Environmental Science & Technology Letters

Methods to concentrate wastewater samples are essential for sensitive environmental surveillance of infectious diseases. We defined six main principles used to concentrate viral pathogens in wastewater and performed a systematic review and meta-analysis of their performance. PubMed and Web of Science were searched on 31 January 2025 using terms wastewater, sewage, concentration methods and wastewater surveillance. We included all studies comparing [≥]2 concentration methods for virus detection. Our search identified 49 eligible studies published since 2013 across seven continents. We ranked the performance of evaluated methods in each study and generated an overall performance metric for each method principle by virus group (enveloped vs. non-enveloped) using Plackett-Luce analysis. Precipitation and filtration methods were the most studied, while magnetic bead-based and centrifugation were least studied. Magnetic bead-based methods were more effective for concentrating enveloped viruses (63% of pairwise comparisons), whereas flocculation performed better for non-enveloped viruses (60%). However, no single method strongly dominated and method rankings were variable between studies. This study provides evidence-based guidance for selecting wastewater concentration methods to support environmental surveillance of viral pathogens.

BackgroundContinuous, non-invasive viral surveillance is essential to monitor emerging pathogens and guide public health responses. Most environmental surveillance studies use targeted qPCR approaches, and comparisons between wastewater and indoor air surveillance remain limited. We aimed to compare the utility of emergency department indoor air and urban wastewater for tracking circulating viruses and resolving genomic information. MethodsWe conducted a matched-pair study comparing 19 weekly indoor air samples from the central ventilation exhaust shaft of an emergency department and 19 24-hour composite municipal wastewater samples in Leuven, Belgium, from December 2024 to April 2025. Both sample sets were processed using probe-based hybrid-capture viral metagenomics targeting over 3000 viral species, using influenza A as a clinically relevant test case. FindingsWastewater captured higher overall viral diversity (233 versus 106 species) and more complete genomes compared to indoor air, showing a relatively stable composition, mainly of enteric and animal-associated viruses. Indoor air demonstrated lower overall diversity but was enriched for respiratory viruses, including influenza A, coronaviruses, metapneumovirus, and respiratory syncytial virus, and more frequently achieved high genome coverage for these pathogens. Although both sample types permitted influenza A subtype characterization, influenza A genomes from wastewater were often less well covered. When coverage thresholds were met, indoor air supported targeted antiviral resistance-site screening for influenza A and RSV-A. InterpretationWastewater and indoor air generate distinct but complementary viromes. Wastewater acts as a diverse, population-level monitor for One-Health applications, whereas indoor air serves as a targeted, human-centric sentinel system facilitating further genomic characterization for respiratory viruses. FundingMustafa Karatas is supported by a Research Foundation Flanders (FWO) fundamental research scholarship (number: 11P7I24N). C.G., L.C., E.H., S.G. and E.A. acknowledge support from the DURABLE project. The DURABLE project has been co-funded by the European Union, under the EU4Health Programme (EU4H), project no. 101102733. Research in context Evidence before this studyWe searched PubMed for studies published between Jan 2000 and March 2024 using the terms "wastewater surveillance", "metagenomics", "indoor air", and "viral metagenomics". Previous studies have shown that wastewater surveillance can detect population-level viral circulation, and more recent work has explored indoor air sampling as a method for monitoring respiratory virus transmission. However, environmental metagenomic studies have largely examined these two sample types separately. Furthermore, most studies relied on untargeted sequencing approaches, which often yield fragmented genomes in these environments. To date, no study has systematically compared indoor air and wastewater using a comprehensive hybrid-capture viral metagenomics approach for virus surveillance. Added value of this studyWe conducted a matched comparison of indoor air from a hospital emergency department and municipal wastewater collected during the same weeks in Leuven, Belgium. We analyzed both sample types using an identical hybrid-capture viral metagenomics workflow targeting more than 3000 viral species. This design enabled a direct evaluation of how the two environmental surveillance lenses differ in viral diversity, genomic recovery, and epidemiological relevance. Wastewater captured broader viral diversity and a stable background dominated by enteric and animal-associated viruses, whereas indoor air captured more respiratory viruses and more frequently yielded high genome completeness for these pathogens. When genome coverage thresholds were met, indoor air data enabled influenza subtype identification and screening for antiviral resistance markers. Implications of all the available evidenceOur findings support a layered environmental surveillance strategy in which different environmental samples provide complementary information. Wastewater offers a stable, population-level view of viral circulation and captures broad viral diversity, including human and animal-associated viruses. Indoor air sampling in human-dominated settings provides a more direct signal of respiratory virus circulation and can yield genomes suitable for subtype and mutation-level characterization. Combining these approaches could strengthen metagenomic surveillance frameworks by improving the interpretation of environmental viral signals, supporting early detection of emerging pathogens, and helping distinguish human virus circulation from environmental or animal-derived detections.

