Eye infection risks from Pseudomonas aeruginosa via hand soap and eye drops.

Eye infections from bacterial contamination of bulk-refillable liquid soap dispensers and artificial tear eye drops continue to occur, resulting in adverse health outcomes that include impaired vision or eye enucleation. Pseudomonas aeruginosa (P. aeruginosa), a common cause of eye infections, can grow in eye drop containers and refillable soap dispensers to high numbers. To assess the risk of eye infection, a quantitative microbial risk assessment for P. aeruginosa was conducted to predict the probability of an eye infection for two potential exposure scenarios: (i) individuals using bacteria-contaminated eye drops and (ii) contact lens wearers washing their hands with bacteria-contaminated liquid soap prior to placing the lens. The median risk of an eye infection using contaminated eye drops and hand soap for both single and multiple exposure events (per day) ranged from 10-1 to 10-4, with contaminated eye drops having the greater risk. The concentration of P. aeruginosa was identified as the parameter contributing the greatest variance on eye infection risk; therefore, the prevalence and level of bacterial contamination of the product would have the greatest influence on health risk. Using eye drops in a single-use container or with preservatives can mitigate bacterial growth, and using non-refillable soap dispensers is recommended to reduce contamination of hand soap. Given the opportunistic nature of P. aeruginosa and its ability to thrive in unique environments, additional safeguards to mitigate bacterial growth and exposure are warranted.IMPORTANCEPseudomonas aeruginosa (P. aeruginosa) is a pathogen that can persist in a variety of unusual environments and continues to pose a significant risk for public health. This quantitative microbial risk assessment (QMRA) estimates the potential human health risks, specifically for eye infections, associated with exposure to P. aeruginosa in bacteria-contaminated artificial tear eye drops and hand soap. This study applies the risk assessment framework of QMRA to evaluate eye infection risks through both consumer products. The study examines the prevalence of this pathogen in eye drops and soap, as well as the critical need to implement measures that will mitigate bacterial exposure (e.g., single-use soap dispensers and eye drops with preservatives). Additionally, limitations and challenges are discussed, including the need to incorporate data regarding consumer practices, which may improve exposure assessments and health risk estimates.

Assessment of a SARS-CoV-2 wastewater monitoring program in El Paso, Texas, from November 2020 to June 2022.

The border city of El Paso, Texas, and its water utility, El Paso Water, initiated a SARS-CoV-2 wastewater monitoring program to assess virus trends and the appropriateness of a wastewater monitoring program for the community. Nearly weekly sample collection at four wastewater treatment facilities (WWTFs), serving distinct regions of the city, was analyzed for SARS-CoV-2 genes using the CDC 2019-Novel coronavirus Real-Time RT-PCR diagnostic panel. Virus concentrations ranged from 86.7 to 268,000 gc/L, varying across time and at each WWTF. The lag time between virus concentrations in wastewater and reported COVID-19 case rates (per 100,00 population) ranged from 4-24 days for the four WWTFs, with the strongest trend occurring from November 2021 - June 2022. This study is an assessment of the utility of a geographically refined SARS-CoV-2 wastewater monitoring program to supplement public health efforts that will manage the virus as it becomes endemic in El Paso.

Wastewater analysis of Mpox virus in a city with low prevalence of Mpox disease: an environmental surveillance study.

