Environmental Science & Technology Letters

Wastewater-based epidemiology (WBE) has the potential to fill gaps in clinical surveillance for respiratory syncytial virus (RSV) burden. Previous studies have shown RSV to be detectable in wastewater, but few have linked detections to clinical data because, in many locations, RSV is not a reportable disease. Further, studies that have linked RSV in wastewater to clinical data have not distinguished between pediatric and adult infections, as is common in studies of RSV. Using 2,662 influent wastewater samples collected from twenty-four treatment plants in four New York counties, we measured the RSV concentration in wastewater and compared levels detected to RSV hospitalizations from September 2022 to July 2024. RSV concentrations in wastewater correlated well with RSV hospitalizations ({rho} between 0.52 and 0.85, P <0.001). RSV concentrations in wastewater lagged hospitalizations for under 10-year-olds by an average of three weeks but were a leading indicator for hospitalizations in patients over 50 by up to two weeks. In predictive models, wastewater explained 88 percent of the variance in RSV hospital admissions among people over 50. Wastewater-based epidemiology of RSV is therefore a reliable surveillance method and could provide early warning for increases in RSV hospitalizations among older populations.

Wastewater genomic surveillance provides an opportunity to detect human and animal influenza A virus (IAV). We aimed to implement an IAV genomic surveillance framework agnostic to subtype, which enables recovery of IAV from multiple hosts and estimation of proportions across subtypes. We conducted IAV genomic surveillance in wastewater during the 2024-2025 flu season at multiple sites in California and compared these data with available human clinical IAV sequences and test positivity. We applied a custom whole-genome, multi-host IAV probe enrichment panel and adapted our custom expectation-maximization (EM) algorithm to deconvolute IAV mixtures in wastewater and infer subtype relative abundances. Absolute IAV concentrations were quantified using RT-PCR-based assays. H5N1 wastewater and clinical sequences were further characterized by constructing a whole-genome maximum-likelihood phylogenetic tree. Finally, we performed variant analysis to examine amino acid substitutions detected in wastewater. Our IAV probe enrichment method and EM algorithm successfully enriched all eight segments of three circulating IAV subtypes and accurately estimated subclade relative abundances for mixed IAV samples. Seasonal human H1N1pdm09 and H3N2 were detected throughout the study period from both wastewater and clinical sequencing data, with H1N1 subclades 6B.1A.5a.2a.1 and 6B.1A.5a.2a co-circulating, and H3N2 dominated by subclade 3C.2a1b.2a.2a.3a.1. Wastewater surveillance consistently detected H5N1 clade 2.3.4.4b across three monitored wastewater sites, while clinical H5N1 detections, from anywhere in CA, were sporadic and rare. Whole-genome phylogenetic analysis revealed that wastewater H5N1 sequences clustered with reference sequences associated with dairy cow and avian infections, while all human clinical H5N1 sequences clustered exclusively with reference sequences associated with dairy cow infections. Amino acid substitutions were identified across viral segments, and no mutations associated with mammalian adaptation were observed from wastewater samples.

While exposure to volatile organic compounds such as ethylene dichloride and vinyl chloride monomer is a well-established cause of liver disease, particularly hepatic hemangiosarcoma, characterizing real-world exposure profiles in communities surrounding industrial centers remains challenging. Calvert City, Kentucky (population ~2,500), provides a unique setting characterized by both active industrial emissions and legacy sources of air toxics. To address these complexities, this method paper describes the framework for the Biomonitoring and Environmental Assessment for Community Outreach and Neighborhood Safety (BEACON) study. By utilizing a novel, multi-dimensional exposure assessment strategy, BEACON aims to characterize air toxic exposures and provide actionable data for community health and safety. For the BEACON study, we will leverage Kentucky Department of Air Quality measures of air toxics, analyze urine samples in a small cohort of community volunteers, analyze community urine via wastewater in an adjacent community, geocode citizen odor reporting, assess blood markers in wildlife, survey small and large animal veterinarians in the area for anomalies in morbidity and mortality, and work with the regional health system to enhance vigilance for health issues associated with toxicants present in the area. In addition, blood samples will be collected at three time points and biobanked for future analyses. Efforts will be made to link this study to additional large-scale long-term cohorts where possible. Throughout the project, community engagement will play a critical role by raising awareness, fostering collaboration, and ensuring that the voices of affected residents are heard.

