. For qPCR, bacterial DNA from culture-enriched samples (n= 1,990) was analyzed by multiplex qPCR specific forS. entericaandL. monocytogenes. For culture detection, enriched samples were selectively enriched, isolated, and PCR confirmed. PPVs for qPCR detection ofS. entericaandL. monocytogeneswere 68% and 67%, respectively. The NPV were 87% (S. enterica) and 85% (L. monocytogenes). Higher levels of qPCR/culture agreement were observed in spring and summer compared to fall and winter forS. enterica; forL. monocytogenes, lower levels of agreement were observed in winter compared to spring, summer, and fall. Reclaimed and pond water supported higher levels of qPCR/culture agreement compared to river water for bothS. entericaandL. monocytogenes, indicating that water type may influence the agreement of these results. IMPORTANCEDetecting foodborne pathogens in irrigation water can inform interventions and management strategies to reduce risk of contamination and illness associated with fresh and fresh-cut fruits and vegetables. The use of non-culture methods like qPCR has the potential to accelerate the testing process. Results indicated that pond and reclaimed water showed higher levels of agreement between culture and qPCR methods than river water, perhaps due to specific physiochemical characteristics of the water. These findings also show that season and sample volume affect the agreement of qPCR and culture results. Overall, qPCR methods could be more confidently utilized to determine the absence ofSalmonella entericaandListeria monocytogenesin irrigation water samples examined in this study. 

Abstract Tobacco use significantly influences the oral microbiome. However, less is known about how different tobacco products specifically impact the oral microbiome over time. To address this knowledge gap, we characterized the oral microbiome of cigarette users, smokeless tobacco users, and non-users over 4 months (four time points). Buccal swab and saliva samples (n = 611) were collected from 85 participants. DNA was extracted from all samples and sequencing was carried out on an Illumina MiSeq, targeting the V3–V4 region of the 16S rRNA gene. Cigarette and smokeless tobacco users had more diverse oral bacterial communities, including a higher relative abundance ofFirmicutesand a lower relative abundance ofProteobacteria, when compared to non-users. Non-users had a higher relative abundance ofActinomyces, Granulicatella, Haemophilus, Neisseria, Oribacterium, Prevotella, Pseudomonas, Rothia, andVeillonellain buccal swab samples, compared to tobacco users. While the most abundant bacterial genera were relatively constant over time, some species demonstrated significant shifts in relative abundance between the first and last time points. In addition, some opportunistic pathogens were detected among tobacco users includingNeisseria subflava, Bulleidia mooreiandPorphyromonas endodontalis. Overall, our results provide a more holistic understanding of the structure of oral bacterial communities in tobacco users compared to non-users. 

Abstract The reproductive success of birds is closely tied to the characteristics of their nests. It is crucial to understand the distribution of nest traits across phylogenetic and geographic dimensions to gain insight into bird evolution and adaptation. Despite the extensive historical documentation on breeding behavior, a structured dataset describing bird nest characteristics has been lacking. To address this gap, we have compiled a comprehensive dataset that characterizes three ecologically and evolutionarily significant nest traits—site, structure, and attachment—for 9,248 bird species, representing all 36 orders and 241 out of the 244 families. By defining seven sites, seven structures, and four attachment types, we have systematically classified the nests of each species using information from text descriptions, photos, and videos sourced from online databases and literature. This nest traits dataset serves as a valuable addition to the existing body of morphological and ecological trait data for bird species, providing a useful resource for a wide range of avian macroecological and macroevolutionary research. 

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.