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Nine different scenarios are considered related to how certain we are that EAB will arrive through known pathways related to wood imports (70%, 50%, 30%) and the probability that EAB would escape at port rather than at the onwards depots (25%, 50%, 75%).  \n\nThe model outputs can be used to predict the best places to locate surveillance technologies (i.e., girdled trees or traps) and included in this dataset are optimised trap locations for 27 scenarios (three trapping types for each of the nine different scenarios). 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We developed maps to identify the most likely first incursion point at locations across Great Britain on a 1km x 1km grid. These maps were informed by data from the forestry commission on likely entry points, and data on firewood use. When creating these maps, we considered nine scenarios related to how certain we are that EAB will arrive through known pathways related to wood imports (70%, 50%, 30%) and the probability that EAB would escape at port rather than at the onwards depots (25%, 50%, 75%).  For each scenario we sampled 10000 realizations for likely entry points.  These form the inputs to our model.\n\nThe model is set up to run for annual time steps for 8 years. For each simulated year the larval density and tree health is recorded in infested cells and reported in output files. The model is currently set up to do this for up to 10000 realizations of entry point. The data in the output file can then be used to optimize surveillance. We did this using simulated annealing for three trapping types (Girdled, sticky straps and under bark sampling) in the nine different scenarios. \n\nThe model code was developed in Visual Studio, but plain text files have been provided so that the code can be compiled and run outside of Visual Studio. The model code was checked for errors and the outputs were validated, as far as possible, against spread characteristics from the US. 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