Population dynamics based on birth intervals and parity progression

Area of Science:

• Demography
• Population Studies
• Mathematical Biology

Background:

• The 'later-longer-fewer' Chinese population policy emphasizes birth intervals and parity.
• Existing population models like Lotka's stable population theory primarily focus on age structure.

Purpose of the Study:

• To propose a novel formulation of population dynamics using birth intervals and parity progression.
• To develop an alternative to Lotka's stable population theory by replacing age with parity and interval since last birth.
• To analyze the effectiveness of this new approach in population projections and data analysis.

Main Methods:

• Formulating population dynamics based on birth interval distributions and parity progression ratios.
• Developing an alternative stable population model where age is replaced by parity and interval since last birth.
• Conducting a numerical comparison between the proposed model and Lotka's model.

Main Results:

• The proposed model provides population projections based on birth interval and parity data.
• A numerical comparison revealed similarities and differences between the new model and Lotka's stable population theory.
• The formulation offers a method to analyze birth interval and parity progression statistics, solving censoring and selection issues.

Conclusions:

• The 'later-longer-fewer' policy can be modeled using birth intervals and parity progression.
• The proposed parity-based model offers a valuable alternative to age-based stable population theory.
• This approach enhances the analysis of demographic data, particularly concerning birth patterns and fertility.