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Uncertainty in malaria simulations in the highlands of Kenya: Relative contributions of model parameter setting, driving climate and initial condition errors

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  • Adrian M Tompkins
  • Madeleine C Thomson

Abstract

In this study, experiments are conducted to gauge the relative importance of model, initial condition, and driving climate uncertainty for simulations of malaria transmission at a highland plantation in Kericho, Kenya. A genetic algorithm calibrates each of these three factors within their assessed prior uncertainty in turn to see which allows the best fit to a timeseries of confirmed cases. It is shown that for high altitude locations close to the threshold for transmission, the spatial representativeness uncertainty for climate, in particular temperature, dominates the uncertainty due to model parameter settings. Initial condition uncertainty plays little role after the first two years, and is thus important in the early warning system context, but negligible for decadal and climate change investigations. Thus, while reducing uncertainty in the model parameters would improve the quality of the simulations, the uncertainty in the temperature driving data is critical. It is emphasized that this result is a function of the mean climate of the location itself, and it is shown that model uncertainty would be relatively more important at warmer, lower altitude locations.

Suggested Citation

  • Adrian M Tompkins & Madeleine C Thomson, 2018. "Uncertainty in malaria simulations in the highlands of Kenya: Relative contributions of model parameter setting, driving climate and initial condition errors," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-27, September.
  • Handle: RePEc:plo:pone00:0200638
    DOI: 10.1371/journal.pone.0200638
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    1. D. A. Stainforth & T. Aina & C. Christensen & M. Collins & N. Faull & D. J. Frame & J. A. Kettleborough & S. Knight & A. Martin & J. M. Murphy & C. Piani & D. Sexton & L. A. Smith & R. A. Spicer & A. , 2005. "Uncertainty in predictions of the climate response to rising levels of greenhouse gases," Nature, Nature, vol. 433(7024), pages 403-406, January.
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    1. Maria Chara Karypidou & Vasiliki Almpanidou & Adrian M. Tompkins & Antonios D. Mazaris & Sandra Gewehr & Spiros Mourelatos & Eleni Katragkou, 2020. "Projected shifts in the distribution of malaria vectors due to climate change," Climatic Change, Springer, vol. 163(4), pages 2117-2133, December.

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