Geology topics

Joel P. Stokdyk

Publications and source records attributed to Joel P. Stokdyk.

27 records · Page 2Linked to original sources

USGS2020

Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA

Drinking water supply wells can be contaminated by a broad range of waterborne pathogens. However, groundwater assessments frequently measure microbial indicators or a single pathogen type, which provides a limited characterization of potential health risk. This study assessed contamination of wells by testing for viral, bacterial, and protozoan pathogens and fecal markers. Wells supplying groundwater to community and noncommunity public water systems in Minnesota, USA (n = 145) were sampled every other month over one or two years and tested using 23 qPCR assays. Eighteen genetic targets were detected at least once, and microbiological contamination was widespread (96% of 145 wells, 58% of 964 samples). The sewage-associated microbial indicators HF183 and pepper mild mottle virus were detected frequently. Human or zoonotic pathogens were detected in 70% of wells and 21% of samples by qPCR, with Salmonella and Cryptosporidium detected more often than viruses. Samples positive by qPCR for adenovirus (HAdV), enterovirus, or Salmonella were analyzed by culture and for genotype or serotype. qPCR-positive Giardia and Cryptosporidium samples were analyzed by immunofluorescent assay (IFA), and IFA and qPCR concentrations were correlated. Comparisons of indicator and pathogen occurrence at the time of sampling showed that total coliforms, HF183, and Bacteroidales -like HumM2 had high specificity and negative predictive values but generally low sensitivity and positive predictive values. Pathogen-HF183 ratios in sewage have been used to estimate health risks from HF183 concentrations in surface water, but in our groundwater samples Cryptosporidium oocyst:HF183 and HAdV:HF183 ratios were approximately 10,000 times higher than ratios reported for sewage. qPCR measurements provided a robust characterization of microbiological water quality, but interpretation of qPCR data in a regulatory context is challenging because few studies link qPCR measurements to health risk.

Minnesota↗

USGS2019

Reporting the limits of detection and quantification for environmental DNA assays

Background Environmental DNA (eDNA) analysis is increasingly being used to detect the presence and relative abundance of rare species, especially invasive or imperiled aquatic species. The rapid progress in the eDNA field has resulted in numerous studies impacting conservation and management actions. However, standardization of eDNA methods and reporting across the field is yet to be fully established, with one area being the calculation and interpretation of assay limit of detection (LOD) and limit of quantification (LOQ). Aims Here, we propose establishing consistent methods for determining and reporting of LOD and LOQ for single‐species quantitative PCR (qPCR) eDNA studies. Materials & Methods/ Results We utilize datasets from multiple cooperating laboratories to demonstrate both a discrete threshold approach and a curve‐fitting modeling approach for determining LODs and LOQs for eDNA qPCR assays. We also provide details of an R script developed and applied for the modeling method. Discussion/Conclusions Ultimately, standardization of how LOD and LOQ are determined, interpreted, and reported for eDNA assays will allow for more informed interpretation of assay results, more meaningful interlaboratory comparisons of experiments, and enhanced capacity for assessing the relative technical quality and performance of different eDNA qPCR assays.

Environmental DNA↗

USGS2019

Laboratory for Infectious Disease and the Environment (LIDE)

The Laboratory for Infectious Disease and the Environment (LIDE) studies the occurrence, fate and transport, and health effects of human and agricultural zoonotic pathogens in the environment. The LIDE is an interagency collaborative effort between the U.S. Geological Survey and the U.S. Department of Agriculture-Agricultural Research Service that conducts research to inform decision makers and advance scientific knowledge. The LIDE collaborates with public agencies and academic researchers in partnerships and works cooperatively or independently on all aspects of the research process. The LIDE's laboratory capabilities include quantitative polymerase chain reaction and pathogen culture.