Background: Tracking infectious diseases at the community level is challenging due to asymptomatic infections and the logistical complexities of mass surveillance. Wastewater surveillance has emerged as a valuable tool for monitoring infectious disease agents including SARS-CoV-2 and Mpox virus. However, detecting the Mpox virus in wastewater is particularly challenging due to its relatively low prevalence in the community. In this study, we aim to characterize three molecular assays for detecting and tracking the Mpox virus in wastewater from El Paso, Texas, during February and March 2023. Methods: In this study, a combined approach utilizing three real-time PCR assays targeting the C22L, F3L, and F8L genes and sequencing was employed to detect and track the Mpox virus in wastewater samples. The samples were collected from four sewersheds in the City of El Paso, Texas, during February and March 2023. Wastewater data was compared with reported clinical case data in the city. Findings: Mpox virus DNA was detected in wastewater from all the four sewersheds, whereas only one Mpox case was reported during the sampling period. Positive signals were still observed in multiple sewersheds after the Mpox case was identified. Higher viral concentrations were found in the pellet than in the supernatant of wastewater. Notably, an increasing trend in viral concentration was observed approximately 1-2 weeks before the reporting of the Mpox case. Further sequencing and epidemiological analysis provided supporting evidence for unreported Mpox infections in the city. Interpretation: Our analysis suggests that the Mpox cases in the community is underestimated. The findings emphasize the value of wastewater surveillance as a public health tool for monitoring infectious diseases even in low-prevalence areas, and the need for heightened vigilance to mitigate the spread of Mpox disease for safeguarding global health. Funding: Center of Infectious Diseases at UTHealth, the University of Texas System, and the Texas Epidemic Public Health Institute. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of these funding organizations.

Informing ASR Treatment Practices in a Florida Aquifer through a Human Health Risk Approach.

Aquifer storage and recovery (ASR) can augment water supplies and hydrologic flows under varying climatic conditions. However, imposing drinking water regulations on ASR practices, including pre-treatment before injection into the aquifer, remains arguable. Microbial inactivation data-Escherichia coli, Pseudomonas aeruginosa, poliovirus type 1 and Cryptosporidium parvum-were used in a human health risk assessment to identify how the storage time of recharged water in the Floridan Aquifer enhances pathogen inactivation, thereby mitigating the human health risks associated with ingestion. We used a quantitative microbial risk assessment to evaluate the risks for a gastrointestinal infection (GI) and the associated disability-adjusted life years (DALYs) per person per year. The risk of developing a GI infection for drinking water no longer exceeded the suggested annual risk threshold (1 × 10-4) by days 31, 1, 52 and 80 for each pathogen, respectively. DALYs per person per year no longer exceeded the World Health Organization threshold (1 × 10-6) by days 27, <1, 43 and 72. In summary, storage time in the aquifer yields a significant reduction in health risk. The findings emphasize that considering microbial inactivation, caused by storage time and geochemical conditions within ASR storage zones, is critical for recharge water treatment processes.

Integrating microbial source tracking with quantitative microbial risk assessment to evaluate site specific risk based thresholds at two South Florida beaches.

Quantitative microbial risk assessment (QMRA) can be used to evaluate health risks associated with recreational beach use. This study developed a site-specific risk assessment using a novel approach that combined quantitative PCR-based measurement of microbial source tracking (MST) genetic markers (human, dog, and gull fecal bacteria) with a QMRA analysis of potential pathogen risk. Water samples (n = 24) from two recreational beaches were collected and analyzed for MST markers as part of a broader Beach Exposure And Child Health Study that examined child behavior interactions with the beach environment. We report here the measurements of fecal bacteria MST markers in the environmental DNA extracts of those samples and a QMRA analysis of potential health risks utilizing the results from the MST measurements in the water samples. Human-specific Bacteroides was enumerated by the HF183 Taqman qPCR assay, gull-specific Catellicoccus was enumerated by the Gull2 qPCR assay, and dog-specific Bacteroides was enumerated by the DogBact qPCR assay. Derived reference pathogen doses, calculated from the MST marker concentrations detected in recreational waters, were used to estimate the risk of gastrointestinal illness for both children and adults. Dose-response equations were used to estimate the probability of the risk of infection (Pinf) per a swimming exposure event. Based on the QMRA simulations presented in this study, the GI risk from swimming or playing in water containing a mixture of human and non-human fecal sources appear to be primarily driven by the human fecal source. However, the estimated median GI health risk for both beaches never exceeded the U.S. EPA risk threshold of 32 illnesses per 1,000 recreation events. Our research suggests that utilizing QMRA together with MST can further extend our understanding of potential recreational bather risk by identifying the source contributing the greatest risk in a particular location, therefore informing beach management responses and decision-making.

