Modelling Malaria Incidence Using Poisson Generalized Linear Model: A Case Study Of Mbita Sub-County, Kenya

Malaria continues to pose a major threat to public health across the world, particularly in African countries where infection rate s remain high. Nearly half of the global population is exposed to the risk of contracting the disease. Malaria is caused by parasites belonging to the Plasmodium family and affects both humans and other warm-blooded animals. Over the years, researchers have explored different causes of malaria transmission using techniques such as spatial analysis, time series methods and regression models. Although these methods are useful, they are less suitable when the data set involved are categorical or count variables. This study used Poisson Generalized Linear Model to investigate factors associated with malaria incidence in Mbita Sub-county. The variables considered included treated mosquito bed net use, age group, educational level of household heads and access to healthcare services. The Poisson Generalized Linear Model was fitted having estimated its parameters. The findings showed that treated mosquito net usage, age group, and access to healthcare facilities were statistically significant. The educational background of the household head was not significant. The association between the exploratory variables and the response variable was determined by use of the Chi-square test.The results indicated that there was an association between mosquito bed net use and malaria, age group and malaria, education level of family head and malaria and finally healthcare access and malaria. The goodness of fit was conducted by the use of deviance statistic. A comparison between the null model and the full model was done and this resulted into a p-value of 0.001871, which was below the 0.05 significance threshold. As a result, the null hypothesis was rejected, indicating that additional exploratory variable improve the model. This suggests that the full model together with additional parameters significantly improves the fit of the model to the data. The study’s findings reinforce existing evidence that the use of treated mosquito bed net use plays an important role in lowering malaria infections. organizations that handle matters in relation to health and environment such as World Health Organization and United Nations may apply the outcome to aid in developing mechanisms to lower the spread of malaria within Mbita Sub-county and other parts of the world with similar settings.

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Journal
American Journal of Theoretical and Applied Statistics
Published
2026-06-12
DOI
https://doi.org/10.11648/j.ajtas.20261503.12
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
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article

Modelling Malaria Incidence Using Poisson Generalized Linear Model: A Case Study Of Mbita Sub-County, Kenya

Martin M. Kithinji, Samuel Okinyi, Joseph Esekon
American Journal of Theoretical and Applied Statistics
Malaria Research and Control
article

Modelling Malaria Incidence Using Poisson Generalized Linear Model: A Case Study Of Mbita Sub-County, Kenya

Martin M. Kithinji, Samuel Okinyi, Joseph Esekon
article en

Abstract

Malaria continues to pose a major threat to public health across the world, particularly in African countries where infection rate s remain high. Nearly half of the global population is exposed to the risk of contracting the disease. Malaria is caused by parasites belonging to the Plasmodium family and affects both humans and other warm-blooded animals. Over the years, researchers have explored different causes of malaria transmission using techniques such as spatial analysis, time series methods and regression models. Although these methods are useful, they are less suitable when the data set involved are categorical or count variables. This study used Poisson Generalized Linear Model to investigate factors associated with malaria incidence in Mbita Sub-county. The variables considered included treated mosquito bed net use, age group, educational level of household heads and access to healthcare services. The Poisson Generalized Linear Model was fitted having estimated its parameters. The findings showed that treated mosquito net usage, age group, and access to healthcare facilities were statistically significant. The educational background of the household head was not significant. The association between the exploratory variables and the response variable was determined by use of the Chi-square test.The results indicated that there was an association between mosquito bed net use and malaria, age group and malaria, education level of family head and malaria and finally healthcare access and malaria. The goodness of fit was conducted by the use of deviance statistic. A comparison between the null model and the full model was done and this resulted into a p-value of 0.001871, which was below the 0.05 significance threshold. As a result, the null hypothesis was rejected, indicating that additional exploratory variable improve the model. This suggests that the full model together with additional parameters significantly improves the fit of the model to the data. The study’s findings reinforce existing evidence that the use of treated mosquito bed net use plays an important role in lowering malaria infections. organizations that handle matters in relation to health and environment such as World Health Organization and United Nations may apply the outcome to aid in developing mechanisms to lower the spread of malaria within Mbita Sub-county and other parts of the world with similar settings.

American Journal of Theoretical and Applied StatisticsVol. 15(3)
Kirinyaga University (KE)
Openalex Percentile: Top 5%
Malaria Research and Control
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