Wisconsin↗

USGS2019

Cryptosporidium incidence and surface water inﬂuence of groundwater supplying public water systems in Minnesota, USA

Regulations for public water systems (PWS) in the U.S. consider Cryptosporidium a microbial contaminant of surface water supplies. Ground- water is assumed free of Cryptosporidium unless surface water is entering supply wells. We determined the incidence of Cryptosporidium in PWS wells varying in surface water inﬂuence. Community and noncommunity PWS wells (n = 145) were sampled (n = 964) and analyzed for Cryptosporidium by qPCR and immunoﬂuorescence assay (IFA). Surface water inﬂuence was assessed by stable isotopes and the expert judgment of hydrogeologists using site-speciﬁc data. Fifty-eight wells (40%) and 107 samples (11%) were Cryptosporidium- positive by qPCR, and of these samples 67 were positive by IFA. Cryptosporidium concentrations measured by qPCR and IFA were signiﬁcantly correlated (p < 0.001). Cryptosporidium incidence was not associated with surface water inﬂuence as assessed by stable isotopes or expert judgment. We successfully sequenced 45 of the 107 positive samples to identify species, including C. parvum (41), C. andersoni (2), and C. hominis (2), and the predominant subtype was C. parvum IIa A17G2R1. Assuming USA regulations for surface water-supplied PWS were applicable to the study wells, wells positive for Cryptosporidium by IFA would likely be required to add treatment. Cryptosporidium is not uncommon in groundwater, even when surface water inﬂuence is absent.

Minnesota↗

USGS2018

Human Bacteroides and total coliforms as indicators of recent combined sewer overflows and rain events in urban creeks

Combined sewer overflows (CSOs) are a known source of human fecal pollution and human pathogens in urban water bodies, which may present a significant public health threat. To monitor human fecal contamination in water, bacterial fecal indicator organisms (FIOs) are traditionally used. However, because FIOs are not specific to human sources and do not correlate with human pathogens, alternative fecal indicators detected using qPCR are becoming of interest to policymakers. For this reason, this study measured correlations between the number and duration of CSOs and mm of rainfall, concentrations of traditional FIOs and alternative indicators, and the presence of human pathogens in two urban creeks. Samples were collected May–July 2016 and analyzed for concentrations of FIOs (total coliforms and E . coli ) using membrane filtration as well as for three alternative fecal indicators (human Bacteroides HF183 marker, human polyomavirus (HPoV), pepper mild mottle virus (PMMoV)) and nine human pathogens using qPCR. Four of the nine pathogens analyzed were detected at these sites including adenovirus, Enterohemorrhagic E . coli , norovirus, and Salmonella . Among all indicators studied, human Bacteroides and total coliforms were significantly correlated with recent CSO and rainfall events, while E . coli, PMMoV, and HPoV did not show consistent significant correlations. Further, human Bacteroides were a more specific indicator, while total coliforms were a more sensitive indicator of CSO and rainfall events. Results may have implications for the use and interpretation of these indicators in future policy or monitoring programs.

Pennsylvania↗

USGS2017

Avian influenza virus RNA in groundwater wells supplying poultry farms affected by the 2015 influenza outbreak

During the 2015 outbreak of highly pathogenic avian influenza virus (HPAI) on poultry farms in the midwestern United States, concern was raised about the potential for HPAI to contaminate groundwater. Our study objective was to evaluate the occurrence of HPAI in the groundwater supply wells on 13 outbreak-affected poultry farms in Iowa and Wisconsin. We sampled 20 wells, six waste-storage lagoons, and one pond. Three wells and one lagoon were positive for the matrix gene indicative of influenza A virus. Using a semi-nested qPCR assay specific to the H5 HPAI outbreak strain, one well was H5-positive, matching the outbreak virus hemagglutinin gene. Matrix gene-positive samples analyzed for avian influenza virus (AIV) by cell culture and embryonating egg culture were negative. Seven wells were positive by PCR for a poultry-specific parvovirus, thus providing corroborating evidence of virus transport pathways between poultry fecal wastes and groundwater. Our data suggest it is possible for AIV to be transported to groundwater, and during an outbreak, the potential for poultry farm wells to become contaminated with AIV should be considered.

Iowa, Wisconsin↗

USGS2017

Quantitative microbial risk assessment for spray irrigation of dairy manure based on an empirical fate and transport model

