Location: Subtropical Plant Pathology Research
Title: Estimating the spatial distribution of a plant disease epidemic when it is first discovered and the design of early detection monitoring Authors
|Parnell, S -|
|Gilks, W -|
|Van Den Bosch, F -|
Submitted to: Journal of Theoretical Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 12, 2012
Publication Date: March 28, 2012
Repository URL: http://dx.doi.org/10.1016/j.jtbi.2012.03.009
Citation: Parnell, S., Gottwald, T.R., Gilks, W.R., Van Den Bosch, F. 2012. Estimating the spatial distribution of a plant disease epidemic when it is first discovered and the design of early detection monitoring. Journal of Theoretical Biology. 305: 30-36. Interpretive Summary: When new plant diseases are discovered that are impacting crops, one of the first things that is needed is a method to survey and sample for the disease, in order to determine its prevalence and distribution and decide on appropriate control or eradication measures. Unfortunately, very often little to no information is know about the disease and the way it is distributed in affected fields or orchards. In this paper we present a method that can estimate the characteristics of how the disease is distributed in the field from a single observation. This information can then be used to develop a sampling method that can be used by researchers and regulatory agencies to find the disease in the region and enable them to make policy/regulatory decisions quickly.
Technical Abstract: The early detection of an invading epidemic is crucial for successful disease control. Although models have been used extensively to test control strategies following the first detection of an epidemic, few studies have addressed the issue of how to achieve early detection in the first place. Moreover, sampling theory has made great progress in understanding how to estimate the incidence or spatial distribution of an epidemic but how to sample for early detection has been largely ignored. Using a simple epidemic model we demonstrate a method to calculate the incidence of an epidemic when it is discovered for the first time (given a monitoring program taking samples at regular intervals). We use the method to explore how the intensity and frequency of sampling influences early detection. In particular, we find that for epidemics characterized by high population growth rates it is most effective to spread sampling resources evenly in time. In addition we derive a useful approximation to our method which results in a simple equation capturing the relation between monitoring and epidemic dynamics. Not only does this provide valuable new insight but it provides a simple rule of thumb for the design of monitoring programs in practice.