Advances in Microbial Advances in Microbial Risks Toward Enhancing Risks Toward Enhancing Water Supply Security Water Supply Security

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13 Νοε 2013 (πριν από 3 χρόνια και 8 μήνες)

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Advances in Microbial
Advances in Microbial
Risks Toward Enhancing
Risks Toward Enhancing
Water Supply Security
Water Supply Security
Tomoyuki Shibata, Ph.D., M.Sc
Tomoyuki Shibata, Ph.D., M.Sc
Center for Advancing Microbial Risk
Center for Advancing Microbial Risk
Assessment, Michigan State University
Assessment, Michigan State University
Home Land
Home Land
Security Issues
Security Issues


BioWatch
BioWatch


Outdoor air
Outdoor air


Indoor air
Indoor air
< 36h
Home Land
Home Land
Security Issues
Security Issues
Need
smart
sensor
Structural Security
Home Land
Home Land
Security Issues
Security Issues

Water Quality:

Biological agents

Harmful concentrations

Real-time monitoring

Response Plans:

TestingCommunication Remediation.
What is Risk in Water Security
What is Risk in Water Security

Risk is the likelihood of (identified?) hazards causing
harm in exposed populations in a specified time frame
including the severity of the consequences.


exposure* hazard
exposure* hazard
chance*hazard*exposure*consequence
chance*hazard*exposure*consequence


EPA has suggested that 1/10,000 infection annually is
EPA has suggested that 1/10,000 infection annually is
an appropriate level of safety for drinking water.
an appropriate level of safety for drinking water.


What is an acceptable risk of fatality caused by a bioterrorism
What is an acceptable risk of fatality caused by a bioterrorism
attack?
attack?
Contents: Methodology for Risk
Contents: Methodology for Risk
Assessment (NAS)
Assessment (NAS)


Quantitative Microbial Risk Assessment (QMRA)
Quantitative Microbial Risk Assessment (QMRA)


Hazard Identification
Hazard Identification


Biological Agent Concern (BAC)
Biological Agent Concern (BAC)


Dose
Dose
-
-
Response Assessment
Response Assessment


Species
Species


Age
Age


Exposure Assessment
Exposure Assessment


New Monitoring Tools
New Monitoring Tools


Water Distribution Transportation Model
Water Distribution Transportation Model


Risk Characterization & Management
Risk Characterization & Management


Summary
Summary
Hazard Identification
Hazard Identification
What is Bioterrorism?
What is Bioterrorism?


A bioterrorism attack is the intentional release of
A bioterrorism attack is the intentional release of
viruses, bacteria, or other germs (agents) used to cause
viruses, bacteria, or other germs (agents) used to cause
illness or death in people
illness or death in people


Biological agents can be spread through the air, through
Biological agents can be spread through the air, through
water, or in food. Terrorists may use biological agents
water, or in food. Terrorists may use biological agents
because they can be extremely difficult to detect and do
because they can be extremely difficult to detect and do
not cause illness for several hours to several days.
not cause illness for several hours to several days.


Some bioterrorism agents, e.g. smallpox virus, can be spread
Some bioterrorism agents, e.g. smallpox virus, can be spread
from person to person
from person to person


Some, e.g. anthrax, can not.
Some, e.g. anthrax, can not.
Bioterrorism Agent
Bioterrorism Agent
Category A
Category A


Easily spread or transmitted from person to person
Easily spread or transmitted from person to person


High death rates
High death rates


Public panic and social disruption
Public panic and social disruption


Special action for public health preparedness
Special action for public health preparedness


Anthrax (
Anthrax (
Bacillus
Bacillus
anthracis
anthracis
)
)


Botulism
Botulism
(
(
Clostridium
Clostridium
botulinum
botulinum
toxin)
toxin)


Plague
Plague
(
(
Yersinia
Yersinia
pestis
pestis
)
)


Smallpox (
Smallpox (
Variola
Variola
major)
major)


Tularemia
Tularemia
(
(
Francisella
Francisella
tularensis
tularensis
)
)


