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Hennessey M, Fournie G, Quaife M, Alarcon P. Modelling multi-player strategic decisions in animal healthcare: A scoping review. Prev Vet Med 2022; 205:105684. [DOI: 10.1016/j.prevetmed.2022.105684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 05/24/2022] [Accepted: 05/26/2022] [Indexed: 11/16/2022]
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Ho E, Rajagopalan A, Skvortsov A, Arulampalam S, Piraveenan M. Game Theory in Defence Applications: A Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:1032. [PMID: 35161778 PMCID: PMC8838118 DOI: 10.3390/s22031032] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/05/2022] [Accepted: 01/06/2022] [Indexed: 06/14/2023]
Abstract
This paper presents a succinct review of attempts in the literature to use game theory to model decision-making scenarios relevant to defence applications. Game theory has been proven as a very effective tool in modelling the decision-making processes of intelligent agents, entities, and players. It has been used to model scenarios from diverse fields such as economics, evolutionary biology, and computer science. In defence applications, there is often a need to model and predict the actions of hostile actors, and players who try to evade or out-smart each other. Modelling how the actions of competitive players shape the decision making of each other is the forte of game theory. In past decades, there have been several studies that applied different branches of game theory to model a range of defence-related scenarios. This paper provides a structured review of such attempts, and classifies existing literature in terms of the kind of warfare modelled, the types of games used, and the players involved. After careful selection, a total of 29 directly relevant papers are discussed and classified. In terms of the warfares modelled, we recognise that most papers that apply game theory in defence settings are concerned with Command and Control Warfare, and can be further classified into papers dealing with (i) Resource Allocation Warfare (ii) Information Warfare (iii) Weapons Control Warfare, and (iv) Adversary Monitoring Warfare. We also observe that most of the reviewed papers are concerned with sensing, tracking, and large sensor networks, and the studied problems have parallels in sensor network analysis in the civilian domain. In terms of the games used, we classify the reviewed papers into papers that use non-cooperative or cooperative games, simultaneous or sequential games, discrete or continuous games, and non-zero-sum or zero-sum games. Similarly, papers are also classified into two-player, three-player or multi-player game based papers. We also explore the nature of players and the construction of payoff functions in each scenario. Finally, we also identify gaps in literature where game theory could be fruitfully applied in scenarios hitherto unexplored using game theory. The presented analysis provides a concise summary of the state-of-the-art with regards to the use of game theory in defence applications and highlights the benefits and limitations of game theory in the considered scenarios.
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Affiliation(s)
- Edwin Ho
- Faculty of Engineering, University of Sydney, Sydney, NSW 2006, Australia;
| | - Arvind Rajagopalan
- Weapons and Combat Systems Division, Defence Science and Technology (DST) Group, Adelaide, SA 5111, Australia;
| | - Alex Skvortsov
- Maritime Division, Defence Science and Technology (DST) Group, Adelaide, SA 5111, Australia; (A.S.); (S.A.)
| | - Sanjeev Arulampalam
- Maritime Division, Defence Science and Technology (DST) Group, Adelaide, SA 5111, Australia; (A.S.); (S.A.)
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3
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Ezanno P, Andraud M, Beaunée G, Hoch T, Krebs S, Rault A, Touzeau S, Vergu E, Widgren S. How mechanistic modelling supports decision making for the control of enzootic infectious diseases. Epidemics 2020; 32:100398. [PMID: 32622313 DOI: 10.1016/j.epidem.2020.100398] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 05/07/2020] [Accepted: 05/29/2020] [Indexed: 12/28/2022] Open
Abstract
Controlling enzootic diseases, which generate a large cumulative burden and are often unregulated, is needed for sustainable farming, competitive agri-food chains, and veterinary public health. We discuss the benefits and challenges of mechanistic epidemiological modelling for livestock enzootics, with particular emphasis on the need for interdisciplinary approaches. We focus on issues arising when modelling pathogen spread at various scales (from farm to the region) to better assess disease control and propose targeted options. We discuss in particular the inclusion of farmers' strategic decision-making, the integration of within-host scale to refine intervention targeting, and the need to ground models on data.
