Sampling for disease absence-deriving informed monitoring from epidemic traits

A - Papers appearing in refereed journals

Bourhis, Y., Gottwald, T.R., Lopez-Ruiz, F.J., Patarapuwadol, S. and Van Den Bosch, F. 2019. Sampling for disease absence-deriving informed monitoring from epidemic traits. Journal of Theoretical Biology. 461, pp. 8-16.

AuthorsBourhis, Y., Gottwald, T.R., Lopez-Ruiz, F.J., Patarapuwadol, S. and Van Den Bosch, F.
Abstract

Monitoring for disease requires subsets of the host population to be sampled and tested for the pathogen. If all the samples return healthy, what are the chances the disease was present but missed? In this paper, we developed a statistical approach to solve this problem considering the fundamental property of infectious diseases: their growing incidence in the host population. The model gives an estimate of the incidence probability density as a function of the sampling effort, and can be reversed to derive adequate monitoring patterns ensuring a given maximum incidence in the population. We then present an approximation of this model, providing a simple rule of thumb for practitioners. The approximation is shown to be accurate for a sample size larger than 20, and we demonstrate its use by applying it to three plant pathogens: citrus canker, bacterial blight and grey mould.

KeywordsDisease absence; Risk assessment; Early detection; Sampling theory; Bayes’ Rule
Year of Publication2019
JournalJournal of Theoretical Biology
Journal citation461, pp. 8-16
Digital Object Identifier (DOI)doi:10.1016/j.jtbi.2018.10.038
Open accessPublished as non-open access
Funder project or codeBBSRC Strategic Programme in Smart Crop Protection
FunderBiotechnology and Biological Sciences Research Council
Output statusPublished
Publication dates
Print19 Jan 2019
Online18 Oct 2018
Publication process dates
Accepted17 Oct 2018
Copyright licensePublisher copyright
PublisherAcademic Press Ltd- Elsevier Science Ltd
ISSN0022-5193

Permalink - https://repository.rothamsted.ac.uk/item/84vq8/sampling-for-disease-absence-deriving-informed-monitoring-from-epidemic-traits

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