Wastewater surveillance (WS) has been widely adopted as a cost-effective and population-representative infectious disease monitoring tool and is increasingly being applied to bacterial and antimicrobial resistance gene (ARG) targets. However, some of these targets may persist in pipe biofilms and detach into wastewater, complicating accurate WS interpretation. To investigate biofilm contributions to wastewater pathogen and ARG signals, paired sink-drain biofilm, branch-drain-plumbing biofilm (sewer biofilm), and wastewater were collected from five hospital sites over a four-month period and analyzed using 16S rRNA gene amplicon sequencing and probe-capture metagenomics. Overall, sewer biofilm bacterial communities were as diverse as wastewater. Across sites, a mean of 9% (0.9 to 23.3%) of wastewater bacterial communities could be attributed to sewer biofilm communities. Many clinically relevant pathogens were consistently detected both in sewer biofilm and wastewater, including environmentally persistent and/or biofilm-associated taxa (e.g., Pseudomonas aeruginosa, Klebsiella pneumoniae). While many ARGs overlapped between wastewater and biofilms (e.g., tetA, sul1, blaCTX-M, vanA), others were significantly enriched in sewer biofilms (e.g., qacL, van-operon and OXA genes). Together, these findings confirm that wastewater pathogen and resistome profiles integrate inputs from both human shedding and pipe-resident communities and therefore need to be considered when selecting WS targets and interpreting signal.

Germicidal UV devices offer a promising solution to mitigate surface-mediated pathogen transmission, providing effective disinfection without material corrosion. This study evaluated the surface inactivation kinetics of two bacteria and two bacteriophages using a low-pressure (LP) mercury UV lamp (254 nm) and a filtered krypton chloride (KrCl*) excimer lamp (222 nm). Three deposition methods (Spray, Spread, and Pipette) and two extraction methods (Swab and Elute) were compared. The UV dose response on surfaces followed a two-region non-linear model due to shielding from dried deposition constituents, primarily through UV absorption. KrCl* excimer exhibited similar bacterial inactivation but slightly lower viral inactivation than LP UV lamp (maximum inactivation [~] 1 log lower), but its safety profile makes it compelling in occupied spaces. Compared to aqueous conditions, bacteria were more UV sensitive on surfaces, whereas viruses were more resistant. The deposition methods affected the inactivation results, with the Spray method resulting in higher bacteria inactivation. While the extraction methods had limited effect on inactivation efficacy, the Swab method provided higher inactivation detection limits ([~] 2 log higher) and more consistent extraction efficiency. This study provides mechanistic insights into the effects of deposition conditions, UV wavelengths, and microbial characteristics on UV surface disinfection and contributes to standardization of testing methods. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/734141v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@11db511org.highwire.dtl.DTLVardef@15aa3faorg.highwire.dtl.DTLVardef@1c39ac9org.highwire.dtl.DTLVardef@e726ed_HPS_FORMAT_FIGEXP M_FIG C_FIG

Wildfire smoke has increasingly affected air quality across North America, raising concerns about the health effects of fine particulate matter (PM2.5) exposure, including potential impacts on brain health. However, relatively few studies have characterized personal PM2.5 exposure during these events using wearable monitoring. We examined daily personal PM2.5 concentrations during wildfire smoke episodes in southeast Michigan alongside neighborhood outdoor PM2.5 estimates. Four participants (one adolescent and three adults) wore AirBeam3 personal monitors during ongoing studies. Neighborhood outdoor PM2.5 was estimated using the average of three nearest PurpleAir outdoor air quality sensors, and wildfire smoke days were identified using state air quality advisories. Group-level descriptive statistics summarized personal and neighborhood outdoor PM2.5 and self-reported time spent outdoors. Exploratory within-participant analyses quantified associations between neighborhood outdoor and personal PM2.5 concentrations on smoke and non-smoke days. Neighborhood outdoor daily PM2.5 concentrations were higher during wildfire smoke days than non-smoke days (87.6 + 80.2 vs. 12.3 + 7.0 {micro}g/m3). Personal PM2.5 concentrations were more than five times higher during wildfire smoke days (28.2 + 20.0 vs. 5.1 + 4.7 {micro}g/m3) than non-smoke days. Within participants, every 10 {micro}g/m3 increase in neighborhood PM2.5 was associated with 2.3 {micro}g/m3 increase in personal PM2.5 concentrations. Wearable PM2.5 monitoring captured elevated personal exposures while providing individual-level exposure information beyond neighborhood outdoor air quality estimates. These findings demonstrate that wearable monitoring complements neighborhood air quality measurements by capturing individual-level exposure, providing a more comprehensive assessment of real-world wildfire smoke exposure for future studies examining the effects on brain health.