Wastewater monitoring enables non-invasive, population-scale tracking of community infections independent of healthcare-seeking behavior and clinical diagnosis. Metagenomic sequencing extends this capability by enabling broad, pathogen-agnostic detection, genomic characterization, and identification of novel or unexpected threats. Here, we present data from CASPER (the Coalition for Agnostic Sequencing of Pathogens from Environmental Reservoirs), a U.S.-based wastewater metagenomic sequencing network designed for deep, untargeted pathogen monitoring at national scale. This release includes 1,206 samples collected between December 2023 and December 2025 from 27 sites across nine states, covering 13 million people. Deep sequencing ([~]1 billion read pairs per sample) generated 1.2 trillion read pairs (357 terabases), enabling detection of even rare taxa, with CASPER representing 67% of all untargeted wastewater sequencing data currently available on the NCBI Sequence Read Archive. Virus abundance trends correlate with nationwide wastewater PCR and clinical data for SARS-CoV-2, influenza A, and respiratory syncytial virus, while the pathogen-agnostic approach captures emerging threats, including avian influenza H5N1 during initial dairy cattle outbreaks, West Nile virus, and measles, among hundreds of viral taxa. As the largest publicly available untargeted wastewater sequencing dataset to date, CASPER provides a shared and growing resource for pathogen surveillance and microbial ecology.

Respiratory infections caused by bacterial pathogens like Mycobacterium tuberculosis and Bordetella pertussis have increased since the COVID 19 pandemic, yet clinical surveillance of both suffers from underreporting and delayed diagnoses. Wastewater monitoring is a valuable public health surveillance tool that can help fill gaps in clinical data yet has rarely been applied to respiratory bacterial pathogens despite evidence of bacterial shedding via excretion types that enter wastewater. In this study, we investigated the possibility for wastewater monitoring of two bacterial respiratory diseases, tuberculosis and pertussis, using two case studies of wastewater monitoring for M. tuberculosis and B. pertussis. We retrospectively measured concentrations of these pathogens in wastewater samples collected longitudinally from communities with and without known outbreaks of these diseases. We designed and validated a novel B. pertussis specific assay for the NAD(P) gene; B. pertussis nucleic acids were detected sporadically in wastewater during an identified outbreak. We used a highly specific, established assay for M. tuberculosis nucleic acids, and found low concentrations of the marker in wastewater that were lag-correlated with clinical incidence rates 5 weeks later. Findings support the potential of wastewater monitoring for M. tuberculosis and B. pertussis to enable identification of communities with outbreaks of tuberculosis and pertussis and provide early warning for tuberculosis.