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Affiliation(s)
- P Ezanno
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - M Andraud
- Unité épidémiologie et bien-être du porc, Anses Laboratoire de Ploufragan-Plouzané, Ploufragan, France.
| | - G Beaunée
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - T Hoch
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - S Krebs
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - A Rault
- INRAE, Oniris, BIOEPAR, Site de la Chantrerie, CS40706, 44307 Nantes, France.
| | - S Touzeau
- INRAE, CNRS, Université Côte d'Azur, ISA, France; Inria, INRAE, CNRS, Université Paris Sorbonne, Université Côte d'Azur, BIOCORE, France.
| | - E Vergu
- INRAE, Université Paris-Saclay, MaIAGE, 78350 Jouy-en-Josas, France.
| | - S Widgren
- Department of Disease Control and Epidemiology, National Veterinary Institute, 751 89 Uppsala, Sweden.
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Delabouglise A, Boni MF. Game theory of vaccination and depopulation for managing livestock diseases and zoonoses on small-scale farms. Epidemics 2019; 30:100370. [PMID: 31587878 DOI: 10.1016/j.epidem.2019.100370] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 09/05/2019] [Accepted: 09/05/2019] [Indexed: 11/26/2022] Open
Abstract
Livestock producers adapt their farm management to epidemiological risks in different ways, through veterinary interventions but also by modulating their farm size and the removal rate of animals. The objective of this theoretical study was to elucidate how these behavioral adaptations may affect the epidemiology of highly-pathogenic avian influenza in domestic poultry and the outcome of the implemented control policies. We studied a symmetric population game where the players are broiler poultry farmers at risk of infection and where the between-farms disease transmission is both environmental and mediated by poultry trade. Three types of farmer behaviors were modelled: vaccination, depopulation, and cessation of poultry farming. We found that the transmission level of the disease through trade networks has strong qualitative effects on the system's epidemiological-economic equilibria. In the case of low trade-based transmission, when the monetary cost of infection is high, depopulation behavior can maintain a stable disease-free equilibrium. In addition, vaccination behavior can lead to eradication by private incentives alone - an outcome not seen for human diseases. In a scenario of high trade-based transmission, depopulation behavior has perverse epidemiological effects as it accelerates the spread of disease via poultry trade. In this situation, state interventions should focus on making vaccination technologies available at a low price rather than penalizing infected farms.
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Affiliation(s)
- Alexis Delabouglise
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA 16802, USA.
| | - Maciej F Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
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Hidano A, Enticott G, Christley RM, Gates MC. Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias. Front Vet Sci 2018; 5:137. [PMID: 29977897 PMCID: PMC6021519 DOI: 10.3389/fvets.2018.00137] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 06/04/2018] [Indexed: 11/13/2022] Open
Abstract
Over the past several decades, infectious disease modeling has become an essential tool for creating counterfactual scenarios that allow the effectiveness of different disease control policies to be evaluated prior to implementation in the real world. For livestock diseases, these models have become increasingly sophisticated as researchers have gained access to rich national livestock traceability databases, which enables inclusion of explicit spatial and temporal patterns in animal movements through network-based approaches. However, there are still many limitations in how we currently model animal disease dynamics. Critical among these is that many models make the assumption that human behaviors remain constant over time. As many studies have shown, livestock owners change their behaviors around trading, on-farm biosecurity, and disease management in response to complex factors such as increased awareness of disease risks, pressure to conform with social expectations, and the direct imposition of new national animal health regulations; all of which may significantly influence how a disease spreads within and between farms. Failing to account for these dynamics may produce a substantial layer of bias in infectious disease models, yet surprisingly little is currently known about the effects on model inferences. Here, we review the growing evidence on why these assumptions matter. We summarize the current knowledge about farmers' behavioral change in on-farm biosecurity and livestock trading practices and highlight the knowledge gaps that prohibit these behavioral changes from being incorporated into disease modeling frameworks. We suggest this knowledge gap can be filled only by more empirical longitudinal studies on farmers' behavioral change as well as theoretical modeling studies that can help to identify human behavioral changes that are important in disease transmission dynamics. Moreover, we contend it is time to shift our research approach: from modeling a single disease to modeling interactions between multiple diseases and from modeling a single farmer behavior to modeling interdependencies between multiple behaviors. In order to solve these challenges, there is a strong need for interdisciplinary collaboration across a wide range of fields including animal health, epidemiology, sociology, and animal welfare.