This study aimed to clarify aerosol exposure risks throughout the workflow of a Biosafety Level 2 (BSL-2) polymerase chain reaction (PCR) laboratory, validate the suitability of the {Phi}X174 bacteriophage as an indicator virus, and provide evidence for biosafety control measures. The {Phi}X174 bacteriophage was used to simulate viral samples, and a concentration-bacteriophage plaque standard curve was constructed (R2=0.998). Five operational steps in a simulated PCR laboratory were quantitatively monitored for aerosol concentration using double-layer agar plates, with blank controls used to eliminate interference. Statistical analysis was employed to identify risk differences. Sample homogenization ((5.67 {+/-} 1.23) x 104 plaque-forming units (PFU)/m3) and nucleic acid extraction ((3.45 {+/-} 0.89) x 104 PFU/m3) were identified as high-/very high-risk steps. The viral load in the samples was strongly positively correlated with the aerosol concentration (r = 0.926, P <0.001), with aerosol levels linearly decreasing with increasing distance in high-risk steps. The {Phi}X174 bacteriophage demonstrated high detection sensitivity (101 PFU/ml) and demonstrated safety compatibility with BSL-2 laboratories. Aerosol risks in PCR laboratories exhibit step-specific differentiation, and {Phi}X174 serves as an ideal indicator virus. Proposed strategies such as equipment upgrades and personal protective equipment (PPE) grading can reduce exposure risks.

Hospital-based wastewater surveillance may complement community and clinical surveillance data in important ways, and may be useful in jurisdictions without community-based wastewater surveillance. From May 2024-April 2026, we analyzed weekly samples (n=190) from three hospitals in New York City using digital PCR to evaluate the sensitivity, specificity, and positive predictive value (PPV) of wastewater viral detection against facility SARS-CoV-2 and influenza A/B inpatient caseloads. Sensitivity was 38-42% for SARS-CoV-2 and 36-49% for influenza A/B, while specificity exceeded 72% for all pathogens. During respiratory seasons, sensitivity reached 81% for SARS-CoV-2 and 81% for influenza A; both had 100% sensitivity during peak case weeks. Notably, off-peak influenza detections occurred in hospital wastewater at all three hospitals in summer 2024 without corresponding hospital case detection, suggesting the presence of undiagnosed cases. These findings underscore the potential utility of hospital-based wastewater monitoring for tracking respiratory virus activity.

The 2020 SARS-CoV-2 pandemic renewed global interest in wastewater-based epidemiology (WBE) as a tool for monitoring public health. Molecular analyses of wastewater are often limited by the small volumes of wastewater that can be processed, due to column clogging, handling constraints, and processing time. Additionally, inhibitors in the complex wastewater matrix reduce the sensitivity of downstream assays such as RT-PCR and sequencing. To address these limitations, we developed a novel column by incorporating a hydrophobic pre-filtration layer and sequential glass fiber filters. This enhanced column design, PureBioX Xpurify Column, enables processing of 1.58 times more wastewater (a 58% increase in throughput) while reducing RT-PCR inhibitors and maintaining compatibility with existing workflows. Despite a modest reduction in nucleic acid yield, the modified column consistently improved viral RNA detection sensitivity, including for SARS-CoV-2. This accessible, scalable upgrade strengthens the utility of direct capture methods in WBE-based public health surveillance.

