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Transcript of MEASURING THE POTENTIAL IMPACTS OF THE …Transport an re an re Food Water Land an re Product...
MEASURING THE POTENTIAL
IMPACTS OF THE UNINTENTIONAL
CONSEQUENCES
Jade Mitchell, PhD
Center for Research on Ingredient Safety (CRIS) Annual Meeting - October 5, 2016
East Lansing Marriot at University Place
R.A.M.A.D.A.
RISK ASSESSMENT MODELING AND DECISION ANALYSIS
Jade Mitchell, PhD
Principal Investigator
www.theramadagroup.com
We perform human health risk analysis to address risks associated with chemical
and microbial stressors in multimedia environments.
Our goal is to increase the utility of risk analysis for decision making and effective
management of legacy and emerging contaminants.
We develop approaches, frameworks, models and data sets to support risk
characterization of poorly described hazards and exposures.
Prescriptive
Predictive
Descriptive
Approaches
Sense -making
Solution - making
Decision - making
Data collection and analysis
Modeling and simulation
Mechanistic systems modeling
o Systems Modeling
Conceptual
Statistical
Environmental and process
o Risk Analysis
o Decision Analysis
o Value of Information
o Multi-criteria Decision
analysis
o Decision Making Under
Uncertainty
o Sensitivity Analysis
o Uncertainty Analysis
o Life-Cycle Assessment
General Research ApproachesResource
Needs and
Complexity of
Effort
Residual
Uncertainty
Fully mechanistic systems
modeling and risk analysis
Predictive, generalizable
and simulation based modeling
Screening based on inherent
chemical, physical and/biological
processes
SOURCE: http://web.bryant.edu/~dlm1/sc372/readings/toxicology/toxicology.htm Dan L. McNally, Associate Professor,
Department of Science and Technology, Bryant University, Smithfield, RI
• Chemical and microbial stressors
exists among and across multiple
sectors
• Many are interrelated
• Identifying and characterizing
relevant exposure pathways
• Integrating risk into decision
frameworks
Applications
“Origins and Fate of PPCPs” Illustration by C.G. Daughton, U.S. EPA, NERL, Las Vegas, NV, February 2001 (revised March 2006); Source:
http://www.epa.gov/ppcp/basic2.html
Applications
Consumer Products
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Release
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Air
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Soil
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Air
Food
ChemicalManufacture
ChemicalTransportation
Production/Formulation
WorkplaceExposure
EnvironmentalRelease
EnvironmentalDisposal
Air
Water
Incineration
RecyclingSewage
Treatment
Food
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Transport
HumanExposure
HumanExposure
Food
Water
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HumanExposureProductDisposal
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Soil
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Air
Food
ChemicalManufacture
ChemicalTransportation
Production/Formulation
WorkplaceExposure
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Air
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Incineration
RecyclingSewage
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Food
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HumanExposure
Food
Water
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RELEASE FATE / TRANSPORT CONCENTRATION ACTIVITY EXPOSURE
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Release
Reaction
ProductUse
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Population
Market Share
Location
FrequencyTiming
Population
Market Share
Water
Outdoor
Air
Surface
Dust
A C
T I
V I
T I
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Soil
Indoor
Air
Food
ChemicalManufacture
ChemicalTransportation
Production/Formulation
WorkplaceExposure
EnvironmentalRelease
EnvironmentalDisposal
Air
Water
Incineration
RecyclingSewage
Treatment
Food
A C
T I
V I
T I
E S
Land
Transport
HumanExposure
HumanExposure
Food
Water
Land
HumanExposureProductDisposal
Air
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RELEASE FATE / TRANSPORT CONCENTRATION ACTIVITY EXPOSURE
EnvironmentalRelease
Exposure-based prioritization
• Focuses on chemicals (or byproducts) intentionally manufactured for commercial use
• Understanding the intersection of inherent properties, purpose, form and use.
• Identifying high-throughput methods and models to estimate exposure potential
Antibiotic Resistance
■ The World Health Organization cites antibiotic resistance as one of the most critical health challenges of the next century.
