Mathematical Modeling and Predicting the Current Trends of Human Population Growth in Bangladesh

Mathematical Modeling and Predicting the Current Trends of Human Population Growth in Bangladesh

Hironmoy Mondol Uzzwal Kumar Mallick Md. H.A. Biswas

Mathematics Discipline, Khulna University, Khulna 9208, Bangladesh

Corresponding Author Email:
25 April 2018
28 May 2018
30 June 2018
| Citation



Bangladesh is an overpopulated and the most densely populated country. It is the world's eighth-most populous country in south Asia with over 160 million people. Population problem in Bangladesh is one of the most burning issues in the recent years. So the increasing trend in population is a great threat to the nation and for this reason, the projection of the population of Bangladesh is essential. The purpose of this paper is to model and design the population growth in Bangladesh to predict the future population size. The exponential and the logistic growth models are applied to predict the population of Bangladesh during 1980 to 2080 using the actual data from 1980 to 2016. By using the exponential growth model, the predicted growth rate has been estimated approximately 2.67% and the population of Bangladesh has been predicted to be 1191 million in 2080. We have determined the carrying capacity (K) and vital coefficients and for the population prediction in vein of logistic growth model. Thus, the population growth rate of Bangladesh according to the logistic model has been estimated approximately 4.03% and the total population of Bangladesh has been predicted to be 245 million in 2080.


exponential growth model, logistic population model, carrying capacity, population growth, vital coefficient

1. Introduction
2. Methodology
3. Results and Discussions
4. Conclusions

We thank the editor and the reviewers for their useful suggestions which have improved the quality of this paper.


[1] Akçakaya HR, Gulve PS. (2000). Population viability analysis in conservation planning: An overview. Ecological Bulletins 48: 9–21.

[2] Biswas MHA, Ara M, Haque MN, Rahman MA. (2011). Application of control theory in the efficient and sustainable forest management. International Journal of Scientific & Engineering Research 2(3): 26–33.

[3] Biswas MHA, Paiva LT, Pinho MD. (2014). A SEIR model for control of infectious diseases with constraints. Mathematical Biosciences and Engineering 11(4): 761–784. 

[4] Biswas MHA. (2014). Optimal control of nipah virus (niv) infections: a bangladesh scenario. Journal of Pure and Applied Mathematics: Advances and Applications 12(1): 77–104.

[5] Biswas MHA. (2012). Model and control strategy of the deadly nipah virus (NiV) infections in Bangladesh. Research & Reviews in BioSciences 6(12): 370–377.

[6] Cohen JE. (1995). Population growth and earth’s human carrying capacity. American Association for the Advancement of Science 269(5222): 341–346.

[7] Deshotel D. (2013). Modeling World Population. Available at dhicketh/DiffEqns/spring13projects/Population%20Model%20Project%202013/PopulationModels2013.pdf.

[8] Edwards CH, Penney DE. (2004). Differential equations and boundary value problems computing and modeling. 3rd Edition, Pearson Education Inc.

[9] Farid KS, Ahamed JU, Sharma PK, Begum S. (2011). Population dynamics in bangladesh: data sources, current facts and past trends. J Bangladesh Agriculture University 9(1): 121–130. 

[9] Haque MM, Ahamed F, Anam S, Kabir MR. (2012). Future population projection of bangladesh by growth rate modeling using logistic population model. Annals of Pure and Applied Mathematics 1(2): 192–202.

[10] Islam MR. (2011). Modeling and predicting cumulative population of Bangladesh. American Journal of Computational and Applied Mathematics 1(2): 98–100.

[11] Islam T, Fiebig DG, Meade N. (2002). Modelling multinational telecommunications demand with limited data. International Journal of Forecasting 18: 605–624.

[12] Koya PR, Goshu AT. (2013). Generalized mathematical model for biological growths. Open Journal of Modelling and Simulation 1: 42–53. 

[13] Malthus TR. (1893). An Essay on the Principle of Population (1st edition, plus excepts 1893 2nd edition). Introduction by Philip Appeman, and assorted commentary on Malthus edited by Appleman, Norton Critical Edition.

[14] Mahsin M, Hossain SS. (2012). Population forecasts for Bangladesh, using a bayesian methodology. Journal of Health, Population and Nutrition 30(4): 456–463.

[15] Murray JD. (1989). Mathematical Biology. 2nd edition, Springer–Verlag Berlin.

[16] Ofori T, Ephraim L, Nyarko F. (2013). Mathematical modeling of Ghana’s population growth. International Journal of Modern Management Sciences 2(2): 57–66.

[17] Omale D, Gochhait S. (2018). Analytical solution to the mathematical models of HIV/AIDS with control in a heterogeneous population using Homotopy Perturbation Method (HPM). AMSE journals-AMSE IIETA-Series: Advances A 55(1): 20-34.

[18] Pozzi F, Small C, Yetman G. (2002). Modeling the distribution of human population with night-time satellite imagery and gridded population of the world. Proceedings of Pecora 15/Land Satellite Information IV/ISPRS Commission I/FIEOS Conference.

[19] Roy B, Roy SK. (2015). Analysis of prey-predator three species models with vertebral and invertebral predators. International Journal Dynamics and Control 3: 306–312.

[20] Roy SK, Roy B. (2016). Analysis of prey-predator three species fishery model with harvesting including prey refuge and migration. International Journal of Bifurcation and Chaos 26(1650022).

[21] Sardar AK, Hanif M, Asaduzzaman M, Biswas MHA. (2016). Mathematical analysis of the two species lotka-volterra predator-prey inter-specific game theoretic competition model. Advanced Modeling and Optimization 18(2): 231-242. 

[22] Shen J, Tang S, Xu C. (2017). Analysis and research  on home-based care for the aged based on insurance policy under government leading. AMSE journals-AMSE IIETA-Series: Advances A 54(1): 106-126.

[23] Tsoularis A. (2001). Analysis of logistic growth models. Res. Lett. Inf. Math. Sci. 2: 23–46.

[24] The World Bank Population Report. Available at

[25] Wali A, Ntubabare D, Mboniragira V. (2011). Mathematical modeling of rwanda’s population growth. Applied Mathematical Science 5(53): 2617–2628.

[26] Wali A, Kagoyire E, Icyingeneye P. (2012). Mathematical modeling of Uganda’s population growth. Applied Mathematical Science 6(84): 4155–4168.