Wastewater sequencing reveals community and variant dynamics of the collective human virome.

Wastewater is a discarded human by-product, but its analysis may help us understand the health of populations. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels while bypassing the difficulties and pit falls of individual testing. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. Here, we conduct a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Critical to detection is the use of a viral probe capture set targeting thousands of viral species or variants. Over 450 distinct pathogenic viruses from 28 viral families are observed, most of which have never been detected in such samples. Sequencing reads of established pathogens and emerging viruses correlate to clinical data sets of SARS-CoV-2, influenza virus, and monkeypox viruses, outlining the public health utility of this approach. Viral communities are tightly organized by space and time. Finally, the most abundant human viruses yield sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health.

Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks.

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.

Prolonged viral shedding from noninfectious individuals confounds wastewater-based epidemiology.

Wastewater surveillance has been widely used to track and estimate SARS-CoV-2 incidence. While both infectious and recovered individuals shed virus into wastewater, epidemiological inferences using wastewater often only consider the viral contribution from the former group. Yet, the persistent shedding in the latter group could confound wastewater-based epidemiological inference, especially during the late stage of an outbreak when the recovered population outnumbers the infectious population. To determine the impact of recovered individuals' viral shedding on the utility of wastewater surveillance, we develop a quantitative framework that incorporates population-level viral shedding dynamics, measured viral RNA in wastewater, and an epidemic dynamic model. We find that the viral shedding from the recovered population can become higher than the infectious population after the transmission peak, which leads to a decrease in the correlation between wastewater viral RNA and case report data. Furthermore, the inclusion of recovered individuals' viral shedding into the model predicts earlier transmission dynamics and slower decreasing trends in wastewater viral RNA. The prolonged viral shedding also induces a potential delay in the detection of new variants due to the time needed to generate enough new cases for a significant viral signal in an environment dominated by virus shed by the recovered population. This effect is most prominent toward the end of an outbreak and is greatly affected by both the recovered individuals' shedding rate and shedding duration. Our results suggest that the inclusion of viral shedding from non-infectious recovered individuals into wastewater surveillance research is important for precision epidemiology.

Wastewater pandemic preparedness: Toward an end-to-end pathogen monitoring program.

Molecular analysis of public wastewater has great potential as a harbinger for community health and health threats. Long-used to monitor the presence of enteric viruses, in particular polio, recent successes of wastewater as a reliable lead indicator for trends in SARS-CoV-2 levels and hospital admissions has generated optimism and emerging evidence that similar science can be applied to other pathogens of pandemic potential (PPPs), especially respiratory viruses and their variants of concern (VOC). However, there are substantial challenges associated with implementation of this ideal, namely that multiple and distinct fields of inquiry must be bridged and coordinated. These include engineering, molecular sciences, temporal-geospatial analytics, epidemiology and medical, and governmental and public health messaging, all of which present their own caveats. Here, we outline a framework for an integrated, state-wide, end-to-end human pathogen monitoring program using wastewater to track viral PPPs.

Wide mismatches in the sequences of primers and probes for monkeypox virus diagnostic assays.

Rapid and accurate diagnosis of infections is fundamental to containment of disease. Several monkeypox virus (MPV) real-time diagnostic assays have been recommended by the CDC; however, the specificity of the primers and probes in these assays for the ongoing MPV outbreak has not been investigated. We analyzed the primer and probe sequences present in the CDC recommended MPV generic real-time PCR assay by aligning those sequences against 1730 MPV complete genomes reported in 2022 worldwide. Sequence mismatches were found in 99.08% and 97.46% of genomes for the MPV generic forward and reverse primers, respectively. Mismatch-corrected primers were synthetized and compared to the generic assay for MPV detection. Results showed that the two primer-template mismatches resulted in a ~11-fold underestimation of initial template DNA in the reaction and 4-fold increase in the 95% LOD. We further evaluated the specificity of seven other real-time PCR assays used for MPV and orthopoxvirus (OPV) detection and identified two assays with the highest matching score (>99.6%) to the global MPV genome database in 2022. Genetic variations in the primer-probe regions across MPV genomes could indicate the temporal and spatial emergence pattern of monkeypox disease. Our results show that the current MPV real-time generic assay may not be optimal to accurately detect MPV, and the mismatch-corrected assay with full complementarity between primers and current MPV genomes could provide a more sensitive and accurate detection of MPV.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data.

