integrated assessment of emerging zoonotic diseases presented at: cfiaphac joint workshop on...
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Integrated Assessment of
Emerging Zoonotic Diseases
Presented at: CFIAPHAC Joint Workshop on Integrated Analysis of non-Foodborne Zoonotic Risk
January 12th 2010
Hadi Dowlatabadi
Jan 12th 2010, Ottawa 2
Overview
• What is an IA?
• A process for creating one
• Examples
• Next steps
Jan 12th 2010, Ottawa 3
The Whole & its Parts
• When the world around us gets too complicated “as a whole” we try to divide it up into sensible “parts”.
– This helps us understand details of parts better.
– But it also encourages working only within boundaries. Losing sight of issues that could cross one or many boundaries.
• IA is about understanding the whole of a cross-cutting issue boundaries will be crossed.
Jan 12th 2010, Ottawa 4
A definition of IA
• Bridging the gap between social and natural sciences and communication of key issues with stakeholders and decision-makers.
• The goal here is to coordinate horizon scanning activities of agencies serving different stakeholders to maximize successful risk management.
Col
lect
ive
deci
sion
-mak
ing
Agency
Limited detection
Imperfect knowledge
Values that change with contexts/time
Blunt mechanisms for realizing goals
...we perceive changes in our system,
... identify their origin & project trends/consequences,
...evaluate various options,
...implement achosen strategy,
Evaluation & Feedback
Human
Jan 12th 2010, Ottawa 6
Applications of IA
• 70s & 80s
– SST, CFCs, Acid Rain
• 90s
– Climate change
– Cryptosporidiosis
– Dengue
• 00s
– Hydatid disease in Katmandu
– Malaria in various regions of the world
Jan 12th 2010, Ottawa 7
IA of Climate Change• Demographics
• Economics
• Social dynamics
• Land use
• Emissions
• Atmospheric physics and Chemistry (GHGs and aerosols)
• Cloud physics
• Climatology• Volcanology
• Solar system physics
• Oceanography
• Hydrology
• Coastal zone dynamics
• Ecosystem dynamics
• Agriculture and forestry
• Zoonotic and other environmental diseases
• Human security
• Insurance
• Law
• Politics
• Psychology
• Ethics
• Other drivers of global change
• Demographics
• Economics• Social dynamics
• Land use
• Emissions
• Atmospheric physics and Chemistry (GHGs and aerosols)
• Cloud physics
• Climatology
• Volcanology
• Solar system physics
• Oceanography
• Hydrology
• Coastal zone dynamics
• Ecosystem dynamics
• Agriculture and forestry
• Zoonotic and other environmental diseases
• Human security
• Insurance
• Law
• Politics
• Psychology
• Ethics
• Other drivers of global change
Jan 12th 2010, Ottawa 8
IA of Climate ChangeEQUAL EMPHASIS• Demographics
• Economics
• Social dynamics
• Land use
• Emissions
• Atmospheric physics and Chemistry (GHGs and aerosols)
• Cloud physics
• Climatology
• Volcanology
• Solar system physics
• Oceanography
• Hydrology
• Coastal zone dynamics
• Ecosystem dynamics
• Agriculture and forestry
• Zoonotic and other environmental diseases
• Human security
• Insurance
• Law
• Politics
• Psychology
• Ethics
• Other drivers of global change
RELEVANCE to CC DECISIONs• Demographics
• Economics• Social dynamics
• Land use
• Emissions• Atmospheric physics and Chemistry (GHGs and aerosols)
• Cloud physics
• Climatology• Volcanology
• Solar system physics
• Oceanography
• Hydrology• Coastal zone dynamics
• Ecosystem dynamics• Agriculture and forestry• Zoonotic and other environmental diseases
• Human security
• Insurance• Law
• Politics
• Psychology • Ethics• Other drivers of global change
1) IA can be used to focus effort according to its relevance to the decisions being contemplated
Jan 12th 2010, Ottawa 9
But what is the Objective?
• Protect the world from the potential adverse effects of climate change.
• To improve our lot without harming the welfare of current and future generations+.
+ All beings
2) IA can highlight inadequacies in the scope of the initial decision space…
Jan 12th 2010, Ottawa 10
“Protect Human & Animal Welfare”
• Under this general rubric the various agencies have been formed and charged with dealing with various aspects of this challenge each with their own sub-objectives…*
• Is the new objective boundary set appropriately?
