DIMACS Workshop on Models/Methodological Problems of Botanical Epidemiology

March 16 - 18, 2009
DIMACS Center, CoRE Building, Rutgers University

Chris Gilligan, Cambridge, cag1@cus.cam.ac.uk
Presented under the auspices of the Special Focus on Computational and Mathematical Epidemiology.

This workshop will gather experts from the botanical epidemiology and genetics communities together with mathematicians interested in modeling using differential equations, discrete systems, and stochastic processes to investigate modeling and methodological problems of spread of disease in plants. The workshop is motivated by biological questions: How can we model: (1) invasion and persistence of plant disease in spatially-extended and heterogeneous environments, and the consequences for optimizing the spatial and temporal deployment of resistance genes; minimizing the risk of pesticide resistance; prediction of crop loss and yield; (2) the effects of changing agricultural practices (use of GM technology, change of farm, field size and landscape mosaic) and changing climate on host (crop), parasite, vectors and antagonist (biocontrol agents) dynamics; (3) the interplay between population genetics, population dynamics and epidemiology. We will confront a variety of modeling issues, including the need to construct a suite of models for spatially-extended dynamics that: goes across heterogeneous scales (from microscopic behavior in soil (porous medium) or in a plant, through single infected plants to a disease patch, multiple patches, field, region and continental scales); includes periodic forcing (due to seasonal change); involves temporally disturbed environments (with abrupt changes due to sowing, harvest and switching on and off of favorable periods for transmission); and deals with quenched systems (as host susceptibility changes with host age). Other issues include: scaling from individual to population behavior; development and testing of stochastic models for the evolution of probability distributions within and between replicate epidemics with and without; model reduction, including perturbation and asymptotics. The workshop will investigate modeling approaches including ode, pde, individual-based models including percolation, random graph, stochastic, spatially-explicit and spatially-implicit (moment closure and pairwise approximation) and metapopulation models. We will also discuss data and model testing issues, such as parameter estimation for spatially-explicit and spatially-implicit models with and without unobserved compartments; data collection for model testing and parameter estimation from lattice crops, row crops, continuum and mosaics; optimization of experimental design for parameter estimation and model discrimination; and analysis of microcosm data to distinguish demographic and environmental stochasticity.
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Document last modified on January 17, 2007.