Decision-making for foot-and-mouth disease control: Objectives matter
Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2016-06-01
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| Series: | Epidemics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S175543651500095X |
| _version_ | 1811267156734640128 |
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| author | William J.M. Probert Katriona Shea Christopher J. Fonnesbeck Michael C. Runge Tim E. Carpenter Salome Dürr M. Graeme Garner Neil Harvey Mark A. Stevenson Colleen T. Webb Marleen Werkman Michael J. Tildesley Matthew J. Ferrari |
| author_facet | William J.M. Probert Katriona Shea Christopher J. Fonnesbeck Michael C. Runge Tim E. Carpenter Salome Dürr M. Graeme Garner Neil Harvey Mark A. Stevenson Colleen T. Webb Marleen Werkman Michael J. Tildesley Matthew J. Ferrari |
| author_sort | William J.M. Probert |
| collection | DOAJ |
| description | Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making. |
| first_indexed | 2024-04-12T20:57:20Z |
| format | Article |
| id | doaj.art-c89bb7b633eb4048bfcd66e00293ba68 |
| institution | Directory Open Access Journal |
| issn | 1755-4365 1878-0067 |
| language | English |
| last_indexed | 2024-04-12T20:57:20Z |
| publishDate | 2016-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Epidemics |
| spelling | doaj.art-c89bb7b633eb4048bfcd66e00293ba682022-12-22T03:16:58ZengElsevierEpidemics1755-43651878-00672016-06-0115C101910.1016/j.epidem.2015.11.002Decision-making for foot-and-mouth disease control: Objectives matterWilliam J.M. Probert0Katriona Shea1Christopher J. Fonnesbeck2Michael C. Runge3Tim E. Carpenter4Salome Dürr5M. Graeme Garner6Neil Harvey7Mark A. Stevenson8Colleen T. Webb9Marleen Werkman10Michael J. Tildesley11Matthew J. Ferrari12Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United StatesCenter for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United StatesDepartment of Biostatistics, Vanderbilt University, Nashville, TN, United StatesUS Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Rd, Laurel, MD, United StatesEpiCentre, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston North, New ZealandVeterinary Public Health Institute, University of Bern, Bern, SwitzerlandAnimal Health Policy Branch, Australian Government, Department of Agriculture, GPO Box 858, Canberra 2601, ACT, AustraliaDepartment of Computing and Information Science, University of Guelph, Guelph, ON, Canada N1G 2W1Faculty of Veterinary Science, University of Melbourne, Melbourne, VIC, AustraliaDepartment of Biology, Colorado State University, Fort Collins, CO, United StatesCentral Veterinary Institute, Wageningen University and Research Centre, Houtribweg 39, 8221 RA Lelystad, The NetherlandsSchool of Veterinary Medicine and Science, University of Nottingham, Leicestershire LE12 5RD, United KingdomCenter for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United StatesFormal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.http://www.sciencedirect.com/science/article/pii/S175543651500095XEpidemiologyManagementDecision makingOptimisationObjectivesFoot-and-mouth disease |
| spellingShingle | William J.M. Probert Katriona Shea Christopher J. Fonnesbeck Michael C. Runge Tim E. Carpenter Salome Dürr M. Graeme Garner Neil Harvey Mark A. Stevenson Colleen T. Webb Marleen Werkman Michael J. Tildesley Matthew J. Ferrari Decision-making for foot-and-mouth disease control: Objectives matter Epidemics Epidemiology Management Decision making Optimisation Objectives Foot-and-mouth disease |
| title | Decision-making for foot-and-mouth disease control: Objectives matter |
| title_full | Decision-making for foot-and-mouth disease control: Objectives matter |
| title_fullStr | Decision-making for foot-and-mouth disease control: Objectives matter |
| title_full_unstemmed | Decision-making for foot-and-mouth disease control: Objectives matter |
| title_short | Decision-making for foot-and-mouth disease control: Objectives matter |
| title_sort | decision making for foot and mouth disease control objectives matter |
| topic | Epidemiology Management Decision making Optimisation Objectives Foot-and-mouth disease |
| url | http://www.sciencedirect.com/science/article/pii/S175543651500095X |
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