Disagreement between molecular and culture-based assays for Legionella pneumophila detection is widely reported, yet comparisons have largely been based on direct assay-derived concentrations or binary positive/negative outcomes. However, it remains unclear whether molecular-culture disagreement reflects concentration-level incompatibility or unaccounted methodological and physiological differences related to DNA recovery and cell culturability. In this study, we observed substantial disagreement between molecular and Legiolert assays in source and finished drinking water samples collected from eight full-scale drinking water systems across the United States. Molecular thresholds adjusted for DNA recovery and cell culturability only partially resolved these discrepancies. We therefore developed a probabilistic Monte Carlo framework that incorporates sample-specific DNA recovery and cell culturability to evaluate the quantitative consistency of culturable L. pneumophila concentrations estimated by molecular and Legiolert assays. Quantitatively consistent and inconsistent samples occurred across both binary concordant and discordant classifications, demonstrating that positive/negative agreement poorly reflects concentration-level comparability. Overall, molecular and Legiolert assays showed strong quantitative consistency once sample-specific DNA recovery and cell culturability were considered. A small proportion of persistent inconsistencies at specific sampling sites, coupled with atypical microbial indicators, suggest that sample heterogeneity likely contributed to the remaining discrepancies. These findings demonstrate that integrating DNA recovery and cell culturability enhanced quantitative consistency between molecular and Legiolert assays and supports the use of molecular methods as rapid quantitative tools to complement culture-based L. pneumophila monitoring.

Background Wildfire activity and smoke exposure are increasing worldwide because of climate and land-use change. Although fine particulate matter (PM2.5) may impair pulmonary immune defences against tuberculosis (TB), population-level evidence remains limited. We estimated the effect of wildfire-related PM2.5 exposure on TB notification rates in Brazil. Methods We conducted a nationwide panel study linking municipality-level monthly TB notifications from Brazil's SINAN system with wildfire-related PM2.5 estimates from GEOS-Chem simulations across 5,545 municipalities (2003-2023). We estimated the impact of high-exposure days (PM2.5 > 25 g/m3) on monthly TB notifications using Poisson regression with fixed effects for municipalities, state-by-year, and state-by-month, controlling for time-invariant differences, secular trends, and seasonality. Distributed lag effects were estimated over 1-24 months before notification. Models accounted for meteorological conditions, GeneXpert diagnostic coverage, and spatial correlation using Conley standard errors. We computed attributable fractions among exposed municipality-months (AFE). Sensitivity analyses evaluated alternative PM2.5 thresholds (15 and 35 g/m3), co-pollutants, and agricultural expansion. Findings From Jan 1, 2003 to Dec 1, 2023, 1,758,982 TB cases were reported. Of these, 353,319 (20.1%) had at least one high-exposure day (PM2.5 > 25 g/m3) 1-24 months before notification. An additional 14 high-exposure days over the 24-month lag period was associated with an average monthly increase of 2.9% [95% CI: 0.9-4.9%] in TB notification rates. Effects peaked at 13 months (IQR: 11-14) prior to notification. Results showed a dose-response relationship across PM2.5 thresholds and were robust to controlling for NO2, O3, and agricultural expansion. Overall, wildfire-related PM2.5 exposure accounted for 2.1% [0.7-3.5%] of TB notifications in exposed municipality-months, corresponding to 7,802 [2,612-12,544] attributable cases. The AFE reached 10.7% [7.1-14.0%] in Pantanal and 7.3% [6.1-8.5%] in Amazonia, areas most impacted by wildfires. Interpretation Wildfire-related PM2.5 exposure may represent an increasingly important and modifiable risk factor for TB. As wildfire activity increases across many regions of the world, these findings highlight the need for integrating air quality into climate adaptation and TB control strategies.

Background: Children spend more than 90% of their time indoors, and early childhood education settings (ECEs) are an understudied, high-occupant-density indoor microenvironment where exposure to volatile organic compounds, particulate matter, and other toxicants has been documented. Limited knowledge exists on ECE-specific exposures affecting young children and how they compare to exposures in the home. Methods: This prospective, repeated-measures pilot study targeted enrollment of 44 preschool-aged children and 8 ECE staff across two geographically and sociodemographically distinct ECEs in metropolitan Atlanta, Georgia. Paired silicone wristbands, one home-designated and one ECE-designated, were exchanged between settings across three consecutive days and nights beginning at enrollment to characterize microenvironment-specific exposure. A single spot urine sample was also collected from each child. Continuous indoor air quality monitoring was conducted in two classrooms per site. Caregivers and ECE staff completed structured questionnaires assessing home and ECE environmental characteristics, child respiratory risk, and protocol feasibility and acceptability. Feasibility was evaluated using eight pre-specified indicators spanning recruitment and enrollment, wristband wear duration and loss by microenvironment, urine sample collection completeness, and survey completion by instrument and respondent group. Conclusion: This pilot will establish feasibility and acceptability parameters for a paired, multi-matrix silicone wristband protocol across home and ECE microenvironments. Findings will inform the design, sample size, and power calculations for a subsequent study testing indoor air interventions and pediatric respiratory outcomes in ECEs. Feasibility outcomes are reported in a companion manuscript.

