Summary
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. The feasibility of control programs is highly dependent on budget availability, thus it is necessary to target and optimize 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 Xylella fastidiosa outbreak 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.
Footnotes
New section "Data and Code availability" has been added to indicate the url direction in which data and code are published to reproduce manuscript analyses; New section "Supplementary Material" has beed added to list all Figures and Tables showed in the Supplementary Material tab.
https://bitbucket.org/elaher/xylellafastidiosa_reproducibleresearch/src