A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale.

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.

Transcultural validation of the SIGAM mobility grades in French: The SIGAM-Fr.

BACKGROUND: The main French language scales evaluating functioning after lower-limb amputation have not undergone exhaustive psychometric validation. OBJECTIVE: A transcultural validation of the Special Interest Group in Amputee Medicine (SIGAM) mobility grades questionnaire, with 21 closed questions, as an administered questionnaire. METHODS: The questionnaire translation, back-translation and original-author validation was followed by a pretest with 5 patients to check comprehension. The psychometric properties of the scale were validated with 49 patients at the definitive prosthesis stage by an investigator via telephone. Criterion validity was evaluated by comparison with the Houghton Scale score and construct validity by correlation between the questionnaire scores and convergent dimensions (performing everyday activities and performing transfers on a numerical rating scale [NRS], 2-min walk test) and divergent dimensions (managing medication and stump skin care on an NRS). Internal consistency was assessed by the Kuder-Richardson Formula 20 (KR-20) coefficient and test-retest reproducibility by the Cohen kappa coefficient. RESULTS: The resulting questionnaire was validated by the original author after the back-translation. It showed good psychometric properties when administered by an investigator as a self-reporting questionnaire, excellent criterion validity (r=0.89, P<0.01), excellent reproducibility (kappa coefficient 0.87) and satisfactory construct validity. The KR-20 coefficient was 0.67. CONCLUSION: The French version of the SIGAM mobility grades questionnaire (SIGAM-Fr) has satisfactory psychometric properties and can be administered in clinical practice.

Modelling collective effectiveness of voluntary vaccination with and without incentives.

Control strategies of infectious diseases at a regional level can rely on vaccination. When the decision to vaccinate is made by each farmer on a voluntary basis, a farmer vaccinates to protect his own herd. If the vaccinated herds are protected against infection, the risk for other herds is reduced, creating a positive externality (i.e. an impact on a third party not directly involved in the decision). The objectives of this study are to evaluate the effectiveness at a regional level of voluntary vaccination and to analyse the effect of financial incentives and compensation for losses due to disease considering the externalities due to vaccination. We developed a dynamic deterministic model, based on a decision model interacting with an epidemiological state transition model. It determines the proportion of farmers who vaccinate over time, and the evolution of the prevalence of infected herds in a population of herds exposed to the same risk. The behaviour of farmers is modelled assuming perfect information (farmers are fully informed about prevalence, costs of disease and costs of vaccination). The decision to vaccinate is made according to a rational economic behaviour: farmers make their choices to maximize their expected utility, considering their risk aversion. The expected utility is calculated with a decision tree. The epidemiological model is based on a SIR (Susceptible, Infectious, Recovered) model modified to consider imperfect vaccination that protects herds for one year. The model is studied analytically and by simulation. For simulations, we define the epidemiological parameters of the model (transmission rate and average duration of the infectious and recovered states), the herd level effectiveness of the vaccination, the cost of vaccination, the reduction of income due to the disease, the incomes of the farmers and the risk aversion of the farmers. These parameters are based on an endemic disease, BVD (Bovine Viral Diarrhoea). The model shows that voluntary vaccination cannot eradicate the modelled disease. Risk aversion of farmers leads to a lower prevalence at the equilibrium than when farmers are risk neutral. Incentives for vaccination decrease the prevalence but do not result in eradication of the disease. Compensating for disease losses in newly infected farms leads to an increase in prevalence, due to moral hazard (farmers behave less carefully than if they were fully exposed to the risk), except if it is restricted to vaccinated herds.