Viral hemorrhagic fevers,
Viral hemorrhagic fevers,


e.g. Lassa, Dengue, Ebola
e.g. Lassa, Dengue, Ebola
B. anthracis
Bioterrorism Agent
Bioterrorism Agent
Category B
Category B


Moderately easy to spread
Moderately easy to spread


Moderate illness rates and low death dates
Moderate illness rates and low death dates


Enhancements of CDC’s lab capacity and disease
Enhancements of CDC’s lab capacity and disease
monitoring
monitoring


Brucellosis (
Brucellosis (Brucella
Brucella
species)
species)


Epsilon toxin of
Epsilon toxin of
Clostridium perfringens
Clostridium perfringens


Glanders
Glanders
(
(
Burkholderia
Burkholderia
mallei
mallei
)
)


Melioidosis
Melioidosis
(
(
Burkholderia
Burkholderia
pseudomallei
pseudomallei
)
)


Psittacosis (
Psittacosis (
Chlamydia
Chlamydia
psittaci
psittaci
)
)


Q fever (
Q fever (
Coxiella
Coxiella
burnetii
burnetii)
)


Ricin
Ricin
toxin from
toxin from
Ricinus
Ricinus
communis
communis
(castor beans)
(castor beans)


Staphylococcal
Staphylococcal
enterotoxin
enterotoxin
B
B


Typhus fever (
Typhus fever (
Rickettsia
Rickettsi
a
prowazekii
prowazekii
)
)


Viral encephalitis (
Viral encephalitis (
alphaviruses
alphaviruses
[e.g., Venezuelan equine encephalitis,
[e.g., Venezuelan equine encephalitis,
eastern equine encephalitis, western equine encephalitis])
eastern equine encephalitis, western equine encephalitis])
Bioterrorism Agent
Bioterrorism Agent
Category B
Category B


Food safety threats
Food safety threats


e.g.,
e.g.,
Salmonella
Salmonella
species,
species,
Escherichia coli
Escherichia coli
O157:H7,
O157:H7, Shigella
Shigella
)
)


Water safety threats
Water safety threats


e.g.,
e.g.,
Vibrio
Vibrio
cholerae
cholerae
,
, Cryptosporidium
Cryptosporidium
parvum
parvum
)
)
Bioterrorism Agent
Bioterrorism Agent
Category C
Category C


Emerging pathogens that could be engineered for mass
Emerging pathogens that could be engineered for mass
spread in the future
spread in the future


Easily available
Easily available


Easily produced and spread
Easily produced and spread


Potential for high mobility and mortality
Potential for high mobility and mortality


Nipah
Nipah
virus
virus


Hantavirus
Hantavirus


Severe acute respiratory syndrome
Severe acute respiratory syndrome
-
-
associated
associated
coronavirus
coronavirus
(SARS
(SARS
-
-
CoV
CoV
)
)


Influenza
Influenza


Multi
Multi
-
-
drug resistant TB
drug resistant TB
Bioterrorism Agent
Bioterrorism Agent
Category C
Category C
Tools for Hazard ID for Water
Tools for Hazard ID for Water


New microbial contaminants in water have been
New microbial contaminants in water have been
identified as a risk for waterborne disease. Known as
identified as a risk for waterborne disease. Known as
the Contaminant Candidate List (CCL), these
the Contaminant Candidate List (CCL), these
microorganisms will be addressed based on health
microorganisms will be addressed based on health
impacts and occurrence in water.
impacts and occurrence in water.


