DIMACS Workshop on Models/Methodological Problems of Botanical Epidemiology
March 16 - 18, 2009
DIMACS Center, CoRE Building, Rutgers University
- Organizers:
- 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.