Decision-making for foot-and-mouth disease control: Objectives matter
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
Affiliations
William J.M. Probert
Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United States
Katriona Shea
Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United States
Christopher J. Fonnesbeck
Department of Biostatistics, Vanderbilt University, Nashville, TN, United States
Michael C. Runge
US Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Rd, Laurel, MD, United States
Tim E. Carpenter
EpiCentre, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston North, New Zealand
Salome Dürr
Veterinary Public Health Institute, University of Bern, Bern, Switzerland
M. Graeme Garner
Animal Health Policy Branch, Australian Government, Department of Agriculture, GPO Box 858, Canberra 2601, ACT, Australia
Neil Harvey
Department of Computing and Information Science, University of Guelph, Guelph, ON, Canada N1G 2W1
Mark A. Stevenson
Faculty of Veterinary Science, University of Melbourne, Melbourne, VIC, Australia
Colleen T. Webb
Department of Biology, Colorado State University, Fort Collins, CO, United States
Marleen Werkman
Central Veterinary Institute, Wageningen University and Research Centre, Houtribweg 39, 8221 RA Lelystad, The Netherlands
Michael J. Tildesley
School of Veterinary Medicine and Science, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
Matthew J. Ferrari
Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United States
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.
