Optimising and Communicating Options for the Control of Invasive Plant Disease When There Is Epidemiological Uncertainty

Abstract

Although local eradication is routinely attempted following introduction of disease into a new region, failure is commonplace. Epidemiological principles governing the design of successful control are not well-understood. We analyse factors underlying the effectiveness of reactive eradication of localised outbreaks of invading plant disease, using citrus canker in Florida as a case study, although our results are largely generic, and apply to other plant pathogens (as we show via our second case study, citrus greening). We demonstrate how to optimise control via removal of hosts surrounding detected infection (i.e. localised culling) using a spatially-explicit, stochastic epidemiological model. We show how to define optimal culling strategies that take account of stochasticity in disease spread, and how the effectiveness of disease control depends on epidemiological parameters determining pathogen infectivity, symptom emergence and spread, the initial level of infection, and the logistics and implementation of detection and control. We also consider how optimal culling strategies are conditioned on the levels of risk acceptance/aversion of decision makers, and show how to extend the analyses to account for potential larger-scale impacts of a small-scale outbreak. Control of local outbreaks by culling can be very effective, particularly when started quickly, but the optimum strategy and its performance are strongly dependent on epidemiological parameters (particularly those controlling dispersal and the extent of any cryptic infection, i.e. infectious hosts prior to symptoms), the logistics of detection and control, and the level of local and global risk that is deemed to be acceptable. A version of the model we developed to illustrate our methodology and results to an audience of stakeholders, including policy makers, regulators and growers, is available online as an interactive, user-friendly interface at http://www.webidemics.com/. This version of our model allows the complex epidemiological principles that underlie our results to be communicated to a non-specialist audience. Author Summary: Increases in global trade and travel suggest outbreaks of plant disease caused by invasive pathogens will increase in frequency. We use mathematical modelling to show how control of such disease outbreaks can be optimised. Although our methods and analyses are generic, we use the attempted eradication of citrus canker from Florida (1996–2006) as a case study, and focus upon the performance of reactive culling (i.e. removal of all host plants within a certain distance of detected infection). We show how the cull radius can be optimised, even when there is significant cryptic infection (i.e. infection without visible symptoms). The inherent randomness of disease transmission implies a control strategy can lead to a number of outcomes: the optimal strategy therefore depends on the level of risk that is tolerable. We also consider balancing local vs. global impacts of disease. We show how it can be optimal to control initial outbreaks very extensively, even though this would lead to many local removals, since timely local eradication reduces the risk of a devastating large-scale epidemic. Our model is available as an interactive, user-friendly interface at http://www.webidemics.com/, intended to illustrate the sometimes counter-intuitive epidemiological principles that underlie successful disease control.

Publication information

Originally published in PLOS Computational Biology on 2015-04-13. Original DOI: 10.1371/journal.pcbi.1004211.

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