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History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust

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Title History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust
 
Creator Sanatkar M
Scoglio, Caterina
Natarajan S
Isard, S.
Garrett, K.A.
 
Subject climate change
agriculture
 
Description Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.
 
Date 2015-07
2015-11-27T09:15:40Z
2015-11-27T09:15:40Z
 
Type Journal Article
 
Identifier Sanatkar M, Scoglio C, Natarajan B, Isard S, Garrett K. 2015. History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust. Phytopathology 105(7): 947-955.
0031-949X
1943-7684
https://hdl.handle.net/10568/69031
https://doi.org/10.1094/PHYTO-12-14-0353-FI
 
Language en
 
Rights Open Access
 
Format 947-955
 
Publisher Scientific Societies
 
Source Phytopathology