Hospital-acquired infections driven by ESKAPEE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) are highly prevalent. Premise plumbing, sinks and drains, seeds these organisms into patient environments via aerosolization and subsequent surface contamination. We measured viable ESKAPEE pathogens and overall microbial communities in and around sinks in two high-burden hospitals in La Paz, Bolivia, using culture and 16S rDNA sequencing. In a prospective observational study (May-August 2025), we collected 233 surface swabs and 39 air samples across four sink-related surface categories and in room air. Samples were plated on selective media for ESKAPEE identification and quantified as colony-forming units (CFU) normalized to 100 cm2 or 6000 L. DNA was extracted, and the full 16S rDNA gene was sequenced on PacBio Revio, analyzed via DADA2/QIIME2 and R. We detected viable presumptive ESKAPEE pathogens in 74.7% surface swabs and 74.4% air samples. Sink basins were most contaminated (mean 31CFU/100 cm2, 95 % CI16-46); concentrations declined with distance from the drain. Klebsiella/Enterobacter spp. showed the highest mean concentration across samples; S. aureus was most frequently detected (54.4% of samples). Hospital-specific differences were evident in culture positivity (Hospital A 85% vs. Hospital B 66.9%) and community composition (PERMANOVA P = 0.001; sample location explained 21.9% vs. 11.7% of variation). 16S profiling confirmed elevated relative abundances of Klebsiella, Enterococcus, and Enterobacter in basins relative to distant surfaces and air. The hospitals studied had high levels of ESKAPEE pathogens, underscoring the need for control measures.

Benzalkonium chloride (BAC) is widely used as a disinfectant in cleaning products and is frequently detected in indoor dust. In this study, we assessed dust samples, along with information on cleaning product use, from 24 pregnant participants. Dust samples were analyzed for BAC concentration and microbial tolerance. Different chain lengths of BAC (C12, C14, and C16) were quantified using LC-MS/MS, and bacterial isolates were tested for BAC tolerance using minimum inhibitory concentration (MIC) assays. BAC was ubiquitously detected, with C12 and C14 being dominant. Higher BAC concentrations were associated with reported disinfectant use and increased microbial tolerance. These findings suggest that indoor antimicrobial use may promote microbial resistance, highlighting potential exposure risks in indoor environments and the need for further investigation into health and ecological impacts.

The core biopolymers (DNA, RNA and proteins) are assembled from their monomers under conditions that avoid water. RNA is crucial for the Origin of Life. When cleaved from its polymerized state, RNA first transitions to nucleoside 2,3-cyclic phosphates. In the reverse direction, RNA polymerizes from 2,3-cyclic monomers in dry states, creating short oligomers that then can ligate on a template under aqueous, alkaline conditions. We studied the role of the counterions in polymerization of 2,3-cyclic nucleotides under geologically plausible settings. Through experiments and simulations, we demonstrate that the presence of ammonium and alkylammonium counterions greatly improves RNA polymerization. The otherwise less reactive cytidine containing monomers formed polyC sequences of up to heptamers; copolymers of AU, GC, or GCAU were detected up to hexamers. Our findings suggest three reasons for this: (1) (Alkyl)ammonium cations form hydrogen bonds with phosphates, (2) their alkaline pKa value can trigger general base catalysis, and (3) (alkyl)ammonium salts naturally form dry, anhydrous materials. The findings indicate that pyrolyzed organic tars creating ammonia-rich gas pockets in subsurface rocks could have enhanced the early evolution of RNA. TOC image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/713775v1_ufig1.gif" ALT="Figure 1"> View larger version (112K): org.highwire.dtl.DTLVardef@1adc431org.highwire.dtl.DTLVardef@12b8da0org.highwire.dtl.DTLVardef@5f187dorg.highwire.dtl.DTLVardef@140ed1a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Wastewater-based epidemiology (WBE) is an effective surveillance approach for monitoring viruses of public health relevance at the community level, complementing clinical surveillance systems. Molecular methods such as PCR/qPCR are widely used for targeted detection, while next-generation sequencing (NGS) with targeted enrichment panels has emerged as a complementary strategy for broader viral detection and genomic characterization. This study comparatively evaluated conventional PCR/qPCR and a targeted enrichment whole-genome sequencing Viral Surveillance Panel (VSP, Illumina) for virus detection in wastewater. Fifty-six wastewater samples collected between 2017 and 2023 from a wastewater treatment plant in Cordoba, Argentina, were concentrated by polyethylene glycol precipitation and pooled by season and year, reaching a total of 14 pools. Each pool was analyzed in parallel by PCR/qPCR for eight human viruses of public health importance and by the VSP, targeting 66 viral species, sequenced on a NovaSeq 6000 platform, and analyzed with the DRAGEN pipeline. Detection frequencies for each virus using PCR/qPCR and VSP were: RoV A 100%/14.3%; NoV 100%/14.3%; AiV 50%/42.9%; SARS-CoV-2 14.3%/0%; HAV 42.9%/0%; HEV 14.3%/0%; JCPyV 35.7%/85.7%; BKPyV 28.6%/71.4%, respectively. In addition, VSP detected the genomes of Astrovirus (71.4%), Salivirus (21.4%), Coxsackie A (14.3%), Rotavirus C (14.3%), and Merkel Cell virus (7.1%), and enable the recovery of 16 near complete genomes (coverage > 92.5%) of AiV, JCPyV, BKPyV, Salivirus and Astrovirus. PCR/qPCR and targeted enrichment NGS provide complementary information wastewater viral surveillance. Their combined application improves virus detection and genomic characterization, reinforcing the value of integrated approaches in environmental virology and public health monitoring.