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Affiliation(s)
- Arata Hidano
- EpiCentre, School of Veterinary Science, Massey University, Palmerston North, New Zealand
| | - Gareth Enticott
- Cardiff School of Geography and Planning, Cardiff University, Cardiff, United Kingdom
| | - Robert M. Christley
- Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Neston, United Kingdom
- Institute of Veterinary Science, University of Liverpool, Neston, United Kingdom
| | - M. Carolyn Gates
- EpiCentre, School of Veterinary Science, Massey University, Palmerston North, New Zealand
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Nixon EJ, Rose Vineer H, Wall R. Treatment strategies for sheep scab: An economic model of farmer behaviour. Prev Vet Med 2017; 137:43-51. [PMID: 28107880 PMCID: PMC5292105 DOI: 10.1016/j.prevetmed.2016.12.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Revised: 10/11/2016] [Accepted: 12/22/2016] [Indexed: 01/15/2023]
Abstract
Ovine psoroptic mange (sheep scab) is a debilitating and damaging condition caused by a hypersensitivity reaction to the faecal material of the parasitic mite Psoroptes ovis. Farmers incur costs from the use of prophylactic acaricides and, if their sheep become infected, they incur the costs of therapeutic treatment plus the economic loss from reduced stock growth, lower reproductive rate, wool loss and hide damage. The unwillingness of farmers to use routine prophylactic treatment has been cited as a primary cause of the growing incidence of sheep scab in the United Kingdom (UK) since the disease was deregulated in 1992. However, if farmers behave rationally from an economic perspective, the optimum strategy that they should adopt will depend on the risk of infection and the relative costs of prophylactic versus therapeutic treatment, plus potential losses. This calculation is also complicated by the fact that the risk of infection is increased if neighbours have scab and reduced if neighbours treat prophylactically. Hence, for any farmer, the risk of infection and optimum approach to treatment is also contingent on the behaviour of neighbours, particularly when common grazing is used. Here, the relative economic costs of different prophylactic treatment strategies are calculated for upland and lowland farmers and a game theory model is used to evaluate the relative costs for a farmer and his/her neighbour under different risk scenarios. The analysis shows that prophylaxis with organophosphate (OP) dipping is a cost effective strategy, but only for upland farmers where the risk of infection is high. In all other circumstances prophylaxis is not cost effective relative to reliance on reactive (therapeutic) treatment. Hence, farmers adopting a reactive treatment policy only, are behaving in an economically rational manner. Prophylaxis and cooperation only become economically rational if the risk of scab infection is considerably higher than the current national average, or the cost of treatment is lower. Should policy makers wish to reduce the national prevalence of scab, economic incentives such as subsidising the cost of acaricides or rigorously applied financial penalties, would be required to make prophylactic treatment economically appealing to individual farmers. However, such options incur their own infrastructure and implementation costs for central government.
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Affiliation(s)
- Emily J Nixon
- Veterinary Parasitology and Ecology Group, University of Bristol, Bristol Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ, United Kingdom.
