A Comparative Analysis of the Malthusian Growth Model and Linear Regression Approach In Predicting Malaria Infection
Year: 2025
Type: article
Abstract: The study shows a comparative analysis between the Malthusian growth model and the simple linear regression approach in predicting the outcome of malaria infection. These two models were 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 would be infected with malaria using the regression model would be one hundred and five million (105,000,000) while that of the Malthusian model predicted ninety-one million, five hundred and thirty thousand (91,530,000). Furthermore, results gotten from the 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 the 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 organizations to apply a proactive measure and plan in dealing with the issue of malaria infection in the nation.
Authors: Ekakitie, O., Omamoke, L.
Institutions: Bayelsa Medical University, University of Africa Toru-Orua
Language: English
Topic: Malaria Research and Control
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4415476677