Molecular tools are providing insight into
Molecular tools are providing insight into
characterization and detection of both new pathogens
characterization and detection of both new pathogens
(CCL e.g.
(CCL e.g.
Helicobacter
Helicobacter
) and our classical pathogens (e.g.
) and our classical pathogens (e.g.
Cryptosporidium
Cryptosporidium
).
).
Microarrays
Microarrays

Chip platform with synthesized genetic
sequences

Hybridization detection

Multiple pathogens
Dr. Syed Hashsham
Michigan State University
Dose
Dose
-
-
Response Assessment
Response Assessment
Dose
Responses
Probability of Infection
Best Fit Models
Best Fit Models


Exponential Model
Exponential Model


Beta
Beta
-
-
Poisson Model
Poisson Model


Major Waterborne Pathogens
Major Waterborne Pathogens


Haas et al. 1999. Quantitative Microbial Risk Assessment
Haas et al. 1999. Quantitative Microbial Risk Assessment
()
doseexp1PI×−−=r
(
)
doseexp1Pi
×

−=r
()
α
α







−+−=12
N
dose
11Pi
1
50
Waterborne Pathogens
Waterborne Pathogens
0%
110100100010000100000
Dose (# of microorganisms ingested), d
Risk of infection, P
i
(d)
Rotavirus
Hepatitis A
A
denovirus 4
Vibrio cholera
Coxackie
Giardia
Campylobactor
Echovirus
Polio
Shigella
Crypt
Salmonella
E. coli
99.99%
Building Dose
Building Dose
-
-
Response Models
Response Models


Determining the applicability of previously used
Determining the applicability of previously used
dose
dose
-
-
response models to the
response models to the
Category A
Category A
bioterrorist agents
bioterrorist agents
via the oral, inhalation and
via the oral, inhalation and
dermal routes.
dermal routes.


Assessing the validity of animal to human
Assessing the validity of animal to human
extrapolation of dose
extrapolation of dose
-
-
response.
response.


Assessing the influence of modifying factors
Assessing the influence of modifying factors
(e.g., host age) on dose
(e.g., host age) on dose
-
-
response.
response.
Anthrax: Dose
Anthrax: Dose
-
-
Response (fatal)
Response (fatal)
Rhesus Monkeys Pooled with Guinea Pigs
Dr. Charles Haas,
Drexel University
Variety of animal
data sets can be
combined
Probability model: Risk of Mortality =
()
974.0
974.01
12
62817
dose
11







−+−
Probabilistic Risk of Mortality
Smallpox: Dose
Smallpox: Dose
-
-
Response
Response
Lower Median infectivity
For the Young
Dr. Charles Haas,
Drexel University
Exposure Assessment
Exposure Assessment
Factors Important in
Factors Important in
Assessing Exposure
Assessing Exposure


Route of Exposures
Route of Exposures


Oral, Inhalation, Dermal
Oral, Inhalation, Dermal


Degree of exposures
Degree of exposures


Liters of water ingested
Liters of water ingested


Number of exposures
Number of exposures


How many times in a day, month, year
How many times in a day, month, year


Concentrations
Concentrations


Spatial and Temporal Variations
Spatial and Temporal Variations


Fate & Transport
Fate & Transport
Exposure Assessment
Exposure Assessment
and Risk Characterization
and Risk Characterization


Exposure and levels of contamination are the most
Exposure and levels of contamination are the most
important aspect for providing input to risk
important aspect for providing input to risk
characterization.
characterization.


Need
Need
new methods
new methods
for better assessment of non
for better assessment of non
-
-
cultivatible
cultivatible
viruses, parasites and bacteria.
viruses, parasites and bacteria.


Need better monitoring data, better
Need better monitoring data, better
transport
transport
models
models
.
.