| | - Hannah Rose Vineer
- Veterinary Parasitology and Ecology Group, University of Bristol, Bristol Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ, United Kingdom
| | - Richard Wall
- Veterinary Parasitology and Ecology Group, University of Bristol, Bristol Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ, United Kingdom
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8
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Pettersen J, Brynildsrud O, Huseby R, Rich K, Aunsmo A, Bang BJ, Aldrin M. The epidemiological and economic effects from systematic depopulation of Norwegian marine salmon farms infected with pancreas disease virus. Prev Vet Med 2016; 132:113-124. [DOI: 10.1016/j.prevetmed.2016.09.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 08/31/2016] [Accepted: 09/01/2016] [Indexed: 10/21/2022]
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Salama NKG, Murray AG, Rabe B. Simulated environmental transport distances of Lepeophtheirus salmonis in Loch Linnhe, Scotland, for informing aquaculture area management structures. JOURNAL OF FISH DISEASES 2016; 39:419-428. [PMID: 25929159 DOI: 10.1111/jfd.12375] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2014] [Revised: 02/11/2015] [Accepted: 03/01/2015] [Indexed: 06/04/2023]
Abstract
In the majority of salmon farming countries, production occurs in zones where practices are coordinated to manage disease agents such as Lepeophtheirus salmonis. To inform the structure of zones in specific systems, models have been developed accounting for parasite biology and system hydrodynamics. These models provide individual system farm relationships, and as such, it may be beneficial to produce more generalized principles for informing structures. Here, we use six different forcing scenarios to provide simulations from a previously described model of the Loch Linnhe system, Scotland, to assess the maximum dispersal distance of lice particles released from 12 sites transported over 19 day. Results indicate that the median distance travelled is 6.1 km from release site with <2.5% transported beyond 15 km, which occurs from particles originating from half of the release sites, with an absolute simulated distance of 36 km observed. This provides information suggesting that the disease management areas developed for infectious salmon anaemia control may also have properties appropriate for salmon lice management in Scottish coastal waters. Additionally, general numerical descriptors of the simulated relative lice abundance reduction with increased distance from release location are proposed.
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Affiliation(s)
- N K G Salama
- Marine Scotland Science, Marine Laboratory, Aberdeen, UK
| | - A G Murray
- Marine Scotland Science, Marine Laboratory, Aberdeen, UK
| | - B Rabe
- Marine Scotland Science, Marine Laboratory, Aberdeen, UK
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Barnes AP, Moxey AP, Vosough Ahmadi B, Borthwick FA. The effect of animal health compensation on 'positive' behaviours towards exotic disease reporting and implementing biosecurity: A review, a synthesis and a research agenda. Prev Vet Med 2015; 122:42-52. [PMID: 26422364 DOI: 10.1016/j.prevetmed.2015.09.003] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Revised: 09/03/2015] [Accepted: 09/04/2015] [Indexed: 11/18/2022]
Abstract
With an increasing burden on public sector budgets, increased responsibility and cost sharing mechanisms for animal diseases are being considered. To achieve this, fiscal and non-fiscal intervention policies need to be designed such that they consistently promote positive disease risk management practices by animal keepers. This paper presents a review of the available evidence towards whether and how the level and type of funding mechanism affects change within biosecurity behaviours and the frequency of disease reporting. A Nuffield Health Ladder of Interventions approach is proposed as a way to frame the debate surrounding both current compensation mechanisms and how it is expected to change behaviour. Results of the review reveal a division between economic modelling approaches, which implicitly assume a causal link between payments and positive behaviours, and socio-geographic approaches which tend to ignore the influence of compensation mechanisms on influencing behaviours. Generally, economic studies suggest less than full compensation rates will encourage positive behaviours, but the non-economic literature indicate significant variation in response to compensation reflecting heterogeneity of livestock keepers in terms of their values, goals, risk attitudes, size of operation, animal species and production chain characteristics. This may be of encouragement to Western Governments seeking to shift cost burdens as it may induce greater targeting of non-fiscal mechanisms, or suggest more novel ways to augment current compensation mechanisms to both increase responsibility sharing and reduce this cost burden. This review suggests that a range of regulatory, fiscal and nudging policies are required to achieve socially optimal results with respect to positive behaviour change. However, the lack of directly available evidence which proves these causal links may hinder progress towards this optimal mixture of choice and non-choice based interventions.
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Affiliation(s)
- Andrew Peter Barnes
- Land Economy, Environment and Society Research Group, SRUC, West Mains Road, King's Buildings, EH9 3JG Edinburgh, UK.
| | | | - Bouda Vosough Ahmadi
- Land Economy, Environment and Society Research Group, SRUC, West Mains Road, King's Buildings, EH9 3JG Edinburgh, UK.
| | - Fiona Ann Borthwick
- Land Economy, Environment and Society Research Group, SRUC, West Mains Road, King's Buildings, EH9 3JG Edinburgh, UK.
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