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.

PAH depletion in weathered oil slicks estimated from modeled age-at-sea during the Deepwater Horizon oil spill.

During time-periods oil slicks are in the marine environment (age-at-sea), weathering causes significant changes in composition and mass loss (depletion) of oil spill chemicals including the more toxic polycyclic aromatic hydrocarbons (PAHs). The goal of this study was to estimate the age-at-sea of weathered oil slicks using the oil spill module of the Connectivity Modeling System and to use this age to interpret PAH concentration measurements. Percent depletion (PD) for each measurement was computed as the percentage difference between the original and measured PAH concentration in the crude oil and weathered oil slicks, normalized upon the mass losses relative to hopane. Mean PD increased with estimated age-at-sea for all PAHs. Less PD was observed for alkylated than for parent PAHs, likely due to decreasing vapor pressure with increasing degree of alkylation. We conclude that estimated age-at-sea can be used to explain PAH depletion in weathered oil slicks. We propose PAH vapor pressure can be coupled with the model to expand capacity for predicting concentration distributions of individual parent and alkylated PAHs in weathered oil along the coastline. This new module will advance the science supporting oil spill response by providing more certain estimates of health risks from oil spills.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data.

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in population-level SEIR model. We demonstrated that the temperature effect on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020 â€" Jan 25, 2021) in the Great Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 16 days and 8.6 folds ( R = 0.93), respectively. This work showcases a simple, yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.

Using satellite-based AOD and ground-based measurements to evaluate the impact of the DWH oil spill on coastal air quality.

The 2010 DWH disaster generated atmospheric pollutants of health concern which reached the Gulf Coast. This study evaluated whether changes in coastal air quality due to the disaster were captured by aerosol optical depth (AOD) estimated using satellite data and by ground-based monitoring of air pollution, including fine particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5), benzene and naphthalene. Mean monthly AOD levels were higher in May 2010 [during oil spill time], (mean AOD = 0.355), than for the prior (mean AOD = 0.258) and following years (mean AOD = 0.252) (p < 0.05). PM2.5 concentrations and AOD were significantly correlated (R2 = 0.59, p < 0.05), for one study area. Elevated PM2.5, benzene, and naphthalene concentrations coincided with downwind directions from the location of the oil slicks. A fully-coupled oil fate and transport atmospheric transport model of oil spill emissions, integrated with AOD and more extensive ground-based measurements, is recommended to predict coastal population exposures during oil spills.

Quantifying pathogen infection risks from household laundry practices.

AIMS: Contaminated laundry can spread infections. However, current directives for safe laundering are limited to healthcare settings and not reflective of domestic conditions. We aimed to use quantitative microbial risk assessment to evaluate household laundering practices (e.g., detergent selection, washing and drying temperatures, and sanitizer use) relative to log10 reductions in pathogens and infection risks during the clothes sorting, washer/dryer loading, folding and storing steps. METHODS AND RESULTS: Using published data, we characterized laundry infection risks for respiratory and enteric pathogens relative to a single user contact scenario and a 1.0 × 10-6 acceptable risk threshold. For respiratory pathogens, risks following cold water wash temperatures (e.g. median 14.4℃) and standard detergents ranged from 2.2 × 10-5 to 2.2 × 10-7 . Use of advanced, enzymatic detergents reduced risks to 8.6 × 10-8 and 2.2 × 10-11 respectively. For enteric pathogens, however, hot water, advanced detergents, sanitizing agents and drying are needed to reach risk targets. SIGNIFICANCE AND IMPACT OF THE STUDY: Conclusions provide guidance for household laundry practices to achieve targeted risk reductions, given a single user contact scenario. A key finding was that hand hygiene implemented at critical control points in the laundering process was the most significant driver of infection prevention, additionally reducing infection risks by up to 6 log10 .

