ArticlePloS one2018
Uncertainty in malaria simulations in the highlands of Kenya: Relative contributions of model parameter setting, driving climate and initial condition errors.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- High resolution physically based modelling reveals malaria incidence reduction by vector control measures.Scientific reports · 2026Article
- Application of remote sensing and geospatial technologies in predicting vector-borne disease outbreaks.Royal Society open science · 2025Review
- Time of Emergence and Future Projections of Extremes of Malaria Infections in Africa.GeoHealth · 2025Article
- Impact of climate change on malaria transmission in Africa: A scoping review of literature.Journal of public health in Africa · 2025Review
- The effect of climate change and temperature extremes onJournal of the Royal Society, Interface · 2024Article
- Climate change, malaria and neglected tropical diseases: a scoping review.Transactions of the Royal Society of Tropical Medicine and Hygiene · 2024Article
- Bias-Corrected CMIP5 Projections for Climate Change and Assessments of Impact on Malaria in Senegal under the VECTRI Model.Tropical medicine and infectious disease · 2023Article
- Understanding the effect of climate change in the distribution and intensity of malaria transmission over India using a dynamical malaria model.International journal of biometeorology · 2021Article
- Projecting the risk of mosquito-borne diseases in a warmer and more populated world: a multi-model, multi-scenario intercomparison modelling study.The Lancet. Planetary health · 2021Article
- Impact of an accelerated melting of Greenland on malaria distribution over Africa.Nature communications · 2021Article
- Climate-proofing a malaria eradication strategy.Malaria journal · 2021Review
- Modelled and observed mean and seasonal relationships between climate, population density and malaria indicators in Cameroon.Malaria journal · 2019Article
- Dynamical Malaria Forecasts Are Skillful at Regional and Local Scales in Uganda up to 4 Months Ahead.GeoHealth · 2019Article
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2 authors.
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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.
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