Thirteen challenges in modelling plant diseases | Zendy

Nik J. Cunniffe | Zendy; Britt Koskella | Zendy; C. Jessica E. Metcalf | Zendy; Stephen Parnell | Zendy; T. R. Gottwald | Zendy; Christopher A. Gilligan | Zendy

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Thirteen challenges in modelling plant diseases

Author(s) -

Nik J. Cunniffe,

Britt Koskella,

C. Jessica E. Metcalf,

Stephen Parnell,

T. R. Gottwald,

Christopher A. Gilligan

Publication year - 2014

Publication title -

epidemics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.023

H-Index - 41

eISSN - 1755-4365

pISSN - 1878-0067

DOI - 10.1016/j.epidem.2014.06.002

Subject(s) - selection (genetic algorithm) , disease , plant disease , organism , epidemiology , biology , microbiology and biotechnology , computer science , data science , medicine , pathology , artificial intelligence , paleontology

The underlying structure of epidemiological models, and the questions that models can be used to address, do not necessarily depend on the host organism in question. This means that certain preoccupations of plant disease modellers are similar to those of modellers of diseases in human, livestock and wild animal populations. However, a number of aspects of plant epidemiology are very distinctive, and this leads to specific challenges in modelling plant diseases, which in turn sets a certain agenda for modellers. Here we outline a selection of 13 challenges, specific to plant disease epidemiology, that we feel are important targets for future work.

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