Disease rates vary between different locations particularly in the rural areas. While a database of diseases occurrence could be easily found, studies have been limited to descriptive statistical analysis, and are mostly restricted to diseases affecting adults. This paper therefore presents a Mathematical Model (MM) for predicting immunize-able diseases that affect children between ages 0 -5 years. The model was adapted and deployed for use in six (6) selected localized areas within Osun State in Nigeria. Using the MATLAB's ANN toolbox, the Statistics toolbox for classification and regression, and the Naïve Bayesian classifier the MM was developed. The MM is robust in that it takes advantage of three (3) data mining techniques: ANN, Decision Tree Algorithm and Naïve Bayes Classifier. These data mining techniques provided the means by which hidden information were discovered for detecting trends within databases, and thus facilitate the prediction of future disease occurrence in the tested locations. Results obtained showed that diseases have peak periods depending on their epidemicity, hence the need to adequately administer immunization to the right places at the right time. Therefore, this paper argues that using this model would enhance the effectiveness of routine immunization in Nigeria.
Today, the Internet has further improved the functionalities of computers. A computer and Internet based technology offering a radically different way to manage spatial data is the GIS. Its useful digital maps are needful and very useful in managing healthcare related affairs and communities as well as industry base issues. Therefore, we describe a distributive information system that uses a web-based GIS spatial approach to aid the distribution of tertiary health facilities in Nigeria. The system would assist its users to identify where health care facilities are concentrated, and how and where to locate them anytime. Some of the resources employed in the system's development include: Macromedia dreamweaver, Java Scripting, PHP, MYSQL; the WAMP server; while the UML was used for the system's design. Implementing the system showed that stakeholders were able to visualize the distribution of tertiary hospitals in Nigeria, and make useful inferential decisions with ease. Conclusively, we believe the system will aid in locating the nearest tertiary hospital, as well as help stakeholders make more informed decisions.
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