Robust early warning of emerging viruses requires sampling populations that drive spread coupled with assays capable of detecting new viral variants or species. Untargeted viral metagenomic sequencing can, in principle, detect any virus, including completely novel ones. Composite airplane wastewater enables monitoring long-distance travelers from central collection points; however, the performance of untargeted viral metagenomic sequencing in this sample type remains unknown. In municipal wastewater, abundant sewer-associated microbes and ribosomal RNA depress viral relative abundance, limiting metagenomic sensitivity. We compared untargeted viral metagenomic sequencing of composite airplane wastewater with time-matched municipal wastewater from the Greater Boston area. Human viruses and other human-associated taxa had consistently higher relative abundance in airplane samples than municipal samples, while most sewer-associated taxa had lower relative abundance. An increased relative abundance of human viruses lowers the sequencing depth required to detect emerging pathogens, suggesting that metagenomic sequencing of composite airplane wastewater is a cost-effective method for pathogen-agnostic surveillance. ImportanceLong-distance air travelers spread viral pathogens globally, making them an ideal sentinel population for pandemic surveillance systems. Testing composite airplane wastewater offers a practical, noninvasive approach to monitoring the traveler population. However, current surveillance systems rely on tests targeting specific known pathogens, missing novel threats. Untargeted metagenomic sequencing can detect viruses known or novel, but remains expensive to implement at scale; in municipal wastewater, sewer-derived microbes tend to overwhelm human viruses in sequencing data. We investigated whether a hypothesized reduced sewer microbial load in airplane wastewater would lower the sequencing effort required for viral detection. Understanding the performance of metagenomic sequencing in this context informs the design of cost-effective early-warning systems for emerging pandemics.

We present findings from the first known pilot study of transatlantic airplane wastewater monitoring, conducted over six months at two connected international airports in the United States and the United Kingdom. This study demonstrates the feasibility of implementing bilateral wastewater-based pathogen surveillance at international travel hubs. We outline the operational and analytical methodologies employed, highlight key challenges encountered in transnational coordination, and provide recommendations for the design and implementation of future surveillance programs at points of entry.

