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Article Dans Une Revue PLoS Computational Biology Année : 2022

How growers make decisions impacts plant disease control

Résumé

While the spread of plant disease depends strongly on biological factors driving transmission, it also has a human dimension. Disease control depends on decisions made by individual growers, who are in turn influenced by a broad range of factors. Despite this, human behaviour has rarely been included in plant epidemic models. Considering Cassava Brown Streak Disease, we model how the perceived increase in profit due to disease management influences participation in clean seed systems (CSS). Our models are rooted in game theory, with growers making strategic decisions based on the expected profitability of different control strategies. We find that both the information used by growers to assess profitability and the perception of economic and epidemiological parameters influence long-term participation in the CSS. Over-estimation of infection risk leads to lower participation in the CSS, as growers perceive that paying for the CSS will be futile. Additionally, even though good disease management can be achieved through the implementation of CSS, and a scenario where all controllers use the CSS is achievable when growers base their decision on the average of their entire strategy, CBSD is rarely eliminated from the system. These results are robust to stochastic and spatial effects. Our work highlights the importance of including human behaviour in plant disease models, but also the significance of how that behaviour is included.
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hal-04069402 , version 1 (14-04-2023)

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Rachel E. Murray-Watson, Frédéric M. Hamelin, Nik J. Cunniffe. How growers make decisions impacts plant disease control. PLoS Computational Biology, 2022, 18 (8), pp.e1010309. ⟨10.1371/journal.pcbi.1010309⟩. ⟨hal-04069402⟩
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