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Outbreak response to quarantine pathogens and pests in the European Union (EU) is regulated by the EU Plant Health Law, but the performance of outbreak management plans in terms of their effectiveness and efficiency has been quantified only to a limited extent. As a case study, the disease dynamics of almond leal' scorch, caused by Xylella fastidiosa, in the affected area of Alicante, Spain, were approximated using an individual-based spatial epidemiological model. The emergence of this outbreak was dated based on phylogenetic studies, and official surveys were used to delimit the current extent of thé disease. Different survey strategies and disease control measures were compared to determine their effectiveness and efficiency for outbreak management in relation to a baseline scenario without interventions. One-step and two-step survey approaches were compared with different confidence levels, buffer zone sizes, and eradication radii, including those set by the EU legislation for X. fastidiosa. The effect of disease control interventions was also considered by decreasing the transmission rate in the buffer zone. All outbreak management plans reduced the number of infected trees (effectiveness), but large differences were observed in the number of susceptible trees not eradicated (efficiency). The two-step survey approach, high confidence level, and the reduction in lhe transmission rate increased the efficiency. Only the outbreak management plans with the two-step survey approach removed infected trees completely, but they required greater survey efforts. Although control measures reduced disease spread, surveillance was the key factor in the effectiveness and efficiency of the outbreak management plans. [ABSTRACT FROM AUTHOR]

Red leaf blotch (RLB) of almond, caused by the ascomycete Polystigma amygdalinum , is a severe foliar disease endemic in the Mediterranean Basin and Middle East. Airborne ascospores of P. amygdalinum were monitored from 2019 to 2021 in two almond orchards in Lleida, Spain, and a Bayesian beta regression was used to model its seasonal dynamics. The selected model incorporated accumulated degree-days (ADD), ADD considering both vapor pressure deficit and rainfall as fixed effects, and a random effect for the year and location. The performance of the model was evaluated in 2022 to optimize RLB fungicide programs by comparing the use of model predictions and action thresholds with the standard program. Two variants were additionally considered in each program to set the frequency between applications, based on (i) a fixed frequency of 21 days or (ii) specific meteorological criteria (spraying within 7 days after rainfalls greater than 10 mm, with daily mean temperatures between 10 and 20°C, and with a minimum frequency of 21 days between applications). Programs were evaluated in terms of RLB incidence and number of applications. The program based on the model with periodic fungicide applications was similarly effective as the standard program, resulting only in a 2.6% higher RLB incidence but with fewer applications (three to four, compared with seven in the standard program). When setting the frequency between applications by using the meteorological criteria, a higher reduction in the number of applications (two to three) was observed, while RLB incidence increased by roughly 16% in both programs. Therefore, the model developed in this study may represent a valuable tool toward a more sustainable fungicide schedule for the control of almond RLB in northeast Spain., Competing Interests: The author(s) declare no conflict of interest.