[Life expectancy and its modeling]

Area of Science:

• Biogerontology
• Mathematical Biology
• Population Dynamics

Background:

• Understanding organismal aging and lifespan is crucial in biology.
• Existing models often focus on individual organisms, with less emphasis on population-level dynamics.
• The transition from individual to population-level aging models requires careful consideration of demographic properties.

Purpose of the Study:

• To present and discuss two distinct models for organismal lifespan: "natural technology" and a homeostatic aging model.
• To investigate the mathematical transition from modeling an individual organism to modeling cohorts and populations.
• To identify the minimal properties required for accurate cohort and population aging simulations.

Main Methods:

• Development of a "natural technology" model for organism lifespan.
• Formulation of a homeostatic model of aging.
• Mathematical analysis of transitions between individual, cohort, and population modeling frameworks.
• Simulation examples for individual, cohort, and population aging.

Main Results:

• The "natural technology" and homeostatic models provide frameworks for understanding limited lifespan.
• Modeling a cohort requires only the property of death occurrence in an organism.
• Modeling a population with overlapping generations necessitates two properties: the ability to die and the ability to reproduce.
• Demonstrated successful modeling of individual organisms, cohorts, and populations.

Conclusions:

• The study successfully models organism lifespan and aging.
• Key demographic properties (death, reproduction) are identified as critical for scaling from individual to population-level aging models.
• The findings provide a foundation for more complex population dynamics and evolutionary studies.