A - Papers appearing in refereed journals

Sampling for disease absence-deriving informed monitoring from epidemic traits

 

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
Publication dates
Print19 Jan 2019
Online18 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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Under embargo until 18 Oct 2019

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