Modeling the Effects of Social Factors on Population Dynamics Using Age-Structured System

The study of demographics is important not only for policy formulation but also for better understanding of human socio-economic characteristics, and assessment of effects of human activities on environmental impact. It is interesting to note that apart from the common population control strategies, industrialization, economic development and improvement of living standards affects population growth parameters. In this paper, an age-structured model was formulated to model population dynamics, and make predictions through simulation using 2019 Kenya population data. The age-structured mathematical model was developed, using partial differential equations on population densities as functions of age and time. The population was structured into 20 clusters each of 5 year interval, and assigned different birth, death rate and transition parameters. Crank-Nicolson numerical scheme was used to simulate the model using the 2019 parameters and population as initial conditions. It was found that; provision of social factors to an efficacy level of δ≥0.75 to a minimum of 70% population leads to a decrease of mortality rate form μ<sub>old</sub>=0.0313 to μ<sub>new</sub>=0.00184 and an increase in birth rate from β<sub>old</sub>=0.02639 to β<sub>new</sub>=0.05104. This collectively leads to an increase in population by 50% from 38,589,011 to 57,956,100 after 35 years. The initial economic dependency ratio of 1:2, was also improved due to changes in technology and improvement of living standards, to a new ratio of 1:1.14. The graphical presentation in form of a pyramid showed a trend of transition from expansive to constrictive population pyramid. This population structure is stable and remains relatively constant as long as the social factors are maintained.