– Pathways, geography, interaction effects, timeline...
– Are all aspects of the objective covered?
– Are there pitfalls in leaving out food-borne diseases?
– How will we solve the “patent office” problem?
Genesis
• Where would new zoonotic diseases emerge?
– Where might they appear?
– Where would be the selection pressure make the emergent novelty relevant as a risk?
– What are the key dynamics of the processes?
– Where else might one be looking for possible emergence?
Jan 12th 2010, Ottawa 12
IA is a More Realistic Ætiology & Response
• Inherent in an idealized system are assumptions that:
– Detection is not being influenced by other factors
– Attributions are not being based on weak causality
– Impact assessment are not being dominated by interest groups
– Program implementation involves resource allocation beyond media sound-bites.
– Program evaluations will be real and use the findings to improve our understanding of how to achieve and refine our objectives more effectively.*
Jan 12th 2010, Ottawa 13
The A2C2FHIP Objective
• Much like the UK’s Human Animal Infections and Risk Surveillance (HAIRS) Group…
– … to identify and assess infections with potential for interspecies transfer (particularly zoonotic infections).
Detection in water
Boil water
advisory
Extreme events & Cryptosporidiosis
Climate change?
Torrential rain Overwhel
ms sewage system Crypto-
in water supply
Epidemic
Indirect alert
Revise sewage handling
Understand what
happened
Reconsider land
use patterns
R&D for better
detection
day 1 day 2 day 3 day 4 day 5 day 6week 2year 2year 20
Detection in water
Detection in
patients
Boil water
advisory
Jan 12th 2010, Ottawa 15
It will take all the
relevant bodies
• We can only succeed in meeting such objectives by crossing institutional boundaries.
• And one entity needs to be responsible and resourced to take the lead position.*
Jan 12th 2010, Ottawa 16
A Value of Information Approach
• What is the value of the objective being met?
• What do we need to know to make the next decision?
– Which information is critical?
– Can that information be gained in time to inform the next decision in a timely fashion?
• Elimination of uncertainty is not a pre-requisite for action.
• Knowledge beyond that needed to make a decision has no additional value for this function.
Jan 12th 2010, Ottawa 17
China is likely the Origin of
the Next Pandemic Flu• They believe once the virus has been
identified, they can quarantine large tracts of their territory
– Therefore, they argue: we need to invest in fast DNA sequencing.
– Meanwhile, they have replaced rural “barefoot doctors” with a fee-for-service healthcare/vet system
Jan 12th 2010, Ottawa 18
Intelligence Gathering
• What factors influence our capacity to collect information?
– Economics of animal husbandry
– Access to insurance
– Technological change
• in detection
• In information management
• …
Jan 12th 2010, Ottawa 19
Timely & Informed Decisions
• Why accept the notion that Canadian cattle will not suffer?
– Why delay the ban on intra/inter-species feed?
• Current know-how shows prions can only be destroyed above 800 C.
– A temperature that cannot be reached except in the largest incinerators? Why allow burial of SRM?
– What are we to do about small scale operations?
– What do consumers expect?
Jan 12th 2010, Ottawa 20
Public Perceptions & Reactions
• The public react to fear from their perceptions of exposure to hazards.
• Communication and engagement is critical to empowering the public to help us better manage risks.
– Dengue in Cuba
– WNv in Canada
• Loss of public trust is extra-ordinarily costly in the long run.
Jan 12th 2010, Ottawa 21
Inaction & Precaution
• Precaution, rational action and delay all have economic and ethical consequences.
– These are asymmetric in magnitude.
– and have very different longevity of effect.
– And need to be assessed in the context of the grand objective of public and animal welfare.*
Jan 12th 2010, Ottawa 22
Philosophy (research)• Understand the range of possible policy solutions before designing
how to research the problem.
– The space of possible solutions defines where effort at learning will have the highest value.
– From an applied science perspective, there is no payoff to knowledge that has no bearing on the best informed policy/ solution.
• Eschew needless detail.
– Uncertainties can wash over details. If so, the details are a false precision and generate a misplaced sense of confidence in state of knowledge.
