An improved delimiting survey approach for Xylella fastidiosa
The EU plant health legislation enforces the implementation of intensive surveillance programs for Xylella fastidiosa (Xf) as a quarantine pathogen (Commission Implementing Regulation (EU) 2020/1201). After a Xf outbreak, delimiting surveys must be implemented to delineate the extent of the pathogen and to execute disease control. The surveillance efficacy can be enhanced by increasing inspection and sampling intensities. Budget constraints often limit survey efforts, thus making it necessary the optimization of surveillance strategies. A sequential adaptive delimiting survey involving a three-phase and a two-phase design with increasing spatial resolution was simulated for the Xf demarcated area in Alicante, Spain. Based on the official survey data of 2018, inspection and sampling intensities were estimated using an optimization algorithm specified under the sequential adaptive delimiting strategy. The sampling intensity thresholds estimated were evaluated by quantifying their effect on the estimation of Xf incidence. This strategy made it possible to sequence inspection and sampling considering increasing spatial resolutions, and to adapt the inspection and sampling intensities according to the information obtained in the previous, coarser, spatial resolution. Our results show that sequencing and adapting inspection and sampling to increasing spatial resolutions allows accurate delimitation of the infested zone while reducing the overall survey efforts, thus improving the efficiency of the surveillance program. From a methodological perspective, our approach provides new insights into alternative delimiting designs and new reference sampling intensity values. Pre-print published at: https://www.biorxiv.org/content/10.1101/2020.03.05.978668v2 ; ES; PPT; lazaro_ele@gva.es