Plastic products have greatly improved convenience in daily life. However, diverse pollutants released from these materials pose substantial risks to human health. Lactiplantibacillus plantarum PD01 has previously been demonstrated to reduce microplastic (MP) bioaccumulation and toxicity in murine model. In this study, we conducted a randomized, double-blind, placebo-controlled trial to further evaluate the efficacy of L. plantarum PD01 in reducing MPs and MP-associated chemicals in humans. A total of 106 participants were recruited in November 2025. Eligible participants were randomly assigned to either the placebo or intervention group, and orally received placebo or 1.0x1010 colony-forming units (CFU) L. plantarum PD01 after meals three times a day, respectively. Fecal, urinary, and blood samples were collected to determine the MPs contents, plasticizer levels, gut microbiota composition, blood metabolic profiles and biochemical indicators. Among these measurements, the analysis of urinary phthalate metabolites was completed first and revealed a significant reduction after the probiotic intervention. Compared with the placebo group, 6-week L. plantarum PD01 supplementation resulted in significant relative reductions in urinary levels of MCMHP by 60.2% (P = 0.0343), MMP by 51.2% (P < 0.001), MEHP by 49.6% (P = 0.0058), MiBP by 45.7% (P = 0.0085), MnBP by 35.8% (P = 0.0478), and {Sigma}DEHP by 46.2% (P = 0.0461). The interim results presented here provide the first clinical evidence that the probiotic strain PD01 can significantly reduce residual MP-associated chemicals in human body. To the best of our knowledge, this is the first randomized controlled trial (RCT) to evaluate probiotic intervention targeting MPs and MP-associated chemicals in humans.

Wastewater metagenomic sequencing (WW-MGS) enables simultaneous detection of hundreds of pathogens, but its use for quantitative pathogen tracking has not been robustly validated. Like wastewater PCR (WW-PCR), WW-MGS is affected by biases from variable fecal dilution and sample processing, but must additionally contend with the compositional structure of sequencing data, where a taxon's apparent abundance depends on the abundance of every other taxon in the sample. Simple summaries such as a pathogen's fraction of total reads may therefore be poorly suited to quantitative use. We retrospectively evaluated seven normalization approaches that attempt to control for these sources of bias against a baseline of total read relative abundance, using 1,425 samples from the CASPER consortium spanning 25 U.S. sites. Each approach was compared against WW-PCR and clinical data across eight total pathogens. Among the normalization strategies we evaluated, tobamovirus markers, diet-derived plant viruses abundant in human stool, performed best. Normalizing WW-MGS data by tobamovirus-genus counts improved median site concordance for 18 of 19 pathogen and comparison-source combinations. Gains were largest for year-round-circulating SARS-CoV-2 and norovirus and smaller for sharply seasonal pathogens such as influenza and respiratory syncytial virus, where baseline concordance was already high. Tobamovirus normalization rarely degraded concordance, with median gains roughly five times larger than median losses. Tobamovirus-normalized WW-MGS reached clinical concordance comparable to targeted WW-PCR, supporting its use as a quantitative trend-monitoring tool alongside pathogen-agnostic detection.

The Arctic is warming rapidly, causing permafrost thaw and accelerating the release of greenhouse gases. Rapid thaw features such as retrogressive thaw slumps are increasing in frequency and severity across the Arctic; however, their associated greenhouse gas emissions are poorly constrained. Current estimates of emissions from retrogressive thaw slumps rely largely on laboratory incubations and carbon stock estimates rather than in-situ field measurements. Here we directly quantify methane and carbon dioxide fluxes from the exposed headwall of an active retrogressive thaw slump. We show that thaw immediately releases biogenic methane and carbon dioxide, originating from gases trapped within the frozen soil matrix. Microbial transcription of methyl-coenzyme M reductase suggests archaea carrying out methanogenesis at subzero temperatures are the source of trapped methane. Carbon emissions varied by an order of magnitude among cryostratigraphic units, reflecting differences in geomorphologic history, organic carbon and nitrogen content, and microbial community composition. Carbon emissions were highest from organic-rich paleo cryosols from the Late Holocene that contained abundant methanogenic archaea. We estimate that [~]300 kg C (CO2 equivalents) is emitted annually from the headwall of this small thaw slump (surface area of [~]1200 m2). Considering the thousands of active slumps and extensive coastal permafrost erosion across the northern continuous permafrost zone, such features may represent a growing natural source of GHG emissions. These findings indicate that current permafrost carbon feedback models underestimate GHG release by omitting the direct release of trapped gases stored in permafrost.

