Estimation And Prediction Of Malaria Occurance In The Community Of Micheal Okpara University Of Agriculture, Umudike Using Interpolation Methodology:- Azuogu Chidiebube G

ABSTRACT viii Malaria remains one ofthe leading public health challenges in Nigeria, particularly in communities where environmental conditions favour mosquito breeding. Accurate estimation and prediction of malaria occurrence are essential for effective planning and disease control; however, incomplete health records often limit reliable analysis. This study focused on the estimation and prediction of malaria occurrence in the Michael Okpara University of Agriculture, Umudike (MOUAU), Abia State, using interpolation methodology. Malaria case data obtained from the university health centre served as the basis forthe analysis. Newton’s Forward Interpolation Formula was employed to estimate missing malaria cases within the available data, while Newton’s Backward Interpolation Formula was used to predict future malaria occurrences. The analysis showed that interpolation techniques effectively estimated missing values and revealed a declining trend in malaria occurrence during the early years ofthe study, followed by an increasing trend in the later years. The predicted results indicate that malaria remains a significant public health concern within the university community and underscore the need for sustained surveillance and preventive interventions. The study concludes that interpolation methods are reliable numerical tools for estimating incomplete epidemiological data and predicting disease trends where continuous records are unavailable. It is recommended that healthcare institutions improve data collection systems and adopt electronic health record management to enhance the accuracy offuture disease surveillance and prediction.