Authors:
Elena Lázaro; Miriam Sesé; Antonio López-Quílez; David Conesa; Vicente Dalmau; Amparo Ferrer-Matoses; Antonio Vicent.
Posted:
March 06, 2020.
Abstract:
Current legislation enforces the implementation of intensive surveillance programs for quarantine plant pathogens. After an outbreak, surveys are implemented to delimit the geographic extent of the pathogen and execute disease control. However, the feasibility of control programs is seriously compromised by the limited efficiency of the current surveillance strategies. A sequential adaptive delimiting survey involving a three-phase and a two-phase design with increasing spatial resolution was developed and implemented for the case study of Xylella fastidiosa in Alicante, Spain. Inspection and sampling intensities were optimized using simulation-based methods and results were validated using Bayesian spatial models. This strategy made it possible to sequence inspection and sampling considering different spatial resolutions, and to adapt the inspection and sampling intensity according to the information obtained in the previous, coarser, spatial resolution. The proposed strategy was able to delimit efficiently the extent of Xf improving efficiency of the current in terms of survey efforts. From a methodological perspective, our approach provides new insights of alternative delimiting designs and new reference sampling intensity values.