Essential for Good Risk Management Decisions
Essential for Good Risk Management Decisions
What if…
What if…
contaminants
contaminants
Fire
Fire
Hydrant
Hydrant
without backflow
without backflow
p
revention devices
p
revention devices
Water Distribution
Water Distribution
Transportation Model
Transportation Model
Serious Engineering
Serious Engineering
and Sensor Research
and Sensor Research
EPA Lab in Cincinnati
EPA Lab in Cincinnati
EPANET
EPANET
EPANET models the hydraulic and water quality
behavior of water distribution piping systems.
EPANET is a ‘free & open source’
Windows
program written in C & Delphi programming
languages that performs extended period
simulation of hydraulic and water-quality
behavior within pressurized pipe networks. A
network can consist of pipes, nodes (pipe
junctions), pumps, valves and storage tanks or
reservoirs.
3D Control
Volume
1D Control Volume
1D Control Volume
2D Control
Volume
Contaminated Water (C = 1)
Contaminated Water (C = 1)
Un
Un
-
-
contaminated
contaminated
Water (C = 0)
Water (C = 0)
C = 0.5?
C = 0.5?
C = 0.5?
C = 0.5?
Perfect Mixing Assumption
Perfect Mixing Assumption
Contaminated Water (C = 1)
Contaminated Water (C = 1)
Un
Un
-
-
contaminated
contaminated
Water (C = 0)
Water (C = 0)
C
C
= 0.85
= 0.85
C = 0.15
Courtesy of Sandia
National Laboratories
Perfect Mixing Assumption
Perfect Mixing Assumption
Improving Transport Model
Improving Transport Model
(EPANET)
(EPANET)
Dr. Christopher Choi
University of Arizona
t
t
t
D
Sc
ρ
μ
=
Water Distribution Systems
Water Distribution Systems
Laboratory
Laboratory
Test bed for Bio
Test bed for Bio
-
-
Sensors
Sensors
and Event Monitors
and Event Monitors
Mixing patterns
Mixing patterns
along the interface
along the interface
a) Velocity vectors and b) Dimensionless NaCl Concentration contours at a
cross junction, when ReS= ReW= ReE= ReN= 44,000 (ReS/W = 1, ReE/N=1),
and Sct= 0.1875
Updating Model
Updating Model
Current
Current
WDS
WDS
Model
Model
Improved
Improved
WDS
WDS
Model
Model
Risk Characterization
Risk Characterization
& Management
& Management
Risk Assessment Framework
Risk Assessment Framework
Hazard
Identification
Risk
Characterization
Dose Response
Exposure
Assessment
literature dose-
response function
specific exposures in
the scenario of
concern
Plug exposure
into the dose-
response
function
Point Estimate
Point Estimate


Single numeric value of risk
Single numeric value of risk


May correspond to best estimate of risk
May correspond to best estimate of risk


May be maximum reasonable exposure
May be maximum reasonable exposure


Use parameter values of exposure and dose response
Use parameter values of exposure and dose response
parameters corresponding to point estimate of interest
parameters corresponding to point estimate of interest
Example: Anthrax attack in water
Example: Anthrax attack in water


What is the risk of Anthrax attack?
What is the risk of Anthrax attack?


Best fit dose
Best fit dose
-
-
response is Beta
response is Beta
-
-
Poisson model
Poisson model


If drinking water contains
If drinking water contains
B.
B.
anthracis
anthracis
1 spore
1 spore
/L
/L


if 1 L of water is ingested, the fatality risk = 1.6 x 10
if 1 L of water is ingested, the fatality risk = 1.6 x 10
-
-
5
5


1 person/population of Lansing (120,000)
1 person/population of Lansing (120,000)
Note: this is the fatality risk via inhalation based on animal t
Note: this is the fatality risk via inhalation based on animal t
ests
ests
()
974.0
974.01
12
62817
dose
11)(







−+−=fatalP
Poisson(10)

0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
-2
0
2
4
6
8
10
12
14
16
18
20
>5.0%5.0%90.0%
5.0015.00
This was our
point estimate
Now it is
our most
likely
value, but
not the
only
possible
value
Uncertainty Analysis
Uncertainty Analysis


Monte
Monte
-
-
Carlo Simulation
Carlo Simulation


Find range of possible outcomes
Find range of possible outcomes


Determine if the uncertainty matters
Determine if the uncertainty matters


Determine which inputs contribute the most to output
Determine which inputs contribute the most to output
uncertainty
uncertainty


Compare range of outcomes under different decisions,
Compare range of outcomes under different decisions,
policies
policies
Risk Characterization
Risk Characterization


What do we really want to get out of our analysis?
What do we really want to get out of our analysis?