Quantified Activity Patterns for Young Children in Beach Environments Relevant for Exposure to Contaminants.

In a study to evaluate beach play activities, 120 children were videotaped to observe and quantify factors that could influence their exposure to contaminants in the beach environment. Children aged 1 to 6 years were followed by researchers with video cameras at beaches (two in Miami, Florida and two in Galveston, Texas) for approximately one hour each. Factors evaluated included time spent in various beach locations, various activities engaged in, and various surfaces contacted (including contacts by hand and mouth). Activities recorded in the videos were transcribed to text files to allow for quantitative analyses. Across all sexes, age groups, and beaches, Wading was the most common activity and Seawater was the most common location where children played. The left hand was found to not be in contact with objects most of the time, while the right hand, considered the most dominant hand in most cases, contacted Plastic-Toys the most. Although activity patterns collection through videotaping and videotranslation can be labor-intensive, once collected, they can be widely useful for estimates of exposures to all contaminants in the beach environment (e.g., microorganisms and chemicals) as well as UV exposure, with considerations for whether the contaminants are found in water, sand or both. These activity patterns were collected to potentially look at exposures following the Deepwater Horizon 2010 Spill.

Review of methods to determine hand surface area of children less than six years old: a case study.

Various methods exist to determine the surface area of hands. The consistency of these methods is essential given that risk assessments utilize hand surface area (HSA) to quantify exposure to environmental contaminants. HSA is also utilized in the clinical setting to estimate size of burns, and to determine specific treatments and medication dosages. A reliable method of surface area measurement is important to guide these decisions, especially in children who are vulnerable to environmental contaminants and medication side effects. Despite this, fewer HSA-determining studies have been performed for children compared to adults. In this study, 122 children completed hand tracings, and the tracings were digitized using an ImageJ program to determine HSA. Six previously published methods of determining HSA were utilized based on the child's height, weight, and length and width of hand. Children were analyzed by age group including 0-2, 3-4, and 5-6 years. The HSA measurements determined by five of the six methods were statistically different from HSA determined using direct hand tracings/Image J methodology (p < 0.001). The single remaining study that did not differ significantly from the hand tracing method provided a uniform hand to total body surface area (TBSA) ratio for children of all ages. Based on these results, we propose a novel age-group-specific ratio utilizing the HSA results from hand tracings and TBSA calculations. The percentages of TBSA that reflect HSA for children aged 0-2, 3-4 and 5-6 years were 0.91%, 0.90% and 0.87%, respectively. These percentages should be considered for use in risk assessments and the clinical setting to guide treatment and prognosis.

Soil-skin adherence measures from hand press trials in a Gulf study of exposures.

