BIOEPAR, INRA, Oniris, Université Bretagne Loire, Nantes, France.
CESAER, AgroSup Dijon, INRA, Univ. Bourgogne Franche-Comté, Dijon, France.
PLoS One. 2018 Jun 13;13(6):e0197612. doi: 10.1371/journal.pone.0197612. eCollection 2018.
The effectiveness of infectious disease control depends on the ability of health managers to act in a coordinated way. However, with regards to non-notifiable animal diseases, farmers individually decide whether or not to implement control measures, leading to positive and negative externalities for connected farms and possibly impairing disease control at a regional scale. Our objective was to facilitate the identification of optimal incentive schemes at a collective level, adaptive to the epidemiological situation, and minimizing the economic costs due to a disease and its control. We proposed a modelling framework based on Markov Decision Processes (MDP) to identify effective strategies to control PorcineReproductive andRespiratorySyndrome (PRRS), a worldwide endemicinfectiousdisease thatsignificantly impactspig farmproductivity. Using a stochastic discrete-time compartmental model representing PRRS virus spread and control within a group of pig herds, we defined the associated MDP. Using a decision-tree framework, we translated the optimal policy into a limited number of rules providing actions to be performed per 6-month time-step according to the observed system state. We evaluated the effect of varying costs and transition probabilities on optimal policy and epidemiological results. We finally identifiedan adaptive policy that gave the best net financial benefit. The proposed framework is a tool for decision support as it allows decision-makers to identify the optimal policy and to assess its robustness to variations in the values of parameters representing an impact of incentives on farmers' decisions.
传染病控制的有效性取决于卫生管理者协调行动的能力。然而，对于非法定动物疾病，农民个体决定是否实施控制措施，这导致了相关农场的正外部性和负外部性，可能会损害区域范围内的疾病控制。我们的目标是在集体层面上促进确定最优激励方案，使其适应流行病学情况，并最小化疾病及其控制造成的经济成本。我们提出了一个基于马尔可夫决策过程（MDP）的建模框架，以确定控制猪繁殖与呼吸综合征（PRRS）的有效策略，PRRS 是一种全球性流行的传染病，严重影响养猪场的生产力。我们使用代表猪群中 PRRS 病毒传播和控制的随机离散时间房室模型来定义相关的 MDP。使用决策树框架，我们将最优策略转换为有限数量的规则，根据观察到的系统状态，为每个 6 个月的时间步提供要执行的操作。我们评估了成本和转移概率变化对最优策略和流行病学结果的影响。最后，我们确定了一种适应性策略，该策略可带来最佳的净财务收益。所提出的框架是一个决策支持工具，因为它允许决策者确定最优策略，并评估其对代表激励对农民决策影响的参数值变化的稳健性。
