Network models for soybean rust epidemics: Adapting to aerially-dispersed pathogens
PIs: Karen Garrett, Caterina Scoglio, Bala Natarajan; students: Sweta Sutrave, Mohammad Reza Sanatkar.
Modeling plant disease epidemics at large scales calls for several adaptations of network models. For example, information about soybean rust is typically available from sentinel plots that function to represent a larger area such as a county. Furthermore, many plant pathogens are capable of long-distance aerial dispersal, so that distant nodes may be connected with a small but non-zero probability. We have already begun developing network models to forecast soybean rust in the US using the sentinel plot data for model construction and validation. We utilize the host abudance data of Soybean and also Kudzu which acts as a reservoir for the pathogen. We also incorporated the wind data as rust propagates through spores carried by the wind.
Presentations & Publications
- S. Sutrave, DYNAMIC NETWORK MODELS OF A CONTINENTAL EPIDEMIC: SOYBEAN RUST IN THE USA, Master of Science Thesis, 2010,
- S. Sutrave, C. Scoglio, S. A. Isard, J. M. S. Hutchinson, and K. A. Garrett
"Identifying highly connected counties compensates for resource limitations when evaluating national spread of an invasive pathogen"
PLoS ONE, Accepted for publication, 2012