Marine oil spills and the resulting environmental contamination is common along coastal areas; however, information is lacking about the safety of impacted beaches for public use, especially for the most vulnerable population: children. One route of exposure for children at oil impacted beaches is through contact with sands. The purpose of this study was to evaluate beach sand skin adherence for children under the age of seven. Each of 122 children participated in a hand press trial conducted at one of four different U.S. beaches (two in Miami, FL, and two in Galveston, TX USA). During the hand press trials, hand conditions of the children were randomized (dry, wet, or with sunscreen), and soil adherence (mass of sand per palmar surface area of the hand) and the maximum pressure applied (force applied per area of hand) was measured and calculated. Each child was instructed to press their hands on a soil laden tray for 5 s and pressure of contact was measured using a scale. Results (n = 98) showed that the average soil adherence for both palmar hands across the four beaches ranged from 0.200 to 234 mg/cm2 with an average of 35.7 mg/cm2, with boys (40.4 mg/cm2) showing slightly higher means than girls (31.7 mg/cm2), but these differences were not significant even after adjusting for age. Among the three conditions evaluated, the highest loading was measured for children with wet hands (mean 65.3 mg/cm2), followed by dry hands (mean 24.5 mg/cm2). Sunscreen hands (mean 23.2 mg/cm2) had the lowest loadings. The pressure of contact ranged from 0.180 to 1.69 psi and varied by age groups and by height and weight, where pressure of contact did not have a significant influence on soil adherence. The average adhered sand grain size and average ambient sand grain size both had a statistically significant impact on hand soil adherence. Overall results from this study can be utilized in exposure and risk assessment models to evaluate the possible health impacts from contaminants found in beach sands.

Quantitative microbial risk assessment of SARS-CoV-2 for workers in wastewater treatment plants.

Faecal-oral transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is yet to be validated, but it is a critical issue and additional research is needed to elucidate the risks of the novel coronavirus in sanitation systems. This is the first study that investigates the potential health risks of SARS-CoV-2 in sewage to wastewater treatment plant (WWTP) workers. A quantitative microbial risk assessment (QMRA) is applied for three COVID-19 scenarios (moderate, aggressive and extreme) to study the effects of different stages of the pandemic in terms of percentage of infected population on the probability of infection to WWTP workers. A dose-response model for SARS-CoV-1 (as a surrogate pathogen) is assumed in the QMRA for SARS-CoV-2 using an exponential model with k = 4.1 × 102. Literature data are incorporated to inform assumptions for calculating the viral load, develop the model, and derive a tolerable infection risk. Results reveal that estimates of viral RNA in sewage at the entrance of WWTPs ranged from 4.14 × 101 to 5.23 × 103 GC·mL-1 (viable virus concentration from 0.04 to 5.23 PFU·mL-1, respectively). In addition, estimated risks for the aggressive and extreme scenarios (2.6 × 10-3 and 1.3 × 10-2, respectively) were likely to be above the derived tolerable infection risk for SARS-CoV-2 of 5.5 × 10-4 pppy, thus reinforcing the concern of sewage systems as a possible transmission pathway of SARS-CoV-2. These findings are helpful as an early health warning tool and in prioritizing upcoming risk management strategies, such as Emergency Response Plans (ERPs) for water and sanitation operators during the COVID-19 and future pandemics.

A novel method to evaluate chemical concentrations in muddy and sandy coastal regions before and after oil exposures.

Oil spills can result in changes in chemical concentrations along coastlines. In prior work, these concentration changes were used to evaluate the date sediment was impacted by oil (i.e., oil exposure date). The objective of the current study was to build upon prior work by using the oil exposure date to compute oil spill chemical (OSC) concentrations in shoreline sediments before and after exposure. The new method was applied to OSC concentration measures collected during the Deepwater Horizon oil spill with an emphasis on evaluating before and after concentrations in muddy versus sandy regions. The procedure defined a grid that overlaid coastal areas with chemical concentration measurement locations. These grids were then aggregated into clusters to allow the assignment of chemical concentration measurements to a uniform coastal type. Performance of the method was illustrated for ten chemicals individually by cluster, and collectively for all chemicals and all clusters. Results show statistically significant differences between chemical concentrations before and after the calculated oil exposure dates (p < 0.04 for each of the 10 chemicals within the identified clusters). When aggregating all chemical measures collectively across all clusters, chemical concentrations were lower before oil exposure in comparison to after (p < 0.0001). Sandy coastlines exhibited lower chemical concentrations relative to muddy coastlines (p < 0.0001). Overall, the method developed is a useful first step for establishing baseline chemical concentrations and for assessing the impacts of disasters on sediment quality within different coastline types. Results may be also useful for assessing added ecological and human health risks associated with oil spills.