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Statistical Modeling of Malaria Incidences in Apac District, Uganda

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Document pages: 19 pages

Abstract: Malaria is a major cause of morbidity and mortality in Apac district,Northern Uganda. Hence, the study aimed to model malaria incidences withrespect to climate variables for the period 2007 to 2016 in Apac district. Dataon monthly malaria incidence in Apac district for the period January 2007 toDecember 2016 was obtained from the Ministry of health, Uganda whereas climatedata was obtained from Uganda National Meteorological Authority. Generalizedlinear models, Poisson and negative binomial regression models were employed toanalyze the data. These models were used to fit monthly malaria incidences as afunction of monthly rainfall and average temperature. Negative binomial modelprovided a better fit as compared to the Poisson regression model as indicatedby the residual plots and residual deviances. The Pearson correlation testindicated a strong positive association between rainfall and malaria incidences.High malaria incidences were observed in the months of August, September andNovember. This study showed a significant association between monthly malariaincidence and climate variables that is rainfall and temperature. This studyprovided useful information for predicting malaria incidence and developing thefuture warning system. This is an important tool for policy makers to put inplace effective control measures for malaria early enough.

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