Accurate quantification of individual exposure to air pollutants remains a major challenge in environmental health, as fixed-site monitoring fails to account for mobility, indoor environments, and physiological variability. We deployed TracMyAir, a smartphone-based digital health platform designed to generate time-resolved, personalized exposure and inhaled dose estimates for PM2.5 and ozone under real-world conditions. In an exploratory study of 18 adults contributing more than 1,500 participant-hours, the platform integrated smartphone geolocation, regulatory (AirNow) and community-based (PurpleAir) air quality data, building infiltration modeling, microenvironment classification, and wearable-derived physical activity metrics to compute eight tiers of hourly exposure estimates, culminating in individualized inhaled dose. Hourly dose estimates derived from smartphone-and smartwatch-based step counts were concordant (Spearman correlation p=0.97-0.98), while heart rate-based estimates yielded greater variability and higher mean values (p=0.82-0.92). Exposure explained 51-73% of variance in inhaled dose of PM2.5 and 68-84% of ozone, suggesting that physiological-based modeling approaches improve hyperlocal estimates of personal pollutant burden. Substantial inter-and intra-individual variability reflect dynamic microenvironmental transitions and activity patterns. Modeled doses based on regulatory and community sensor networks were strongly correlated (R=0.84), with community sensors located closer to participants on average, supporting the feasibility of integrating dense, low-cost monitoring networks. No consistent association was observed between outdoor pollutant levels and neighborhood socioeconomic status in this cohort. These findings demonstrate the feasibility of a scalable, smartphone-centered digital health approach for hyperlocal exposure and inhaled dose modeling. By leveraging ubiquitous consumer devices and existing air quality networks, TracMyAir enables personalized environmental exposure assessment with potential applications in epidemiology, population health, and precision environmental medicine.

Background Following the end of a public health emergency of international concern, divergence emerged between reported coronavirus disease 2019 (COVID-19) cases and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater. Exploring viral, clinical, patient, and surveillance-related factors underlying this divergence, we developed models to predict clinically confirmed infections, hospitalizations, and severe cases. Methods In this observational study, we analyzed ~2 years of data from January 2022 in Kanagawa Prefecture, Japan, assessing associations between wastewater SARS-CoV-2 RNA concentrations and confirmed, hospitalized, and severe cases, adjusting for wave and variant effects. Findings Our models based on wastewater viral RNA concentrations showed high predictive accuracy (R^2 = 0.8199-0.9961), closely tracking confirmed, hospitalized, and severe cases. Models derived from earlier waves were applied to subsequent waves with residual correction based on prior prediction errors and maintained good predictive performance (root mean square error = 0.0665-0.2065). Divergence between wastewater viral RNA concentrations and reported cases was not explained by changes in viral shedding. Declines in patients' healthcare-seeking behavior and testing were associated with trends in confirmed cases, whereas milder clinical presentation was associated with severe case trends. The lineages XBB.1.9.2 and BA.2.86 were identified as candidates associated with reduced virulence. Interpretation By incorporating understanding of viral, clinical, and surveillance-related mechanisms, wastewater surveillance may enable prediction of case trends approximately one week earlier than official reporting and inform healthcare capacity planning.

Understanding how airborne particulates disrupt the human alveolar barrier requires in vitro systems that accurately replicate its composition and function. We present a biodegradable lung alveoli-on-a-chip that reproduces the architecture and physiology of the human air-blood interface using a porous poly(lactic-co-glycolic acid) (PLGA) membrane positioned between epithelium and endothelium under air-liquid interface (ALI) culture. The membrane, fabricated by porogen-assisted nonsolvent-induced phase separation, exhibited >50 % porosity, [~]2 {micro}m thickness, and mechanical compliance over 100-fold higher than conventional Transwell inserts, closely resembling the native interstitium. During co-culture, gradual PLGA degradation was compensated by cell-secreted extracellular-matrix (ECM) proteins such as collagen IV and laminin, forming a self-remodeling barrier that maintained integrity for at least 11 days. The platform supported stable epithelial-endothelial co-culture, high transepithelial electrical resistance, and physiologically relevant permeability. To demonstrate its utility, the chip was used to assess pulmonary toxicity of four types of waste-combustion-derived particulates, including rubber, plastic bags, plastic bottles, and textile fibers, delivered apically under ALI conditions. All combustion products reduced cell viability, increased hydrogen-peroxide release, and elevated {gamma}-H2AX expression, indicating oxidative and genotoxic stress, while disrupting barrier permeability. Rubber combustion particles elicited the most severe toxicity, causing the greatest loss of viability, accumulation of reactive oxygen species, and formation of DNA double-strand breaks. Together, these results establish a biodegradable, ECM-remodeling lung alveoli-on-a-chip as a physiologically relevant platform for investigating source-specific particulate toxicity and alveolar-barrier pathophysiology. By bridging environmental exposure models with human-relevant lung biology, this system provides a quantitative and translatable tool for evaluating respiratory risks and therapeutic interventions.

