VECTRI simulations of malaria incidence in the highlands of Kenya, accounting for climate, model and initial condition uncertainty using a genetic algorithm framework

10.1594/PANGAEA.890161Tompkins, Adrian MarkAdrian MarkTompkins0000-0003-0975-6691Thomson, Madeleine CMadeleine CThomsonVECTRI simulations of malaria incidence in the highlands of Kenya, accounting for climate, model and initial condition uncertainty using a genetic algorithm frameworkPANGAEA2018File contentFile nameFile formatFile sizeUniform resource locator/link to fileSupplementary Dataset10.1371/journal.pone.020063815 data pointstext/tab-separated-valuesCreative Commons Attribution 3.0 UnportedThe 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. http://www.gitlab.com/tompkins/vectri).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), e020063838.01.0Africa, Kenya