• Characterize uncertainties in:
– how the processes may be working;
– how to parameterize them;
– what we value.
Jan 12th 2010, Ottawa 23
Philosophy (management)
• Bring all relevant parties into the tent.
• Assign resources and control in ONE lead entity.
• Understand how concerns of stakeholders influence institutional responses.
• Use the framework to prioritize research and allocate resources according to where additional knowledge would be most valuable.
• Be honest and open about what can and cannot be known and acted upon under the current mandate/resource constraints.
Jan 12th 2010, Ottawa 24
Next Steps• Clarify the objective
– Use a value of information approach for budget allocation
– Define the lead and respect all participants
– Define criteria for “triggering observations”
– Define the steps for processing observations into information critical to the decision process.*
– Evaluate the program
• Iterate steps above, including the articulation of objective and refine as needed
Questions/Discussion
Other stuff
Jan 12th 2010, Ottawa 27
Cryptosporidiosis as an emerging disease
1907 Discovered in mice and named
1955 Recognized as a disease agent in turkeys
1971 Recognized as a disease agent in cattle
1972 Identified in humans
1984-94 Series of large waterborne outbreaks in
the US
Jan 12th 2010, Ottawa 28
Outbreaks of Waterborne
Cryptosporidiosis in the US Cases Presumptive Cause Filtered?
1984 2,000 sewage in chlorinated well water no
1987 13,000 water treatment interruption yes
1992 3,000 inadequate filtration yes
1992 550 surface water contamination of spring no
1993 403,000 problems with new coagulant yes
1994 100 all HIV+, no malfunction yes
1994 130 sewage in untreated well water no
Jan 12th 2010, Ottawa 29
Influence Diagram
Summarizes the current state of knowledge concerning the important scientific, engineering, institutional, and behavioral factors and their interactions relevant to the risk and its management.
Jan 12th 2010, Ottawa 30Top Level Diagram: Awareness, Communication, and Behavior
Routine testing water
type
routine testing type
treatment levels
treatment options
index variables for tables
Routine testing results
Utility awareness
Health Department awareness
Media coverage
Consumer awareness for public systems
Tap test
Medical Awareness
Trigger Event
Well test
Consumer awareness for private
wells
Utility Communique
Utility treatment
options
Consumption of well water
Consumption of treated water
Averting behavior for public
systems
Averting behavior
for private wells
Special studies
Joint task force
Health EffectsContamination of Drinking Water
timestep = 1 week
Info sources
-
Jan 12th 2010, Ottawa 31
Government enforcement
actions
Source of Cryptosporidium
Present in surface water
Present in utility intake
Present in ground water
Present in private wells
Access to ground water
Subsurface attenuation
Well vulnerability
Present in finished water
Distribution system
contamination
Present at tap
Source water type
timestep = 1 week
-
Contamination of Drinking Water Module
Jan 12th 2010, Ottawa 32
Proportion on Public
System
Epidemic Morbidity
Proportion HIV+
Secondary Transmission
Herd Immunity
Endemic rate HIV -
Endemic rate HIV+
Total Endemicity
Other Sources
timestep = 1 week
Mortality
-
Health Effects Module
Jan 12th 2010, Ottawa 33
Foodborne Recreational Water
prepared foods and meat
fresh fruits, vegetablesand drinks
lakes, ponds rivers, streams
swimming pools, beaches
irrigation water
wash water
handler feces
Outbreaks caused by Other Factors
Person to Person and
Zoonotic
Hospital and Nursing Home
Day Care
swimmers exposed
eatersexposedpeople
exposed
Animal Contact
Sexual contact
-
Other Sources Module
Jan 12th 2010, Ottawa 34
Routine testing water
type
routine testing type
treatment levels
treatment options
index variables for tables
Routine testing results
Utility awareness
Health Department awareness
Media coverage
Consumer awareness for public systems
Tap test
Medical Awareness
Trigger Event
Well test
Consumer awareness for private
wells
Utility Communique
Utility treatment
options
Consumption of well water
Consumption of treated water
Averting behavior for public
systems
Averting behavior
for private wells
Special studies
Joint task force
Health EffectsContamination of Drinking Water
timestep = 1 week
-
Table 3. Influence Diagram “Awareness” Variables Va lues, Base CaseVariable Range Week 1 Week 2 Week 3 Week 4 Week 5 Week 6
Utility Awareness 0 to 5 0 1 1 4 5 4
Medical Awareness 0 to 2 0 1 2 2 1 1
Health Department Awareness 0 to 2 0 0 1 2 2 2
Media Coverage 0 to 2 0 0 0 2 2 2
Consumer Awareness 0 to 2 0 0 0 2 2 2
Jan 12th 2010, Ottawa 35
Information Collection Rule of 1996
• Purpose: To provide the information necessary for the development of the final form of the Cryptosporidium rules
• Mandates collection and reporting of monitoring data by water suppliers serving more than 100,000 customers
Jan 12th 2010, Ottawa 36
What is so unusual and elusive about Cryptosporidium that requires a 6-year data collection program before the finalization of drinking water standards?
