Integrated Assessment of Emerging Zoonotic Diseases Presented at

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 12 th 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. Jan 12 th 2010, Ottawa 3

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. Jan 12 th 2010, Ottawa 4

Collective decision-making Human 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

Applications of IA • 70 s & 80 s – SST, CFCs, Acid Rain • 90 s – Climate change – Cryptosporidiosis – Dengue • 00 s – Hydatid disease in Katmandu – Malaria in various regions of the world Jan 12 th 2010, Ottawa 6

IA of Climate Change • Demographics • Economics • Social dynamics • Land use • Emissions • Atmospheric physics and Chemistry (GHGs and aerosols) • Cloud physics • Demographics • Economics • Social dynamics • Climatology • 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 12 th 2010, Ottawa 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 RELEVANCE to CC DECISIONs • Demographics • Economics • Social dynamics • • Land use Emissions • Atmospheric physics and Chemistry (GHGs and • • 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 aerosols) 1) IA can be used to focus effort according to its relevance to the decisions being contemplated Jan 12 th 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… All beings Jan 12 th 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 subobjectives…* • 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 12 th 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 12 th 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). Jan 12 th 2010, Ottawa 13

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

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 12 th 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. Jan 12 th 2010, Ottawa 16

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 12 th 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 12 th 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 12 th 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 12 th 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 12 th 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. Jan 12 th 2010, Ottawa 22

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 12 th 2010, Ottawa 23

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 12 th 2010, Ottawa 24

Questions/Discussion

Other stuff

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 12 th 2010, Ottawa 27

Outbreaks of Waterborne Cryptosporidiosis in the US Cases Presumptive Cause 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 12 th 2010, Ottawa Filtered? 28

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 12 th 2010, Ottawa 29

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

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

Health Effects Module Jan 12 th 2010, Ottawa 32

Other Sources Module Jan 12 th 2010, Ottawa 33

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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 12 th 2010, Ottawa 35

What is so unusual and elusive about Cryptosporidium that requires a 6 -year data collection program before the finalization of drinking water standards? Jan 12 th 2010, Ottawa 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 – 3 cases in 10, 000 get reported (Perz, 1998) Jan 12 th 2010, Ottawa 37

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 12 th 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 12 th 2010, Ottawa 39

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

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

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 12 th 2010, Ottawa 42

Motivation • Real world problems are often complex because they involve: • Disciplinary solutions are not helpful because they tend to: ü many different stakeholders with competing agendas; o address only one dimension of stakeholder needs; ü interacting socioeconomic, environmental & other issues; o reflect only one aspect of the dynamic processes involved; ü a range of space and time scales. o focus on one scale or time step. Jan 12 th 2010, Ottawa 43

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

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

BSE UK: Canada: – Exp. Loss 3. 5 B – Exp. Loss, 3. 1 B – Compensation 19% – Compensation 20% Jan 12 th 2010, Ottawa 46