Not just a number but to inform multiple decisions
Not just a number but to inform multiple decisions


What is acceptable risk?
What is acceptable risk?


EPA dirking water 1/10000 infection
EPA dirking water 1/10000 infection


What is an acceptable
What is an acceptable
risk of fatality
risk of fatality
caused by a
caused by a
bioterrorism attack
bioterrorism attack
?
?


How bad could it be?
How bad could it be?


Can the risk be reduced?
Can the risk be reduced?


What do we need to know to improve management of this
What do we need to know to improve management of this
risk?
risk?


Are there subpopulations we should be concerned about?
Are there subpopulations we should be concerned about?
Informing Risk Management
Informing Risk Management


What protective action is needed to reduce
What protective action is needed to reduce


best estimate of risk to a target value?
best estimate of risk to a target value?


upper bound of risk to the target value?
upper bound of risk to the target value?


How much will different risk management actions cost
How much will different risk management actions cost
and what risk reductions will they achieve?
and what risk reductions will they achieve?


How certain are we?
How certain are we?
Relative Risks Associated with
Chlorinated Water
Health Outcomes
Survival
Anthrax
Norwalk
Crypto
E.coli
0157
E.coli
Current Microbial
Current Microbial
Drinking Water Standard
Drinking Water Standard


Total
Total
coliforms
coliforms


including fecal coliform and
including fecal coliform and
E. coli
E. coli


Heterotrophic plate count
Heterotrophic plate count


Cryptosporidium
Cryptosporidium


Giardia
Giardia
lamblia
lamblia


Legionella
Legionella


Viruses (enteric)
Viruses (enteric)


Turbidity
Turbidity
EPA's Surface Water
EPA's Surface Water
Treatment Rules
Treatment Rules


Cryptosporidium
Cryptosporidium
: 99% removal.
: 99% removal.


Giardia
Giardia
lamblia
lamblia
: 99.9% removal/inactivation
: 99.9% removal/inactivation


Viruses: 99.99% removal/inactivation
Viruses: 99.99% removal/inactivation
Summary & Conclusion
Summary & Conclusion


QMRA for decision making
QMRA for decision making


Better monitoring systems and water
Better monitoring systems and water
distribution model
distribution model


Update treatment systems
Update treatment systems


Water
Water
BioWatch
BioWatch


Communication
Communication
Center for Advancing Microbial
Center for Advancing Microbial
Risk Assessment (CAMRA)
Risk Assessment (CAMRA)


U.S. EPA and Dept of Homeland Security
U.S. EPA and Dept of Homeland Security


Established in 2005
Established in 2005


7 Universities
7 Universities


Michigan State University, Drexel University, University
Michigan State University, Drexel University, University
of Arizona, Northern Arizona University,
of Arizona, Northern Arizona University,
University of Michigan, Carnegie Mellon University,
University of Michigan, Carnegie Mellon University,
University of California Berkeley
University of California Berkeley


Interdisciplinary Researchers
Interdisciplinary Researchers


Microbiologists, Environmental Engineers,
Microbiologists, Environmental Engineers,
Epidemiologists, Veterinarians, Information Technologists
Epidemiologists, Veterinarians, Information Technologists
CAMRA’s
CAMRA’s
Missions
Missions

Develop models, tools and information that will be
used in a credible risk assessment framework to reduce
or eliminate health impacts from deliberate use of
biological agents of concern (BAC) in the indoor and
outdoor environment

Build a national network for microbial risk knowledge
management, learning and transfer, for the community
of scientists, and students via educational programs and
community of professionals in the field and in our
communities.
Thank you
Thank you
Tomoyuki Shibata, Ph.D., M.Sc
Tomoyuki Shibata, Ph.D., M.Sc
e
e
-
-
mail:
mail:
tshibata@msu.edu
tshibata@msu.edu
CAMRA homepage
CAMRA homepage
:
:
www.camra.msu.edu
www.camra.msu.edu