Integrated Assessment of Emerging Zoonotic Diseases

Presented at: CFIAPHAC Joint Workshop on Integrated Analysis of non-Foodborne Zoonotic Risk January 12 th 2010 Hadi Dowlatabadi

Overview

• What is an IA?

• A process for creating one • Examples • Next steps Jan 12th 2010, Ottawa 2

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.

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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.

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Human

Agency

Limited detection

...we perceive changes in our system,

Imperfect knowledge

... identify their origin & project trends/consequences,

Values that change with contexts/time

...evaluate various options,

Blunt mechanisms for realizing goals

...implement a chosen strategy, Evaluation & Feedback

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 6

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 Jan 12th 2010, Ottawa • 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 7

IA of Climate Change

EQUAL 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 to the decisions being contemplated • • • • • • • • • • • • • • • • • • • • • • •

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 Jan 12th 2010, Ottawa 8

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 + .

+ 2) IA can highlight inadequacies in the scope of the initial decision space… Jan 12th 2010, Ottawa 9

•

“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?

Jan 12th 2010, Ottawa 10

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?

•

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 12

The A

2

C

2

FHIP 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).

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Extreme events &

Cryptosporidiosis

day 1 day 2 day 3 day 4 day 5 day 6 week 2 year 2 year 20 Climate change?

Torrential rain Overwhelm s sewage system Detection in water Crypto in water supply Reconside r land use patterns Revise sewage handling Detection in patients Indirect Epidemic alert Understand what happened Boil water advisory R&D for better detection

It will take the relevant bodies

all

• 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 15

•

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.

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•

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 17

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 18

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 19

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 20

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 21

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.

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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.

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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 Jan 12th 2010, Ottawa 24

Questions/Discussion

Other stuff

1907

Cryptosporidiosis

as an emerging disease

Discovered in mice and named 1955 Recognized as a disease agent in turkeys 1971 1972 Recognized as a disease agent in cattle Identified in humans 1984-94 Series of large waterborne outbreaks in the US Jan 12th 2010, Ottawa 27

Outbreaks of Waterborne

Cryptosporidiosis

in the US

Cases Presumptive Cause Filtered?

1984 2,000 sewage in chlorinated well water 1987 13,000 water treatment interruption 1992 3,000 1992 550 inadequate filtration surface water contamination of spring 1993 403,000 1994 100 1994 130 problems with new coagulant all HIV+, no malfunction sewage in untreated well water no yes yes no yes yes no Jan 12th 2010, Ottawa 28

Jan 12th 2010, Ottawa

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.

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Contamination of Drinking Water Health Effects

timestep = 1 week Routine testing res ults Utility treatment options Utility awareness Health Department awareness Utility Communique Consumption of treated water Consumption of well water Medical Awarenes s Tap test Averting behavior for public sys tems Info sources Averting behavior for private wells Consumer awareness for public s ystems Consumer awareness for private wells Well test Trigger Event Special studies Joint tas k forc e Media coverage Top Level Diagram: Awareness, Communication, and Behavior Jan 12th 2010, Ottawa 30 index variables for tables Routine testing water type routine testing type treatment levels treatment options

Present in surface water Contamination of Drinking Water timestep = 1 week Module Source of Cryptos poridium Acces s to ground water Government enforcement actions Present in ground water Present in utility intake Source water type Present in finished water Well vulnerability Subsurface attenuation Present at tap Distribution sys tem contamination Present in private wells Jan 12th 2010, Ottawa 31

Proportion HIV+ timestep = 1 week Mortality Proportion on Public System Endemic rate HIV+ Endemic rate HIV Epidemic Morbidity Secondary Transmis sion Total Endemicity Herd Immunity Health Effects Module

Other Sources

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Outbreak s caused by Other Factors people exposed Person to Person and Zoonotic Sexual contact Animal Contac t Day Care Hospital and Nursing Home eaters exposed Foodborne prepared foods and meat fres h fruits, vegetables and drink s swimmers exposed Recreational Water handler fec es wash water irrigation water lak es, ponds rivers, s treams swimming pools, beaches Other Sources Module Jan 12th 2010, Ottawa 33

Table 3

. Influen ce Diagram “Awa rene ss” Va riables Values, Ba se Case

Utility Awa reness Medical Awareness

Variable Range Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 0 t o 5 0 1 1 4 5 4 0 t o 2 0 1 2 2 1 1

Health Depa rtment Awareness Media Coverage

0 t o 2 0 t o 2 0 0 0 0 1 0 2 2 2 2 2 2

Consumer Awareness

0 t o 2 0 0 0 2 2 2

Contamination of Drinking Water Health Effects

timestep = 1 week Routine testing res ults Trigger Event Utility treatment options Utility awareness Special studies Health Department awareness Utility Communique Medical Awarenes s Joint tas k forc e Consumption of treated water Averting behavior for public sys tems Consumption of well water Averting behavior for private wells Consumer awareness for public s ystems Tap test Consumer awareness for private wells Well test Media coverage Jan 12th 2010, Ottawa 34 index variables for tables Routine testing water type routine testing type treatment levels treatment options

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 35

Jan 12th 2010, Ottawa

What is so unusual and elusive about

Cryptosporidium

that requires a 6-year data collection program before the finalization of drinking water standards?

36

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 – Jan 12th 2010, Ottawa 3 cases in 10,000 get reported (Perz, 1998) 37

Detection

• • • Small concentrations of

Cryptosporidium

likely to be found in many source waters.

are • 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 38

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 39

Expert Model

• Is constructed using an extensive literature review.

• Then refined through feedback from microbiologists, engineers, and utility personnel.

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Jan 12th 2010, Ottawa

An IA for the Arctic

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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.

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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 43

BSE & vCJD in the UK

40,000 30,000 Intra-species Feed Ban

UK BSE/vCJD Profile

Confirmed Cases of BSE Confirmed Cases of vCJD SRM removal Inter-species Feed Ban SRM removal 40 30 20,000 20 Export Ban 10,000 10 Jan 12th 2010, Ottawa 1987 0 1992 1997

Year

2002 Sources: ( Collinge, 1999; DEFRA, 2005; EC 96/362, 1996; SEAC, 1996 ) 44

CDN Risk Management

CDN BSE/vCJD Profile

Confirmed Cases of BSE 4 3 UK Import Ban Intra-species feed ban BSE Blended Export Ban SRM removal 2 1 0 1988 1993

Date

1998 2003 Source: CFIA, 2005 Jan 12th 2010, Ottawa 45

UK: – Exp. Loss 3.5B

– Compensation 19%

BSE

Canada: – Exp. Loss, 3.1B

– Compensation 20% Jan 12th 2010, Ottawa 46