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...
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| _version_ | 1850230735935373312 |
|---|---|
| author | Anne-France Viet Stéphane Krebs Olivier Rat-Aspert Laurent Jeanpierre Catherine Belloc Pauline Ezanno |
| author_facet | Anne-France Viet Stéphane Krebs Olivier Rat-Aspert Laurent Jeanpierre Catherine Belloc Pauline Ezanno |
| author_sort | Anne-France Viet |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d97ece2b9dbe471885d34b2bb6607d12 |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-d97ece2b9dbe471885d34b2bb6607d122025-08-20T02:03:46ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01136e019761210.1371/journal.pone.0197612A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale.Anne-France VietStéphane KrebsOlivier Rat-AspertLaurent JeanpierreCatherine BellocPauline EzannoThe 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.https://storage.googleapis.com/plos-corpus-prod/10.1371/journal.pone.0197612/1/pone.0197612.pdf?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=wombat-sa%40plos-prod.iam.gserviceaccount.com%2F20210218%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20210218T135227Z&X-Goog-Expires=3600&X-Goog-SignedHeaders=host&X-Goog-Signature=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 |
| spellingShingle | Anne-France Viet Stéphane Krebs Olivier Rat-Aspert Laurent Jeanpierre Catherine Belloc Pauline Ezanno A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale. PLoS ONE |
| title | A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale. |
| title_full | A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale. |
| title_fullStr | A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale. |
| title_full_unstemmed | A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale. |
| title_short | A modelling framework based on MDP to coordinate farmers' disease control decisions at a regional scale. |
| title_sort | modelling framework based on mdp to coordinate farmers disease control decisions at a regional scale |
| url | https://storage.googleapis.com/plos-corpus-prod/10.1371/journal.pone.0197612/1/pone.0197612.pdf?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=wombat-sa%40plos-prod.iam.gserviceaccount.com%2F20210218%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20210218T135227Z&X-Goog-Expires=3600&X-Goog-SignedHeaders=host&X-Goog-Signature=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 |
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