Ensemble modelling and structured decision-making to support Emergency Disease Management

Prev Vet Med. 2017 Mar 1:138:124-133. doi: 10.1016/j.prevetmed.2017.01.003. Epub 2017 Jan 16.

Abstract

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application.

Keywords: Disease management; Ensemble modelling; Foot and mouth disease; Policy; Structured decision-making.

MeSH terms

  • Animals
  • Computer Simulation
  • Decision Making
  • Decision Support Techniques*
  • Disease Management
  • Disease Outbreaks / prevention & control
  • Disease Outbreaks / veterinary*
  • Foot-and-Mouth Disease / epidemiology*
  • Foot-and-Mouth Disease / prevention & control*
  • Models, Biological*
  • United Kingdom / epidemiology