Disinfection with bleach is recommended for surface cleaning in healthcare facilities, but bleach degrades over time, reducing disinfection effectiveness. We evaluated whether local bleach produced by hospitals using novel technology had adequate shelf life to justify use. Two hospitals (A and B) each produced and stored 0.5% bleach in two 20-liter plastic containers; bleach in one container was alkalinized for increased stability to pH 12; bleach in the other container was not stabilized and, for comparison, a third container of commercial bleach was tested. We tested three bleach samples from each of the containers produced by hospitals A and B, and commercial bleach for free available chlorine (FAC) using N,N-diethyl-p-phenylenediamine at irregular intervals up to 216 days. We compared the expected percent decrease in FAC per 7 days by bleach type using log-normal regression. Stabilized bleach decreased by 1% and 2% in hospitals A and B, respectively, every 7 days while non-stabilized bleach decreased by 21% and 12%, respectively (all p<0.001); commercial bleach decreased by <1% per 7 days. Bleach production proved feasible in hospitals, and both stabilized and commercial bleach maintained adequate concentration for disinfection; non-stabilized bleach maintains a useful concentration for not longer than three weeks after production.

Since the COVID-19 pandemic, wastewater-based surveillance (WBS) has emerged as a key approach to assess community-level health and the evolution of pathogens. To date, most established WBS systems focus on polymerase chain reaction (PCR) based detection and targeted sequencing of known pathogens because these approaches are well-accepted and include amplification of pathogen target sequences of interest thereby enabling lower limits of detection. Metagenomic next-generation sequencing (mNGS) is a promising approach to enable pathogen detection and surveillance beyond predefined pathogen lists, but its regular application to WBS has not been yet widely adopted because many key performance characteristics are not well-understood, including limit of detection (LOD) and false positive/negative rates. This paper describes a computational analysis to estimate the operational LOD of various sequencing approaches using a simplified model of a local wastewater (WW) system involving a military base. This paper also presents findings from two types of experiments: 1) laboratory-spiked, those for which Atlantibacter subterraneus (Asub) is introduced into real-world WW samples in a laboratory setting, and 2) system-spiked, those for which Asub is introduced at a source location of a real-world WW system. Findings indicate that mNGS detection performance varies with sequencing method and the data analysis process. In addition, findings indicate that site-specific method characterization should be used when implementing mNGS for WBS because sites can have different WW system configurations, background organisms and sequencing inhibitors.

Background: Environmental noise and air pollution are both shaped by road traffic and the built environment, and exposure assessment increasingly folds them into composite indices or proxies both by traffic exposure. Whether the two share a social distribution has rarely been tested against direct measurement of several exposures in the same communities, and community noise is almost always characterized by A-weighted levels alone, which discount low-frequency energy. Methods: At 176 sites across Rhode Island, spanning the contiguous urban area of Providence, Central Falls, and Pawtucket together with four rural municipalities, we measured the acoustic environment under A- and C-weighting (LAeq, LCeq), fine particulate matter (PM2.5), night-time illuminance, and relative humidity across four session types over roughly one year (704 site-sessions). Exposures were linked to census-tract composition (American Community Survey), and mixed-effects models were fitted for each of eight area-level markers of disadvantage, adjusting for campaign and session. Relative humidity was carried through the identical model as a negative control. Results: A-weighted noise was consistently higher in more disadvantaged tracts, rising with non-White, poverty, renter, and no-vehicle shares and falling with income and older-resident share (six of eight markers significant; 1.3 to 1.8 dBA per standard deviation; 6.6 dBA between the least and most racially diverse neighborhoods). C-weighted levels followed the same gradient on every marker and exceeded their A-weighted counterparts at block-group scale for renter occupancy and vehicle absence. Night-time illuminance was also socially patterned, whereas short-term PM2.5 was roughly an order of magnitude weaker and relative humidity showed no gradient. The acoustic gradient persisted within the urban core alone. Conclusions: Measured burden was carried by the acoustic environment, including its low-frequency component, and by night-time light, not by short-term particulates. The exposure metric and the averaging time determine which disparities are visible at all.