■ Antibiotic use plays a major role in the emerging public health crisis of antibiotic resistance.
– Majority of antibiotic use in the United States occurs in agricultural settings,
– Relatively little research regarding how antibiotic use in farm animals contributes to the overall problem of antibiotic resistance.
■ Use of antibiotics and discharge into the environment may encourage horizontal gene transfer to human commensal gut bacteria and/or pathogens
Risk assessment models across food safety pathway
HGT ???
Multi-criteria Decision Analysis for Antibiotic Usage
•Properties
•Withdrawal periods
•Degradation rates
•Bioavailability
•Disposal
•Irrigation
•Treatment
•Associated disease prevalence
•Regional population analysis
•Production
•Availability
•Indications
•Administration
Usage Excretion
FatePractices
LINKING ANTIBIOTIC USAGE ON DAIRY FARMSTO PROLIFERATION OF ANTIMICROBIAL
RESISTANCE
Objectives
Evaluates the usage of a β-lactam antibiotic (Cephalosporin) at the Kellogg Biological Station (KBS) Pasture Dairy
■ To investigate the fate and transport of antimicrobial resistance in agricultural lands.
■ To determine the effects of manure management practices on the delivery of antimicrobial resistance in the environment.
■ To identify the conditions promoting the transport of antimicrobialresistant genes to environment.
■ To monitor temporal and spatial variations in the abundance of antimicrobal resistant genes in manure, soil, and groundwater.
■ To identify the correlations in the co-occurrence of clusters of identical antimicrobial resistance genes in impacted soils and groundwater.
Kellogg Biological Station
The W.K. Kellogg Biological Station is Michigan State University’s largest off-campus education complex close to
Kalamazoo in south west Michigan.
Manure application methods at KBS farms
■ Slurry surface application
■ Compost surface application
■ Bed-pack surface application
KBS
■ KBS Pasture Dairy primarily administered ceftiofur, a β-lactam antibiotic (a class of cephalosporins deemed critically important in human medicine) to treat mastitis and foot rot.
■ The use of ceftiofur antibiotics at the KBS Dairy did require a blanket veterinary prescription, however, individual treatment decisions were made by lay farm workers in accordance with manufacturer’s guidelines.
■ Other antimicrobials intermittently administered at the dairy include tulathromycin for respiratory infection and oxyteracyclinefor conjunctivitis.
■ The herd, consisting of approximately 160 milking-age cows, was predominantly maintained on rotationally grazed pastures from April-November, with access to the barn, and then housed exclusively in the barn during winter months.
Sampling
■ Animal feces
■ Several wells nearby
■ Animal feed and drinking water before animal contact
■ Animal feed and drinking water after animal contact
■ Lakes nearby
■ Manure compost
■ Slurry
■ Animals drinking water
■ Soils at three depths in fields where manure in slurry, compost, and bed-pack forms were applied last year
■ Soils at three depths in fields where manure in slurry, compost, and bed-pack forms were applied an hour before sampling
Proportion of positive qPCR assays to total assay (%)
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Stagnat slurry Compost Agitated lagoon Beded-pack Feces
Proportion of positive assays in slurry, compost, bed-pack and cow feces
Proportion of positive assays in water samples
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Potable water from a well adjacent to the dairy barn
Non-potable (for human) water from cistern
Water from where cows drink
Prairieville Creek
Well beside Field 508
Duck Lake
Future Work
■ Studying the physical, chemical, and microbiological processes affecting the fate and transport of antimicrobial resistance in dairy farms.
■ Modelling the fate and transport of antimicrobial resistance in the farm environment.
■ Studying the mitigation strategies associated with antimicrobial resistance from agricultural lands through risk-based manure management strategies.
Acknowledgements
■ Dr. Sina Akram
■ Dr. Robert Stedtfeld
■ Alexandre Chabrelie, BAE Graduate Student
■ Center for Health Impacts of Agriculture