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Integrated Assessment of Emerging Zoonotic Diseases Presented at: CFIAPHAC Joint Workshop on Integrated Analysis of non-Foodborne Zoonotic Risk January.

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Presentation on theme: "Integrated Assessment of Emerging Zoonotic Diseases Presented at: CFIAPHAC Joint Workshop on Integrated Analysis of non-Foodborne Zoonotic Risk January."— Presentation transcript:

1 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

2 Jan 12th 2010, Ottawa 2 Overview What is an IA? A process for creating one Examples Next steps

3 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.

4 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.

5 Collective decision-making 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 a chosen strategy, Evaluation & Feedback Human

6 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

7 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

8 Jan 12th 2010, Ottawa 8 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 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

9 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…

10 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?

11 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?

12 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.*

13 Jan 12th 2010, Ottawa 13 The A 2 C 2 FHIP Objective Much like the UKs Human Animal Infections and Risk Surveillance (HAIRS) Group… –… to identify and assess infections with potential for interspecies transfer (particularly zoonotic infections).

14 Detection in water Boil water advisory Extreme events & Cryptosporidiosis Climate change? Torrential rain Overwhelm s sewage system Crypto- in water supply Epidemic Indirect alert Revise sewage handling Understand what happened Reconside r land use patterns R&D for better detection day 1day 2day 3day 4day 5day 6week 2year 2 year 20 Detection in water Detection in patients Boil water advisory

15 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.*

16 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.

17 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

18 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 …

19 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?

20 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.

21 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.*

22 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.

23 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.

24 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

25 Questions/Discussion

26 Other stuff

27 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 Series of large waterborne outbreaks in the US

28 Jan 12th 2010, Ottawa 28 Outbreaks of Waterborne Cryptosporidiosis in the US Cases Presumptive Cause Filtered? ,000 sewage in chlorinated well waterno ,000 water treatment interruptionyes ,000 inadequate filtrationyes surface water contamination of springno ,000 problems with new coagulantyes all HIV+, no malfunction yes sewage in untreated well waterno

29 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.

30 Jan 12th 2010, Ottawa 30 Top Level Diagram: Awareness, Communication, and Behavior

31 Jan 12th 2010, Ottawa 31 Contamination of Drinking Water Module

32 Jan 12th 2010, Ottawa 32 Health Effects Module

33 Jan 12th 2010, Ottawa 33 Other Sources Module

34 Jan 12th 2010, Ottawa 34

35 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

36 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?

37 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)

38 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?

39 Jan 12th 2010, Ottawa 39 Mental Models Methodology Depicts an individuals 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

40 Jan 12th 2010, Ottawa 40 Expert Model Is constructed using an extensive literature review. Then refined through feedback from microbiologists, engineers, and utility personnel.

41 Jan 12th 2010, Ottawa 41 An IA for the Arctic

42 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.

43 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: oaddress only one dimension of stakeholder needs; oreflect only one aspect of the dynamic processes involved; ofocus on one scale or time step.

44 Jan 12th 2010, Ottawa 44 BSE & vCJD in the UK Sources: ( Collinge, 1999; DEFRA, 2005; EC 96/362, 1996; SEAC, 1996 ) SRM removal Inter-species Feed Ban Export Ban Intra-species Feed Ban SRM removal

45 Jan 12th 2010, Ottawa 45 CDN Risk Management UK Import Ban Intra-species feed ban BSE Blended Export Ban SRM removal Source: CFIA, 2005

46 Jan 12th 2010, Ottawa 46 BSE UK: –Exp. Loss 3.5B –Compensation 19% Canada: –Exp. Loss, 3.1B –Compensation 20%


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