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Yeka, A., Gasasira, A., Mpimbaza, A., Achan, J., Nankabirwa, J., Nsobya, S., Staedke, S.G., Donnelly, M.J., Wabwire-Mangen, F., Talisuna, A., et al. (2012) Malaria in Uganda: Challenges to Control on the Long Road to Elimination: I. Epidemiology and Current Control Efforts. Acta Tropica, 121, 184-195.
has been cited by the following article:
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TITLE:
Statistical Modeling of Malaria Incidences in Apac District, Uganda
AUTHORS:
Ayo Eunice, Anthony Wanjoya, Livingstone Luboobi
KEYWORDS:
Malaria Incidence, Climate Variables, Poisson Regression, Negative Binomial Regression, Generalized Linear Model, Apac District
JOURNAL NAME:
Open Journal of Statistics,
Vol.7 No.6,
November
16,
2017
ABSTRACT: Malaria is a major cause of morbidity and mortality in Apac district,
Northern Uganda. Hence, the study aimed to model malaria incidences with
respect to climate variables for the period 2007 to 2016 in Apac district. Data
on monthly malaria incidence in Apac district for the period January 2007 to
December 2016 was obtained from the Ministry of health, Uganda whereas climate
data was obtained from Uganda National Meteorological Authority. Generalized
linear models, Poisson and negative binomial regression models were employed to
analyze the data. These models were used to fit monthly malaria incidences as a
function of monthly rainfall and average temperature. Negative binomial model
provided a better fit as compared to the Poisson regression model as indicated
by the residual plots and residual deviances. The Pearson correlation test
indicated a strong positive association between rainfall and malaria incidences.
High malaria incidences were observed in the months of August, September and
November. This study showed a significant association between monthly malaria
incidence and climate variables that is rainfall and temperature. This study
provided useful information for predicting malaria incidence and developing the
future warning system. This is an important tool for policy makers to put in
place effective control measures for malaria early enough.