Modelling malaria transmission dynamics in irrigated areas of Tana River County, Kenya
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Muriuki, J., Kitala, P., Muchemi, G. and Bett, B. 2014. Modelling malaria transmission dynamics in irrigated areas of Tana River County, Kenya. Poster presented at the fifth South African Centre for Epidemiological Modelling and Analysis (SACEMA) annual clinic on the meaningful modelling of epidemiological data, Muizenberg, Cape Town, South Africa, 2-13 June 2014. Nairobi, Kenya: ILRI.
Permanent link to cite or share this item: http://hdl.handle.net/10568/41593
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Development of irrigation schemes is usually associated with escalation of the malaria problem. Mathematical models can be used to explain the effects of irrigation on malaria transmission dynamics. This study aimed at developing and validating a one-host one-vector deterministic model made up of a mosquito population sub-module and disease transmission sub-module. Model parameters were obtained from the literature. Data covering the year 2013 were collected and these included the amount of irrigation water per unit area of irrigated land, rainfall, temperature and prevalence of malaria from the local hospitals. The Fuzzy distribution function was used to relate rainfall and irrigation patterns with oviposition and mortality rates of acquatic stages of mosquitoes. The model was fitted to malaria prevalence data obtained from the local hospitals by varying the parameters of the Fuzzy distribution function. Parameter values that gave the least variance between predicted and observed prevalence were used. The model was implemented in MS Excel using difference equations.The model fitted the data well and predicts an upsurge in the number of malaria cases 2-3 months after the rains or active irrigation. The model could be used to predict the prevalence of malaria in this area enabling decision makers to implement appropriate control measures in good time. Data from non-irrigated areas and covering a longer period of time should be collected for more rigorous model validation and simulation of the effectiveness of various the interventions.