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Research Article |

Bayesian Kernel Machine Analysis of Communicable Diseases Distribution in Machakos County, Kenya

Effective management and control of communicable diseases are paramount for healthcare managers. Data-driven analysis plays a crucial role in understanding and curbing the spread of such diseases. While numerous epidemiological models have been developed to explain disease spread, many lack the incorporation of prior and posterior probabilities. In this research, we introduce a novel model called BKMR, designed to analyze and predict communicable disease occurrences in Machakos County. This study underscores the significance of data-driven approaches and outlines a plan to evaluate prediction accuracy through empirical analysis, with a particular focus on comparing BKMR with existing models using the R statistical software. We highlight the differences between estimated parameters and actual observations, emphasizing aspects not present in the training dataset. Our findings demonstrate that BKMR outperforms the Poisson regression model, offering greater flexibility and robustness. Moreover, it provides the ability to quantify uncertainty in model parameters, enhancing the capacity to make inferences about the real world. This research has substantial implications for healthcare management and disease control efforts in Machakos County.

Communicable Diseases, Data Driven Analysis, Health-Care Managers, Epidemiological Models, Prior Probabilities, Posterior Probabilities, BKMR, Poisson Distribution

APA Style

Cecilia Mbithe Titus, Anthony Wanjoya, Thomas Mageto. (2023). Bayesian Kernel Machine Analysis of Communicable Diseases Distribution in Machakos County, Kenya. International Journal of Data Science and Analysis, 9(2), 43-49. https://doi.org/10.11648/j.ijdsa.20230902.13

ACS Style

Cecilia Mbithe Titus; Anthony Wanjoya; Thomas Mageto. Bayesian Kernel Machine Analysis of Communicable Diseases Distribution in Machakos County, Kenya. Int. J. Data Sci. Anal. 2023, 9(2), 43-49. doi: 10.11648/j.ijdsa.20230902.13

AMA Style

Cecilia Mbithe Titus, Anthony Wanjoya, Thomas Mageto. Bayesian Kernel Machine Analysis of Communicable Diseases Distribution in Machakos County, Kenya. Int J Data Sci Anal. 2023;9(2):43-49. doi: 10.11648/j.ijdsa.20230902.13

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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