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Modeling spatiotemporal dynamics and time to...

Modeling spatiotemporal dynamics and time to regional outbreaks of soybean rust in southern Brazil

Emerson M. Del Ponte

August 20, 2020
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  1. Modeling spatiotemporal dynamics and time to regional outbreaks of soybean

    rust in southern Brazil Kaique Alves | Adam Sparks | Emerson Del Ponte
  2. Follow up: now using 15 years - SBR prevalence All

    years (2005 - 2019) 2 States (south) PR and RS Commercial soybean fields First (date) report in a county 2,027 records ~15,000 records PR RS
  3. Epidemic time MaxPrev AUDPC r Time_10 10% Prev90 Prev120 Temporal

    progress description / analysis Time to outbreak (Survival analysis)
  4. Conclusions • Large scale spatiotemporal spread varies among seasons and

    states • Multiple inoculum sources affect initial epidemic area • Early- and mid- season weather plays a major role • ENSO conditions useful as early warning Tactical Strategical Pre-season Growing season Risk prediction Outlook Forecasting Warning What's next? Develop models for predicting and mapping disease risk at the regional level Thank you! @edelponte