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Article Open Access January 19, 2024

Modelling Population Growth Prognosis

Emmanuel Akaligwo 1,*, Boniface Aharanwa 2 and Joshua Aderotimi 2
1
Department of Mathematics, Federal University Lokoja, Kogi State, Nigeria
2
Department of Mathematics/Statistics, Imo State Polytechnic Omuma, Imo State, Nigeria
Publihed in: Current Research in Public Health (Volume 2, Issue 1, 2024)
Page(s): 28-36
DOI: 10.31586/jml.2024.846
Received
December 09, 2023
Revised
January 10, 2024
Accepted
January 18, 2024
Published
January 19, 2024
Keywords
Census; Population Growth; Carrying Capacity; Population Size
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2024. Published by Scientific Publications
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Cite This Article

APA Style
Akaligwo, E. , Aharanwa, B. , & Aderotimi, J. (2024). Modelling Population Growth Prognosis. Current Research in Public Health, 2(1), 28-36. https://doi.org/10.31586/jml.2024.846
ACS Style
Akaligwo, E. ; Aharanwa, B. ; Aderotimi, J. Modelling Population Growth Prognosis. Current Research in Public Health 2024 2(1), 28-36. https://doi.org/10.31586/jml.2024.846
Chicago/Turabian Style
Akaligwo, Emmanuel, Boniface Aharanwa, and Joshua Aderotimi. 2024. "Modelling Population Growth Prognosis". Current Research in Public Health 2, no. 1: 28-36. https://doi.org/10.31586/jml.2024.846
AMA Style
Akaligwo E, Aharanwa B, Aderotimi J. Modelling Population Growth Prognosis. Current Research in Public Health. 2024; 2(1):28-36. https://doi.org/10.31586/jml.2024.846 
@Article{crph846,
AUTHOR = {Akaligwo, Emmanuel and Aharanwa, Boniface and Aderotimi, Joshua},
TITLE = {Modelling Population Growth Prognosis},
JOURNAL = {Current Research in Public Health},
VOLUME = {2},
YEAR = {2024},
NUMBER = {1},
PAGES = {28-36},
URL = {https://www.scipublications.com/journal/index.php/JML/article/view/846},
ISSN = {2831-5162},
DOI = {10.31586/jml.2024.846},
ABSTRACT = {Logistic growth model and its variants have been adjudged to be the most appropriate model for forecasting human population. However, in this article, we estimated the carrying capacity of Abuja using the logistic model. Then, we presented the parameters used to ascertain that the logistic model has the best fit in modelling population growth of Abuja over time. Meanwhile, a population growth sensitivity analysis is presented for the year 1962 to 2200.The result shows that by the year 2050, Abuja population growth rate will be out of control, if nothing substantial is implemented. Similarly, from the year 2150, the results show that stability will return again. Furthermore, the result of the error analysis conducted on the logistic model shows that Abuja has a growing population and that logistic growth model with MAPE and RMSE values of 0.98% and 7,817.07 respectively is the most accurate. The study concludes that logistic growth model with R−squared value of 0.776 has the best fit for population growth projection of Abuja. With approximate growth rate at 9.3% per annum, the projected population of Abuja will hit 30,220,701 million by the year 2039 all things being equal. Therefore, we recommend that the government should invest in massive agricultural reforms to accommodate the growing population, expand Abuja by developing its suburbs, and engage in massive reorientation of the populace on the dangers of uncontrolled births and the education of the girl child.},
}
%0 Journal Article
%A Akaligwo, Emmanuel
%A Aharanwa, Boniface
%A Aderotimi, Joshua
%D 2024
%J Current Research in Public Health

%@ 2831-5162
%V 2
%N 1
%P 28-36

%T Modelling Population Growth Prognosis
%M doi:10.31586/jml.2024.846
%U https://www.scipublications.com/journal/index.php/JML/article/view/846

TY  - JOUR
AU  - Akaligwo, Emmanuel
AU  - Aharanwa, Boniface
AU  - Aderotimi, Joshua
TI  - Modelling Population Growth Prognosis
T2  - Current Research in Public Health
PY  - 2024
VL  - 2
IS  - 1
SN  - 2831-5162
SP  - 28
EP  - 36
UR  - https://www.scipublications.com/journal/index.php/JML/article/view/846
AB  - Logistic growth model and its variants have been adjudged to be the most appropriate model for forecasting human population. However, in this article, we estimated the carrying capacity of Abuja using the logistic model. Then, we presented the parameters used to ascertain that the logistic model has the best fit in modelling population growth of Abuja over time. Meanwhile, a population growth sensitivity analysis is presented for the year 1962 to 2200.The result shows that by the year 2050, Abuja population growth rate will be out of control, if nothing substantial is implemented. Similarly, from the year 2150, the results show that stability will return again. Furthermore, the result of the error analysis conducted on the logistic model shows that Abuja has a growing population and that logistic growth model with MAPE and RMSE values of 0.98% and 7,817.07 respectively is the most accurate. The study concludes that logistic growth model with R−squared value of 0.776 has the best fit for population growth projection of Abuja. With approximate growth rate at 9.3% per annum, the projected population of Abuja will hit 30,220,701 million by the year 2039 all things being equal. Therefore, we recommend that the government should invest in massive agricultural reforms to accommodate the growing population, expand Abuja by developing its suburbs, and engage in massive reorientation of the populace on the dangers of uncontrolled births and the education of the girl child.
DO  - Modelling Population Growth Prognosis
TI  - 10.31586/jml.2024.846
ER  -