A two-step framework combines stacked hurdle random forest models for local severity prediction with semi-parametric spatio-temporal modeling to reconstruct large-scale disease dynamics from imperfect indicators, demonstrated on sugar beet yellows in France.
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Predicting disease severity and large-scale spread from coupled severity measurements and imperfect indicators: Application to beet yellows
A two-step framework combines stacked hurdle random forest models for local severity prediction with semi-parametric spatio-temporal modeling to reconstruct large-scale disease dynamics from imperfect indicators, demonstrated on sugar beet yellows in France.