The EU plant health legislation enforces the implementation of intensive surveillance programs for quarantine pests. After an outbreak, surveys are implemented to delimit the extent of the infested zone and to manage disease control. Surveillance in agricultural and natural environments can be enhanced by increasing the survey efforts. Budget constraints often limit inspection and sampling intensities, thus making it necessary to adapt 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 demarcated area in Alicante, Spain. Inspection and sampling intensities were optimized using simulation-based methods. Sampling intensity thresholds were evaluated by quantifying their effect on the estimation of X. fastidiosa incidence. This strategy made it possible to sequence inspection and sampling taking into account increasing spatial resolutions, and to adapt the inspection and sampling intensities according to the information obtained in the previous, coarser, spatial resolution. The proposed strategy was able to efficiently delimit the extent of Xylella fastidiosa, while improving on the efficiency and maintaining the efficacy of the official survey campaign. From a methodological perspective, our approach provides new insights into alternative delimiting designs and new reference sampling intensity values.

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.

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