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Journal Articles Royal Society Open Science Year : 2018

Using sensitivity analysis to identify key factors for the propagation of a plant epidemic

Abstract

Identifying the key factors underlying the spread of a disease is an essential but challenging prerequisite to design management strategies. To tackle this issue, we propose an approach based on sensitivity analyses of a spatiotemporal stochastic model simulating the spread of a plant epidemic. This work is motivated by the spread of sharka, caused by plum pox virus, in a real landscape. We first carried out a broad-range sensitivity analysis, ignoring any prior information on six epidemiological parameters, to assess their intrinsic influence on model behaviour. A second analysis benefited from the available knowledge on sharka epidemiology and was thus restricted to more realistic values. The broad-range analysis revealed that the mean duration of the latent period is the most influential parameter of the model, whereas the sharka-specific analysis uncovered the strong impact of the connectivity of the first infected orchard. In addition to demonstrating the interest of sensitivity analyses for a stochastic model, this study highlights the impact of variation ranges of target parameters on the outcome of a sensitivity analysis. With regard to sharka management, our results suggest that sharka surveillance may benefit from paying closer attention to highly connected patches whose infection could trigger serious epidemics.
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hal-02621209 , version 1 (26-05-2020)

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Loup Rimbaud, Claude Bruchou, Sylvie Dallot, David Pleydell, Emmanuel Jacquot, et al.. Using sensitivity analysis to identify key factors for the propagation of a plant epidemic. Royal Society Open Science, 2018, 5 (1), pp.171435. ⟨10.1098/rsos.171435⟩. ⟨hal-02621209⟩
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