Jan 12th 2010, Ottawa 37
The data stink• Environmental Screening:
– Before Information Collection Rule, no mandated sampling of drinking water
– Recovery of Indirect Fluorescent Assay (IFA) 5 to 25%
• Medical Surveillance:
– Same symptoms as other GI disorders
– 75% doctors never order crypto tests
– 30% thought they were included in ova & parasite tests (Morin, 1997)
– Detection limit 5,000 oocysts/gm stool
– Not all infected individuals shed oocysts. In those who do, shedding is sporadic.
– Mild cases do not get treated or reported
– 3 cases in 10,000 get reported (Perz, 1998)
Jan 12th 2010, Ottawa 38
Detection
• Small concentrations of Cryptosporidium are likely to be found in many source waters.
• How should utilities report this information to avoid misunderstandings?
• How to communicate risk and uncertainty while maintaining customer confidence?
• How can the utility be sure customers understand the information?
Jan 12th 2010, Ottawa 39
Mental Models Methodology
• Depicts an individual’s beliefs regarding a risk process and the options for addressing the risk
• Identifies crucial gaps in information and misunderstandings by contrasting the mental model with an expert model
Jan 12th 2010, Ottawa 40
Expert Model
• Is constructed using an extensive literature review.
• Then refined through feedback from microbiologists, engineers, and utility personnel.
Jan 12th 2010, Ottawa 41
An IA for the Arctic
Jan 12th 2010, Ottawa 42
Methodology• Use anything that helps improve understanding of the issues
and address the concerns of different stakeholders.
• But remember that integration does not mean that one can cobble together any and all disciplinary insights.
– Disciplines have been constructed through restrictive assumptions isolating the processes of interest from outside influences.
– Integration is about how these “seemingly independent” processes influence one another.
– Therefore, some of the received doctrine from disciplines will have to be ditched in order to develop coherent integrated assessments.
Jan 12th 2010, Ottawa 43
Motivation
• Real world problems are often complex because they involve:
many different stakeholders with competing agendas;
interacting socio-economic, environmental & other issues;
a range of space and time scales.
• Disciplinary solutions are not helpful because they tend to:
o address only one dimension of stakeholder needs;
o reflect only one aspect of the dynamic processes involved;
o focus on one scale or time step.
Jan 12th 2010, Ottawa 44
BSE & vCJD in the UK
Sources: (Collinge, 1999; DEFRA, 2005; EC 96/362, 1996; SEAC, 1996)
SRM removal
UK BSE/vCJD Profile
-
10,000
20,000
30,000
40,000
1987 1992 1997 2002Year
Incidence of BSE
0
10
20
30
40
Incidence of vCJD
Confirmed Cases of BSE
Confirmed Cases of vCJD
Inter-species Feed Ban
Export Ban
Intra-species Feed Ban
SRM removal
Jan 12th 2010, Ottawa 45
CDN Risk ManagementCDN BSE/vCJD Profile
0
1
2
3
4
1988 1993 1998 2003Date
Incidence of BSE
Confirmed Casesof BSE
UK Import BanUK Import Ban
Intra-species feed ban
BSEBSE
Blended Export Ban Blended Export Ban
SRM removalSRM removal
Source: CFIA, 2005Source: CFIA, 2005
Jan 12th 2010, Ottawa 46
BSE
UK:
– Exp. Loss 3.5B
– Compensation 19%
Canada:
– Exp. Loss, 3.1B
– Compensation 20%