A Comparative Analysis of the Malthusian Growth Model and Linear Regression Approach in Predicting Malaria Infection.
Publication Date: 23/10/2025
Author(s): Ekakitie Omamoke, Omamoke Layefa.
Volume/Issue: Volume 8, Issue 4 (2025)
Page No: 33-43
Journal: African Journal of Mathematics and Statistics Studies (AJMSS)
Abstract:
The study shows a comparative analysis between Malthusian growth model and simple linear regression approach in predicting the outcome of malaria infection. These two models was applied in predicting the number of persons infected with malaria in Nigeria in the nearest future (2023 to 2030) using data from 2019 to 2022. The outcome revealed that at the end of 2030 the population of persons that will be infected with malaria using the regression model was One hundred and five million (105, 000, 000) while that of Malthusian model was Ninety one million, five hundred and thirty (91, 530, 000). Furthermore, results gotten from Malthusian model proved to be more reliable than the results gotten from the regression model because the coefficient of correlation and Residual sum of squares for Malthusian model was 0.999 and 1801670629370.527 with the data showing a level of statistical significance compared to the simple linear regression model approach which was 1.00 and 0.00 respectively. This research will assist government organizations; non-government organizations, private and health organization to apply a proactive measure and plan in dealing with the issue of malaria infection in the nation
Keywords:
Regression, Malthusian Model, Malaria, Comparative Analysis, Sum of Squares.