Background: Autonomous ultraviolet-C (UV-C) disinfection systems are increasingly used to supplement manual environmental cleaning, yet evidence-based guidance defining pathogen-specific UV-C dose requirements across representative surfaces remains limited. Aim: To characterize operational UV-C dose requirements for clinically relevant pathogens across diverse high-touch and healthcare surfaces and determine how experimentally derived microbial inactivation can inform operational exposure parameters. Methods: SARS-CoV-2, adenovirus, Pseudomonas aeruginosa, Staphylococcus aureus, Klebsiella pneumoniae, Enterococcus faecalis, Candida auris, and Clostridioides difficile spores were exposed to defined UV-C doses on representative high-touch materials or stainless steel under standardized conditions, including a 10% fetal bovine serum organic soil challenge. Microbial inactivation was quantified by viable recovery. Dose-response analysis and operational modelling were used where supported by the experimental data. Findings: UV-C exposure significantly reduced viable recovery of all pathogens, with substantial differences in the exposure conditions associated with microbial inactivation. SARS-CoV-2 exhibited substantial inactivation at doses as low as 2.6 mJ/cm2, whereas the highest evaluated doses were 1,800 mJ/cm2 for C. difficile spores and 3600 mJ/cm2 for C. auris. For C. auris, multi-dose data estimated that approximately 1,410 mJ/cm2 was associated with a 2-log10 reference reduction, enabling distance-dependent exposure-time predictions. Conclusion: Experimentally quantified UV-C exposures produced substantial microbial inactivation across diverse pathogen classes and surfaces. Integrating delivered dose with microbial reduction provides a quantitative framework for translating laboratory efficacy into operational parameters for autonomous UV-C disinfection.

Mass gatherings pose significant public health risks by facilitating the spread of infectious diseases. While wastewater-based surveillance (WBS) has been widely used to monitor pathogens in high-income settings, its use as a practical, multi-pathogen surveillance tool during mass gatherings in low- and middle-income countries remains limited. This study aimed to assess the operational feasibility, epidemiological significance, and public health utility of multi-pathogen WBS during the African Nations Championship (CHAN) football tournament in Uganda. Wastewater surveillance was conducted at Mandela National Stadium during eight match days in August 2025. Moore swabs were deployed at 38 manholes receiving wastewater from different toilet facilities across the stadium to capture representative wastewater samples. Samples were processed using Nanotrap(R) microbiome virus particles to concentrate pathogens, followed by nucleic acid extraction. Samples were analyzed for multiple enteric and respiratory pathogens, including Mpox, using quantitative PCR (qPCR). Descriptive analyses were performed to characterize pathogen detection patterns, positivity rates, and temporal distribution across surveillance sites. A total of 304 wastewater samples were collected and analyzed, of which 259 (85.2%) tested positive for at least one pathogen. Multiple pathogens were consistently detected across sampling days, with enteric pathogens predominating, particularly Shigella spp. (53.6%), Rotavirus A (35.9%) and Enterovirus (32.2%). The mpox virus was also detected in a notable proportion of samples (28.6%) across several sampling days. Respiratory pathogens, including SARS-CoV-2 (11.8%) and Influenza B (8.2%), were identified intermittently at lower frequencies. Pathogen diversity varied over time, with up to eight pathogens detected on a single day, and co-detection of multiple pathogens observed in the majority of positive samples. Cq value distributions further demonstrated variability in detected signal patterns across pathogens. Surveillance findings informed real-time public health interventions, including sanitation reinforcement, intensified hygiene promotion, environmental disinfection, and targeted risk communication, strengthened syndromic surveillance with on-site triage, and targeted environmental health assessments of food handling and wastewater infrastructure. These findings demonstrate the operational feasibility and public health utility of integrating multi-pathogen wastewater-based surveillance into mass-gathering preparedness and response frameworks in low-resource settings. By capturing diverse pathogen signals and informing targeted interventions during the CHAN football tournament, WBS can provide actionable population-level insights that can support outbreak preparedness and response. Scaling WBS within national preparedness systems could strengthen epidemic intelligence, enhance early warning capacity, and support data-driven public health decision-making during future mass gatherings and emerging infectious disease threats.