Surveillance to inform control of emerging plant diseases; an epidemiological perspective

Authors: PARNELL, STEPHEN - University Of Salford; VAN DEN BOSCH, FRANK - Rothamsted Research; Gottwald, Timothy; GILLIGAN, CHRISTOPHER - University Of Cambridge

Submitted to: Annual Review of Phytopathology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/5/2017
Publication Date: 5/21/2017
Citation: Parnell, S., Van Den Bosch, F., Gottwald, T.R., Gilligan, C.A. 2017. Surveillance to inform control of emerging plant diseases; an epidemiological perspective. Annual Review of Phytopathology. 55:591-610.

Interpretive Summary: Recent times have seen a dramatic rise in the number of emerging diseases of plants associated with a range of natural and human influences. Pathogens have been introduced to new geographic areas by human movement of infected material, long range wind dispersal of inoculum, and changes in climate that favor pathogen establishment in areas where it was not possible before. New strains of pathogens have also emerged to overcome previously-effective disease control methods and unfavorable environmental conditions. The impacts on crop production and food security have been extreme. The authors have collaborated for the past three decades on surveillance (survey) method and theory to locate and find exotic invasive diseases quickly prior to spread so the control and/or eradication efforts can be effective and optimized. For this reason, the authors were invited to contribute a review of surveillance methods and models. Surveillance involves the collection and analysis of information relating to plant disease epidemics and is crucial for detection and successful control of emerging diseases and emerging strains of endemic diseases. In this review we describe the recent history of the development and extension of statistically relevant methods and models with examples for each. The challenges of early detection and assessment of invasion are substantial for plant disease. The motivation in writing this review is to show how epidemiological insight about the dynamics of disease spread can be used to improve the effectiveness of disease surveillance strategies for emerging epidemics.

Technical Abstract: In order to design an effective surveillance strategy for a particular objective, we need to understand when, where and how disease is likely to occur, at what intensity, and, crucially, to use this information to identify how many sites should be surveyed, how often and where. We can begin to do this using standard statistical approaches that use probability distributions to capture the intensity and variability of disease and relate this to sampling effort. We illustrate some elementary yet powerful statistical approaches to identify the sampling effort required to achieve particular levels of confidence in a surveillance plan. The statistical approaches involve certain simplifying assumptions about epidemic dynamics. We explore how relaxing some of these assumptions to allow for temporal and spatial dynamics of epidemics can improve the flexibility of the statistical approach. This leads naturally to consideration of the use of stochastic, spatially explicit simulation models to inform surveillance schemes by simulating the dynamics of emerging epidemics across heterogeneous landscapes under varying environmental conditions.