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      A review of qualitative risk assessment in animal health: Suggestions for best practice

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          Abstract

          Qualitative risk assessment (QRA) can provide decision support in line with the requirement for an objective, unbiased assessment of disease risk according to the Agreement on the Application of Sanitary and Phytosanitary Measures of the World Trade Organization. However, in order for a QRA to be objective and consistently applied it is necessary to standardize the approach as much as possible. This review considers how QRAs have historically been used for the benefit of animal health, what problems have been encountered during their progression, and considers best practice for their future use. Four main elements were identified as having been the subject of some proposed standard methodology: (i) the description of risk levels, (ii) combining probabilities, (iii) accounting for trade volume and time period, and (iv) uncertainty. These elements were addressed in different ways but were highlighted as being fundamental to improving the robustness in estimating the risk and conveying the results to the risk manager with minimal ambiguity. In line with this, several tools have been developed which attempt to use mathematical reasoning to incorporate uncertainty and improve the objectivity of the qualitative framework. This represents an important advance in animal health QRA. Overall, animal health QRAs have established their usefulness by providing a tool for rapid risk estimation which can be used to identify important chains of events and critical control points along risk pathways and inform risk management programmes as to whether or not the risk exceeds a decision-making threshold above which action should be taken. Ensuring a robust objective methodology is used and that the reasons for differences in results, such as assumptions and uncertainty are clearly described to the customer with minimal ambiguity is essential to maintain confidence in the QRA process. However, further work needs to be done to determine if one objective uniform methodology should be developed and considered best practice. To this end, a set of best practice guidelines presenting the optimal way to conduct a QRA and regulated by bodies such as the World Organization for Animal Health or the European Food Safety Authority would be beneficial.

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          Most cited references57

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          Guidance on Uncertainty Analysis in Scientific Assessments

          Abstract Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. It is therefore relevant in all EFSA's scientific assessments and also necessary, to ensure that the assessment conclusions provide reliable information for decision‐making. The form and extent of uncertainty analysis, and how the conclusions should be reported, vary widely depending on the nature and context of each assessment and the degree of uncertainty that is present. This document provides concise guidance on how to identify which options for uncertainty analysis are appropriate in each assessment, and how to apply them. It is accompanied by a separate, supporting opinion that explains the key concepts and principles behind this Guidance, and describes the methods in more detail.
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            What's wrong with risk matrices?

            Risk matrices-tables mapping "frequency" and "severity" ratings to corresponding risk priority levels-are popular in applications as diverse as terrorism risk analysis, highway construction project management, office building risk analysis, climate change risk management, and enterprise risk management (ERM). National and international standards (e.g., Military Standard 882C and AS/NZS 4360:1999) have stimulated adoption of risk matrices by many organizations and risk consultants. However, little research rigorously validates their performance in actually improving risk management decisions. This article examines some mathematical properties of risk matrices and shows that they have the following limitations. (a) Poor Resolution. Typical risk matrices can correctly and unambiguously compare only a small fraction (e.g., less than 10%) of randomly selected pairs of hazards. They can assign identical ratings to quantitatively very different risks ("range compression"). (b) Errors. Risk matrices can mistakenly assign higher qualitative ratings to quantitatively smaller risks. For risks with negatively correlated frequencies and severities, they can be "worse than useless," leading to worse-than-random decisions. (c) Suboptimal Resource Allocation. Effective allocation of resources to risk-reducing countermeasures cannot be based on the categories provided by risk matrices. (d) Ambiguous Inputs and Outputs. Categorizations of severity cannot be made objectively for uncertain consequences. Inputs to risk matrices (e.g., frequency and severity categorizations) and resulting outputs (i.e., risk ratings) require subjective interpretation, and different users may obtain opposite ratings of the same quantitative risks. These limitations suggest that risk matrices should be used with caution, and only with careful explanations of embedded judgments.
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              Scientific Opinion on Risk Assessment Terminology

              (2012)
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                Author and article information

                Contributors
                Journal
                Front Vet Sci
                Front Vet Sci
                Front. Vet. Sci.
                Frontiers in Veterinary Science
                Frontiers Media S.A.
                2297-1769
                07 February 2023
                2023
                : 10
                : 1102131
                Affiliations
                [1] 1Department of Epidemiological Sciences, Animal and Plant Health Agency , Surrey, United Kingdom
                [2] 2Department of Mathematics and Statistics, University of Strathclyde , Glasgow, United Kingdom
                Author notes

                Edited by: Marta Martinez Aviles, Instituto Nacional de Investigación y Tecnología Agroalimentaria (INIA), Spain

                Reviewed by: Katharina D. C. Stärk, Federal Food Safety and Veterinary Office (FSVO), Switzerland; Giuseppe Ru, Experimental Zooprophylactic Institute for Piedmont, Liguria and Valle d'Aosta (IZSTO), Italy

                *Correspondence: Verity Horigan ✉ verity.horigan@ 123456apha.gov.uk

                This article was submitted to Veterinary Epidemiology and Economics, a section of the journal Frontiers in Veterinary Science

                Article
                10.3389/fvets.2023.1102131
                9941190
                36825234
                49d8cac3-21b9-4e6f-b5a5-2faf1d3f3750
                Copyright © 2023 Horigan, Simons, Kavanagh and Kelly.

                Crown Copyright © 2023 Horigan, Simons, Kavanagh and Kelly. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 November 2022
                : 17 January 2023
                Page count
                Figures: 2, Tables: 7, Equations: 0, References: 62, Pages: 11, Words: 9232
                Funding
                This research was funded by the Animal and Plant Health Agency and the University of Strathclyde.
                Categories
                Veterinary Science
                Review

                qualitative,risk,assessment,animal,health
                qualitative, risk, assessment, animal, health

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