BACKGROUND: Spray irrigation for land-applying livestock manure is increasing in the United States as farms become larger and economies of scale make manure irrigation aﬀordable. Human health risks from exposure to zoonotic pathogens aerosolized during manure irrigation are not well understood. OBJECTIVES: We aimed to a) estimate human health risks due to aerosolized zoonotic pathogens downwind of spray-irrigated dairy manure; and b) determine which factors (e.g., distance, weather conditions) have the greatest inﬂuence on risk estimates. METHODS: We sampled downwind air concentrations of manure-borne fecal indicators and zoonotic pathogens during 21 full-scale dairy manure irri- gation events at three farms. We ﬁt these data to hierarchical empirical models and used model outputs in a quantitative microbial risk assessment (QMRA) to estimate risk [probability of acute gastrointestinal illness (AGI)] for individuals exposed to spray-irrigated dairy manure containing Campylobacter jejuni, enterohemorrhagic Escherichia coli (EHEC), or Salmonella spp. RESULTS: Median risk estimates from Monte Carlo simulations ranged from 10−5 to 10−2 and decreased with distance from the source. Risk estimates for Salmonella or EHEC-related AGI were most sensitive to the assumed level of pathogen prevalence in dairy manure, while risk estimates for C. jejuni were not sensitive to any single variable. Airborne microbe concentrations were negatively associated with distance and positively associated with wind speed, both of which were retained in models as a signiﬁcant predictor more often than relative humidity, solar irradiation, or temperature. CONCLUSIONS: Our model-based estimates suggest that reducing pathogen prevalence and concentration in source manure would reduce the risk of AGI from exposure to manure irrigation, and that increasing the distance from irrigated manure (i.e., setbacks) and limiting irrigation to times of low wind speed may also reduce risk.

Environmental Health Perspectives↗

USGS2016

U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)

Introduction Through the Science Strategy for Highly Pathogenic Avian Influenza (HPAI) in Wildlife and the Environment, the USGS will assess avian influenza (AI) dynamics in an ecological context to inform decisions made by resource managers and policymakers from the local to national level. Through collection of unbiased scientific information on the ecology of AI viruses and wildlife hosts in a changing world, the U.S. Geological Survey (USGS) will enhance the development of AI forecasting tools and ensure this information is integrated with a quality decision process for managing HPAI. The overall goal of this USGS Science Strategy for HPAI in Wildlife and the Environment goes beyond documenting the occurrence and distribution of AI viruses in wild birds. The USGS aims to understand the epidemiological processes and environmental factors that influence HPAI distribution and describe the mechanisms of transmission between wild birds and poultry. USGS scientists developed a conceptual model describing the process linking HPAI dispersal in wild waterfowl to the outbreaks in poultry. This strategy focuses on five long-term science goals, which include: Science Goal 1—Augment the National HPAI Surveillance Plan; Science Goal 2—Determine mechanisms of HPAI disease spread in wildlife and the environment; Science Goal 3—Characterize HPAI viruses circulating in wildlife; Science Goal 4—Understand implications of avian ecology on HPAI spread; and Science Goal 5—Develop HPAI forecasting and decision-making tools. These goals will help define and describe the processes outlined in the conceptual model with the ultimate goal of facilitating biosecurity and minimizing transfer of diseases across the wildlife-poultry interface. The first four science goals are focused on scientific discovery and the fifth goal is application-based. Decision analyses in the fifth goal will guide prioritization of proposed actions in the first four goals.

Open-File Report↗

USGS2016

Determining the 95% limit of detection for waterborne pathogen analyses from primary concentration to qPCR

The limit of detection (LOD) for qPCR-based analyses is not consistently defined or determined in studies on waterborne pathogens. Moreover, the LODs reported often reflect the qPCR assay alone rather than the entire sample process. Our objective was to develop an approach to determine the 95% LOD (lowest concentration at which 95% of positive samples are detected) for the entire process of waterborne pathogen detection. We began by spiking the lowest concentration that was consistently positive at the qPCR step (based on its standard curve) into each procedural step working backwards (i.e., extraction, secondary concentration, primary concentration), which established a concentration that was detectable following losses of the pathogen from processing. Using the fraction of positive replicates (n = 10) at this concentration, we selected and analyzed a second, and then third, concentration. If the fraction of positive replicates equaled 1 or 0 for two concentrations, we selected another. We calculated the LOD using probit analysis. To demonstrate our approach we determined the 95% LOD for Salmonella enterica serovar Typhimurium, adenovirus 41, and vaccine-derived poliovirus Sabin 3, which were 11, 12, and 6 genomic copies (gc) per reaction (rxn), respectively (equivalent to 1.3, 1.5, and 4.0 gc L −1 assuming the 1500 L tap-water sample volume prescribed in EPA Method 1615). This approach limited the number of analyses required and was amenable to testing multiple genetic targets simultaneously (i.e., spiking a single sample with multiple microorganisms). An LOD determined this way can facilitate study design, guide the number of required technical replicates, aid method evaluation, and inform data interpretation.

Water Research↗