The output is simulated cases per 1000 population for a highland location in the Kenyan highlands. Each file represents a single ensemble member integration of the model in the final generation of the genetic algorithm calibration method outlined in the paper. The global meta data gives the set of parameters used to define this run, as well as the exact version of the model code used (ref.
gitlab.com). Supplement to: Tompkins, Adrian Mark; Thomson, Madeleine C (2018): Uncertainty in malaria simulations in the highlands of Kenya: Relative contributions of model parameter setting, driving climate and initial condition errors. PLoS ONE, 13(9), e0200638