A.N.M. Rezaul Karim Mohammed Nizam Uddin Masud Rana Mayeen Uddin Khandaker M. R. I. Faruque Sofi Mahmud Parvez


The biggest challenge in the world is population growth and determining how society and the state adapt to it as it directly affects the fundamental human rights such as food, clothing, housing, education, medical care, etc. The population estimates of any country play an important role in making the right decision about socio-economic and population development projects. Unpredictable population growth can be a curse. The purpose of this research article is to compare the accuracy process and proximity of three mathematical model such as Malthusian or exponential growth model, Logistic growth model and Least Square model to make predictions about the population growth of Bangladesh and India at the end of 21st century. Based on the results, it has been observed that the population is expected to be 429.32(in million) in Bangladesh and 3768.53 (in million) in India by exponential model, 211.70(in million) in Bangladesh and 1712.94(in million) in India by logistic model and 309.28 (in million) in Bangladesh and 2686.30 (in million) in India by least square method at the end of 2100. It was found that the projection data from 2000 to 2020 using the Logistic Growth Model was very close to the actual data. From that point of view, it can be predicted that the population will be 212 million in Bangladesh and 1713 million in India at the end of the 21st century. Although transgender people are recognized as the third sex but their accurate statistics data is not available. The work also provides a comparative scenario of how the state has adapted to the growing population in the past and how they will adapt in the future.


Download data is not yet available.


Metrics Loading ...




Adaptation, Basic human needs, Mathematical modeling, Population growth

Ali, L. E., Khan, B. R., and Sams, I. S. (2015). Brief study on census and predicted population of Bangladesh using Logistic population model. Annals of Pure and Applied Mathematics, 10(1) : 41–47
BBS) (2011. Population census- 2011. Preliminary report. Bangladesh Bureau of Statistics (BBS), Ministry of Planning, Dhaka
BBS (2018). Bangladesh Sample Vital Statistics. National Volume-3 : Urban Area Report. Bangladesh Bureau of Statistics (BBS), Bangladesh
Brauer, F. Castillo-Ch! avez, C. (2001). Mathematical models in population biology and epidemiology. Texts in Applied Mathematics, volume no 40., DOI: 10.1007/978-1-4757-3516-1
Census (2011). Primary census abstracts, Registrar General of India, Ministry of Home Affairs, Government of India, Available at: http://www.censusindia.gov. in/2011ce nsus/PCA/pca_highlights/pe_data.
Cohen, J. (1995). Human carrying capacity. Science. http://ehsapes.pbworks.com/f/Population%2BGrowth%2B%26%2BEarth’s%2BHuman%2BCarrying%2BCapacity.pdf
Dawed, M. Y., Koya, P. R., and Goshu, A. T. (2014). Mathematical modelling of population growth: The case of Logistic and Von bertalanffy models. Open Journal of Modelling and Simulation, 02 (04) : 113–126 https://doi.org/10.4236/ojmsi.2014.24013
Islam, N. (1997). Addressing the urban poverty agenda in Bangladesh. Critical issues and the 1995 Survey findings, Dhaka: University Press Ltd.
Kerry, C. C., Tessy, S., Ezeora, J. N., and Iweanandu, O. J. (2017). A comparative study of mathematical and statistical models for population projection of Nigeria. 8(2) : 777–785.
Kulkarni, S., R Kulkarni, S., and J Patil, S. (2014). Analysis of Population Growth of India and Estimation for Future. International Journal of Innovative Research in Science, Engineering and Technology, 03(09) : 15843–15850. https://doi.org/10.15680/ijirset.2014.0309008
Law, R., Murrell, D. J., &Dieckmann, U. (2003). Population growth in space and time: spatial logistic equations. Ecology, 84 (1) : 252-262.
Mondol, H., Mallick, U. K., & Biswas, M. H. A. (2018). Mathematical modeling and predicting the current trends of human population growth in Bangladesh. Advances in Modelling and Analysis A, 55(2) : 62–69. https://doi.org/10.18280/ama_a.550204
Ofori, T., Ephraim, L., Nyarko, F., Keshtavar, A., Moeinaddin, M., Dehnavi, H. D., ... &Oladejo, N. K. (2013). Mathematical Model of Ghana’s Population Growth. International Journal of Modern Management Sciences, 2(2), 57-66.
PCA (2011). Primary census abstract for total population and houseless population, office of the Registrar general and census commissioner, India
Rosario, G. M., and Antony, M. J. (2017). Mathematical Model for Future Popu-lation Scenario In India And China–An Econometric Approach. International Journal of Scientific & Engineering Research, 8(5) : 62.
Rahman, S. (2010). Six decades of agricultural land use change in Bangladesh : effects on crop diversity, productivity, food availability and the environment,1948-2006. Singapore Journal of Tropical Geography, 31: 245-269
Report on Bangladesh sample vital statistics (2018). Bangladesh Bureau of Statistics (BBS), Statistics and Informatics Division (SID), Ministry of Planning, Dhaka
Shepherd, J. J., and Stojkov, L. (2007). The logistic population model with slowly varying carrying capacity. ANZIAM Journal, 47: 492. https://doi.org/10.21914/anziamj.v47i0.1058
Simon, J., and Malthus, T. R. (2018). An Essay on the principle of population as it affects the future improvement of society (First Edition). The Economics of Population, 219–222. https://doi.org/10.4324/9781351291521-31
Wali, A. N., Ntubabare, D., and Mboniragira, V. (2011). Mathematical modeling of Rwanda’s population growth. Appl. Math. Sci.,5(53): 2617 – 2628
Wali, A., Kagoyire, E., &Icyingeneye, P. (2012). Mathematical modeling of Uganda population growth. Applied Mathematical Sciences, 6(81–84) : 4155–4168.
World Bank (2020). Poverty and shared prosperity-2020. Reversals of fortune. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/34496 License: CC BY 3.0 IGO.”
WEO (2020). A Long and Difficult Ascent. World economic outlook (WEO) report, International Monetary Fund. October 2020 retrieved from https://www.imf.org/en/Publications/WEO/Issues/2020/09/30/world-economic-outlook-october-2020
Citation Format
How to Cite
Rezaul Karim, A. ., Nizam Uddin, M. ., Rana, M. ., Khandaker, M. U. ., Faruque , M. R. I. ., & Parvez, S. M. . (2020). Modeling on population growth and its adaptation: A comparative analysis between Bangladesh and India. Journal of Applied and Natural Science, 12(4), 688-701. https://doi.org/10.31018/jans.v12i4.2396
More Citation Formats:
Research Articles

Most read articles by the same author(s)