ArticleMalaria journal2014
Testing a multi-malaria-model ensemble against 30 years of data in the Kenyan highlands.
Article in Malaria journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 25 citations in OpenAlex.
- Impacts of long-term climate change on human health: a global scoping review of quantitative research.BMJ open · 2026Article
- Malaria epidemic and transmission foci in highland of Kisii, western Kenya.Parasite epidemiology and control · 2022Article
- Predicting malaria outbreaks from sea surface temperature variability up to 9 months ahead in Limpopo, South Africa, using machine learning.Frontiers in public health · 2022Article
- Climate-proofing a malaria eradication strategy.Malaria journal · 2021Review
- Modelling for policy: The five principles of the Neglected Tropical Diseases Modelling Consortium.PLoS neglected tropical diseases · 2020Review
- Article
- Using Rainfall and Temperature Data in the Evaluation of National Malaria Control Programs in Africa.The American journal of tropical medicine and hygiene · 2017Article
- Predicting lymphatic filariasis transmission and elimination dynamics using a multi-model ensemble framework.Epidemics · 2017Article
- Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan.PloS one · 2017Article
- An integrated risk and vulnerability assessment framework for climate change and malaria transmission in East Africa.Malaria journal · 2016Article
- Trends in the Mechanistic and Dynamic Modeling of Infectious Diseases.Current epidemiology reports · 2016Review
- 10 Years of Environmental Change on the Slopes of Mount Kilimanjaro and Its Associated Shift in Malaria Vector Distributions.Frontiers in public health · 2016Article
- Predictability of epidemic malaria under non-stationary conditions with process-based models combining epidemiological updates and climate variability.Malaria journal · 2015Article
- Climate, environmental and socio-economic change: weighing up the balance in vector-borne disease transmission.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015Review
- Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.Scientific reports · 2014Article
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Authors and funding
6 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMulti-model ensembles could overcome challenges resulting from uncertainties in models' initial conditions, parameterization and structural imperfections. They could also quantify in a probabilistic way uncertainties in future climatic conditions and their impacts.
methodsA four-malaria-model ensemble was implemented to assess the impact of long-term changes in climatic conditions on Plasmodium falciparum malaria morbidity observed in Kericho, in the highlands of Western Kenya, over the period 1979-2009. Input data included quality controlled temperature and rainfall records gathered at a nearby weather station over the historical periods 1979-2009 and 1980-2009, respectively. Simulations included models' sensitivities to changes in sets of parameters and analysis of non-linear changes in the mean duration of host's infectivity to vectors due to increased resistance to anti-malarial drugs.
resultsThe ensemble explained from 32 to 38% of the variance of the observed P. falciparum malaria incidence. Obtained R²-values were above the results achieved with individual model simulation outputs. Up to 18.6% of the variance of malaria incidence could be attributed to the +0.19 to +0.25°C per decade significant long-term linear trend in near-surface air temperatures. On top of this 18.6%, at least 6% of the variance of malaria incidence could be related to the increased resistance to anti-malarial drugs. Ensemble simulations also suggest that climatic conditions have likely been less favourable to malaria transmission in Kericho in recent years.
conclusionsLong-term changes in climatic conditions and non-linear changes in the mean duration of host's infectivity are synergistically driving the increasing incidence of P. falciparum malaria in the Kenyan highlands. User-friendly, online-downloadable, open source mathematical tools, such as the one presented here, could improve decision-making processes of local and regional health authorities.
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