Prediction of the human life expectancy

TL;DR

This paper uses a Monte Carlo simulation with the Penna model to analyze demographic changes and predict future human life expectancy based on genetic and age structure data.

Contribution

It introduces a simulation approach that accurately models demographic and genetic factors influencing human life expectancy and age distribution.

Findings

Simulated age distributions match real demographic data.

Genetic defect compensation methods significantly increase lifespan.

Population age structure predictions align with observed trends.

Abstract

We have simulated demographic changes in the human population using the Penna microscopic model, based on the simple Monte Carlo method. The results of simulations have shown that during a few generations changes in the genetic pool of a population are negligible, while improving the methods of compensation of genetic defects or genetically determined proneness to many disorders drastically affects the average life span of organisms. Age distribution and mortality of the simulated populations correspond very well to real demographic data available from different countries. Basing on the comparison of structures of real human populations and the results of simulations it is possible to predict changes in the age structure of populations in the future.