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1.
J Environ Qual ; 45(2): 666-74, 2016 Mar.
Article in English | MEDLINE | ID: mdl-27065414

ABSTRACT

Production of both livestock and food crops are central priorities of agriculture; however, food safety concerns arise where these practices intersect. In this study, we investigated the public health risks associated with potential bioaerosol deposition to crops grown in the vicinity of manure application sites. A field sampling campaign at dairy manure application sites supported the emission, transport, and deposition modeling of bioaerosols emitted from these lands following application activities. Results were coupled with a quantitative microbial risk assessment model to estimate the infection risk due to consumption of leafy green vegetable crops grown at various distances downwind from the application area. Inactivation of pathogens ( spp., spp., and O157:H7) on both the manure-amended field and on crops was considered to determine the maximum loading of pathogens to plants with time following application. Overall median one-time infection risks at the time of maximum loading decreased from 1:1300 at 0 m directly downwind from the field to 1:6700 at 100 m and 1:92,000 at 1000 m; peak risks (95th percentiles) were considerably greater (1:18, 1:89, and 1:1200, respectively). Median risk was below 1:10,000 at >160 m downwind. As such, it is recommended that a 160-m setback distance is provided between manure application and nearby leafy green crop production. Additional distance or delay before harvest will provide further protection of public health.


Subject(s)
Crops, Agricultural , Manure , Public Health , Agriculture , Humans , Risk Assessment , Soil Microbiology
2.
Environ Sci Technol ; 49(16): 9842-9, 2015 Aug 18.
Article in English | MEDLINE | ID: mdl-26158489

ABSTRACT

In this study, we report the human health risk of gastrointestinal infection associated with inhalation exposure to airborne zoonotic pathogens emitted following application of dairy cattle manure to land. Inverse dispersion modeling with the USEPA's AERMOD dispersion model was used to determine bioaerosol emission rates based on edge-of-field bioaerosol and source material samples analyzed by real-time quantitative polymerase chain reaction (qPCR). Bioaerosol emissions and transport simulated with AERMOD, previously reported viable manure pathogen contents, relevant exposure pathways, and pathogen-specific dose-response relationships were then used to estimate potential downwind risks with a quantitative microbial risk assessment (QMRA) approach. Median 8-h infection risks decreased exponentially with distance from a median of 1:2700 at edge-of-field to 1:13 000 at 100 m and 1:200 000 at 1000 m; peak risks were considerably greater (1:33, 1:170, and 1:2500, respectively). These results indicate that bioaerosols emitted from manure application sites following manure application may present significant public health risks to downwind receptors. Manure management practices should consider improved controls for bioaerosols in order to reduce the risk of disease transmission.


Subject(s)
Aerosols/analysis , Air Pollutants/analysis , Bacteria/isolation & purification , Manure/analysis , Public Health , Risk Assessment , Animals , Cattle , Dairying , Humans , Models, Theoretical , New York
3.
Environ Monit Assess ; 187(1): 4168, 2015 Jan.
Article in English | MEDLINE | ID: mdl-25504186

ABSTRACT

Forty-two percent of Escherichia coli and 58% of Enterococcus spp. isolated from cattle feedlot runoff and associated infiltration basin and constructed wetland treatment system were resistant to at least one antibiotic of clinical importance; a high level of multidrug resistance (22% of E. coli and 37% of Enterococcus spp.) was observed. Hierarchical clustering revealed a closely associated resistance cluster among drug-resistant E. coli isolates that included cephalosporins (ceftiofur, cefoxitin, and ceftriaxone), aminoglycosides (gentamycin, kanamycin, and amikacin), and quinolone nalidixic acid; antibiotics from these classes were used at the study site, and cross-resistance may be associated with transferrable multiple-resistance elements. For Enterococcus spp., co-resistance among vancomycin, linezolid, and daptomycin was common; these antibiotics are reserved for complicated clinical infections and have not been approved for animal use. Vancomycin resistance (n = 49) only occurred when isolates were resistant to linezolid, daptomycin, and all four of the MLSB (macrolide-lincosamide-streptogramin B) antibiotics tested (tylosin, erythromycin, lincomycin, and quinipristin/dalfopristin). This suggests that developing co-resistance to MLSB antibiotics along with cyclic lipopeptides and oxazolidinones may result in resistance to vancomycin as well. Effects of the treatment system on antibiotic resistance were pronounced during periods of no rainfall and low flow (long residence time). Increased hydraulic loading (short residence time) under the influence of rain caused antibiotic-resistant bacteria to be flushed through the treatment system. This presents concern for environmental discharge of multidrug-resistant organisms relevant to public health.


Subject(s)
Drug Resistance, Bacterial/physiology , Enterococcus/growth & development , Escherichia coli/growth & development , Waste Disposal, Fluid , Wastewater/microbiology , Animal Husbandry , Animals , Bacteria/drug effects , Cattle , Enterococcus/classification , Enterococcus/isolation & purification , Environmental Monitoring , Escherichia coli/classification , Escherichia coli/isolation & purification , Microbial Sensitivity Tests
4.
Biometrics ; 65(2): 341-52, 2009 Jun.
Article in English | MEDLINE | ID: mdl-18537949

ABSTRACT

SUMMARY: A new methodology is proposed for clustering datasets in the presence of scattered observations. Scattered observations are defined as unlike any other, so traditional approaches that force them into groups can lead to erroneous conclusions. Our suggested approach is a scheme which, under assumption of homogeneous spherical clusters, iteratively builds cores around their centers and groups points within each core while identifying points outside as scatter. In the absence of scatter, the algorithm reduces to k-means. We also provide methodology to initialize the algorithm and to estimate the number of clusters in the dataset. Results in experimental situations show excellent performance, especially when clusters are elliptically symmetric. The methodology is applied to the analysis of the United States Environmental Protection Agency's Toxic Release Inventory reports on industrial releases of mercury for the year 2000.


Subject(s)
Algorithms , Biometry/methods , Cluster Analysis , Data Interpretation, Statistical , Epidemiologic Research Design , Proportional Hazards Models , Risk Assessment/methods , Computer Simulation , Pattern Recognition, Automated , Reproducibility of Results , Sensitivity and Specificity
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