While distinct environmental exposures imprint unique mutational signatures on cancer genomes, the specific causal patterns for many known carcinogens remain uncharacterized in relevant human tissues. To address this gap, we developed a novel, physiologically relevant system that uses a combination of airway epithelial cells and whole genome sequencing to characterize mutational patterns induced by genotoxic carcinogens associated with lung cancer. After validating the platforms accuracy by successfully recapturing the known signature for Benzo(a)pyrene (BaP), we used this system to gain detailed insights into the types of mutations that occur with exposure to N-nitrosotris-(2-chloroethyl) urea (NTCU) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), genotoxic compounds that induce lung squamous cell carcinoma and lung adenocarcinoma in mouse models, respectively. Cells exposed to NTCU had significantly more somatic SNVs compared to control samples. An average of 82.3% of mutations in NTCU samples were attributed to a novel mutational signature distinct from those in the COSMIC database but highly correlated with recent in vivo mouse models. In contrast, NNK exposure did not demonstrate a distinct mutational pattern above background at both high and low concentrations. Ultimately, this in vitro system provides a robust platform to define causal links between environmental exposures and mutational patterns in lung cancer mutagenesis. Statement of SignificanceIn vitro exposure of N-nitrosotris-(2-chloroethyl) urea to airway epithelial cells revealed a distinct mutational signature.

Traditionally, studies have explored the impacts of individual water chemistry parameters on the persistence of Mycobacterium spp. and Legionella spp. in isolation with the underlying assumption that these associations are likely monotonic in nature. Yet chemical and microbiological changes are complex, and associations are likely highly combinatorial. In this study, we use interpretable machine learning models to disentangle the integrative and nonlinear associations between water chemistry and occurrence/abundance of Mycobacterium spp. and Legionella spp. Seasonal data from source water, point-of-entry and distribution systems of eight full-scale drinking water systems demonstrated that shifts in overall water chemistry were associated with the changes in microbial abundance during treatment and distribution. Machine learning models indicated moderate predictive ability of integrated water chemistry towards Legionella spp. abundance and towards the occurrence of both Legionella spp. and Mycobacterium spp., whereas predictive performance for Mycobacterium spp. abundance was limited. The association between nitrate and Legionella spp. abundance was disinfectant regimes dependent, while dissolved organic carbon exhibited a concentration dependent response type (i.e., positive and negative association). In chloraminated systems, Legionella spp. abundance was positively associated with ammonia and nitrate, highlighting the critical role of nitrification. Here, it appears that pH likely influences the initial colonization of Legionella spp. while ammonia governs its abundance in drinking water. Overall, this study demonstrates that integrated water chemistry and parameter-specific nonlinear effects collectively explain persistence of Mycobacterium spp. and Legionella spp. in drinking water systems.

Polyethylene (PE) is a widely used plastic that persists in the environment and resists breakdown via microbial degradation. In this work, we discovered a new bacterium, Paenibacillus polyethylenelyticus JNU01, that grows on a PE-like wax (PELW, 4 kDa) as its sole carbon source, causing chemical modifications to the substrate and releasing small-molecule products. Genomic and transcriptomic analyses identified a multicopper oxidase (PpMmcO) as a key enzyme candidate for this observed activity. PpMmcO caused surface oxidation, increased hydrophilicity, and the release of oxygenated products such as ketones, alkanes, and alkenoic acids. Scanning electron microscopy confirmed surface damage on both PELW and post-use greenhouse PE films. Weight loss analysis showed mass losses of 5.2% for the PELW powder and 1.6% for the greenhouse PE film after treatment with wild-type PpMmcO. We propose a radical-mediated pathway catalyzed by PpMmcO. These findings identify a new bacterium and enzyme capable of initiating PE oxidation and provide insight into biological processes that may act on polyethylene.

IntroductionParticulate Matter (PM2.5) exposure contributes to the global disease burden, yet its monitoring remains sparse and uneven and is limited in many limited ground monitoring network settings. Road-traffic proxy indicators can provide indirect estimates of PM2.5 where measurements are limited but require context-specific validation. We evaluated three PM2.5 road-traffic related proxies:(I) population-Weighted Road Network Density (WRND), (ii) Euclidean (straight line) distance from highways (EH), and (iii) Euclidean distance from main roads (EM). MethodsWe validated proxies using high-resolution outdoor filtered PM2.5 personal exposure measurements collected over 1 year from 343 postpartum participants in The Gambia, Kenya, and Mozambique. Village-level spatial patterns for the PM2.5-proxy relationship were mapped using 5 km hexagonal aggregated tessellations. Proxy-PM2.5 associations were assessed using Spearman correlation, and predictive utility was tested using country-specific and global Random Forest (RF) models (3-fold cross-validation), reporting R2, RMSE, and feature importance ResultsSpatial mapping showed heterogeneous proxy-PM2.5 relationships across and within sites, with elevated PM2.5 occurring in both low- and high-proxy contests. WRND-PM2.5 correlations were weak overall and statistically significant only in Mozambique (r = 0.351; p = 0.005), with non-significant associations in Kenya (r = -0.041; p = 0.673) and The Gambia (r = -0.020; p = 0.909). EH-PM2.5 correlations were positive in The Gambia (r = 0.335; p = 0.053) and Mozambique (r = 0.292; p = 0.020) but negative and significant in Kenya (r = -0.224; p = 0.018).Single-variable RF models performed poorly across all countries (R2 < 0.45) and the Global model (R2=0.42). Combining proxies improved performance in Kenya (R2=0.52; RMSE=31.7{micro}g/m3) and Mozambique (R2=0.60; RMSE=8.9 {micro}g/m3), Global R2=0.46; RMSE=29.1 {micro}g/m3), although in The Gambia, the combined model (R2=0.53; RMSE=37.6 {micro}g/m3) did not exceed the best single-proxy model. ConclusionRoad-network proxies provide context-dependent signals of personal PM2.5 exposure, and predictive performance is strengthened when proxies are combined in a hybrid model.

Background Ambient air pollution is a leading global health risk and disproportionately affects populations of Low- and Middle-Income Countries (LMICs). In 2021, WHO revised its Air Quality Guidelines (AQG), lowering recommended annual limits for Particulate Matter 2.5 (PM2.5) and Nitrogen Dioxide (NO2). We estimated the potential health and economic impacts of achieving WHO Interim Target 3 (IT3) and AQG concentrations across LMICs. Methods We conducted a health impact assessment across 136 LMICs to quantify one-year changes in all-cause and cause-specific mortality (chronic obstructive pulmonary disease [COPD], ischaemic heart disease [IHD], and stroke) and disease incidence (COPD, dementia, IHD, and stroke) under WHO IT3 and AQG counterfactual scenarios for PM2.5 and NO2. Concentration-response functions were applied at 1km x 1km resolution. Economic welfare impacts of mortality risk reductions were estimated using country-adjusted values of a statistical life (VSL, Int$ PPP-adjusted 2021). Direct medical and productivity-related costs associated with incident cases were estimated using a cost-of-illness (COI) framework. Uncertainty intervals (UI) reflect uncertainty in concentration-response functions. Results Attainment of WHO IT3 and AQG concentrations for PM2.5 was associated with an estimated 16.04% reduction (6.58million, UI: 6.10-7.07million) and 22.97% reduction (9.43million, UI: 8.75-10.11million) in annual deaths, respectively. Corresponding VSL-based estimates of deaths averted were Int$5.5 trillion (7.0% of aggregate LMIC GDP) and Int$8.4 trillion (10.6% of GDP), respectively. For NO2, IT3 and AQG scenarios were associated with estimated reductions of approximately 1.06% (approximately 435,000 deaths, UI: 388,000-483,000) and 2.79% (435,000 deaths; UI: 388,000-483,000), yielding gains of Int$0.6 trillion (0.7% of GDP) and Int$1.5 trillion (1.9% of GDP). Disease-specific mortality reductions were most prominent for IHD and stroke in Asia and Africa. Under the PM2.5 AQG scenario, an estimated 2.82million (1.67-2.97) COPD, 1.10million (0.83-1.37) dementia, 7.3million (6.41-8.19) IHD, and 2.3million (2.19-2.41) stroke cases could be delayed or averted in one year. Associated reductions in direct medical and productivity-related costs were greatest for IHD, COPD, and stroke. NO2-related morbidity reductions were smaller across all outcomes. All estimates represent one-year changes in risk relative to counterfactual exposure and may reflect delayed rather than permanently avoided events. Discussion Achieving both WHO IT3 and AQG values in LMICs could yield substantial reductions in premature mortality and disease incidence, particularly for cardiovascular and respiratory conditions, alongside large, monetised welfare gains from reduced mortality risk. These findings underscore the considerable societal value of air quality improvements and support accelerated action toward meeting WHO guideline levels in regions bearing the highest pollution burden.

Mass gatherings pose a concern for public health because they are associated with dense crowds, increased social interaction, and travel, all of which can facilitate the rapid transmission of infectious diseases. Wastewater and environmental surveillance (WES) were used for pathogen monitoring during the 2024 NFL Annual Player Selection Meeting (the Draft) in Detroit, MI, an event that drew an estimated 775,000 attendees. Wastewater and environmental samples were queried for respiratory viruses and clinically relevant antimicrobial resistance genes (ARG). WES did not detect an increase in the concentration of monitored respiratory viruses (SARS-CoV-2, IAV, IBV, and RSV) associated with the 2024 NFL Draft. In contrast, WES detected a transient increase in carbapenemase targets in wastewater, primarily driven by a fourfold increase in blaOXA-48. Resistome structure in wastewater was dominated by sampling site characteristics rather than changes associated with the event. The Draft weekend coincided with rainfall-driven combined sewer overflow (CSO), potentially allowing the dissemination of ARG to the environment. In surface waters receiving wastewater effluent, an increase in detection frequency and normalized concentrations for multiple ARG were observed following the Draft. WES provided an overview of pathogen prevalence before, during, and after a large-scale gathering, showing how it can warn of emerging health risks in near real time.

Wildfire smoke (WFS) events are an important public health concern for communities in the Pacific Northwest of the United States. Previous studies of portable air cleaners, including high efficiency particulate air (HEPA) filtration and do-it-yourself (DIY) box fan filters built with MERV 13-rated filters, have indicated that their use in residential settings may be an effective way to reduce indoor exposures to fine particulate matter during WFS episodes. The lower-cost, easy to build instructions and availability of materials of DIY box fan filters have made their distribution by both public health agencies and community groups an attractive approach to improve community preparedness. Here, we describe a low-cost, easy-to-assemble, portable exposure chamber system that can be used to support a variety of community-engaged demonstrations of WFS removal efficiency as well as provide a mechanism to estimate the efficiency of filtration systems in a controlled environment. We conducted experiments using the portable chamber to assess the clean air delivery rate (CADR) of a MERV 13-rated DIY box fan filter, which was found to be 92.2 and 145.2 cfm at low and high fan speeds, respectively. In addition to using the chamber system to evaluate the CADR of DIY box fan filters, we also provide a case-study example, working with a tribal community in Central Washington, who used the tent system for a live demonstration of a DIY box fan filter experiment during their community gathering to promote WFS and air quality intervention knowledge and distribution of box fan filters.