title: Simulations of a mortality plateau in the sexual Penna model for biological aging.
abstract: The Penna model is a strategy to simulate the genetic dynamics of age-structured populations, in which the individual genomes are represented by bit strings. It provides a simple metaphor for the evolutionary process in terms of the mutation accumulation theory. In its original version, an individual dies due to inherited diseases when its current number of accumulated mutations, n, reaches a threshold value T. Since the mean number of diseases increases with age, the probability to die is zero for very young ages (n < T) and equals 1 for the old ones (n > or = T). Here, instead of using a step function to determine the genetic death age, we test several other functions that may or may not slightly increase the death probability at young ages (n < T), but that decrease this probability at old ones. Our purpose is to study the oldest old effect, that is, a plateau in the mortality curves at advanced ages. By imposing certain conditions, it has been possible to obtain a clear plateau using the Penna model. However, a more realistic one appears when a modified version, that keeps the population size fixed without fluctuations, is used. We also find a relation between the birth rate, the age structure of the population, and the death probability.
authors.affiliation: Instituto de Física, Universidade Federal Fluminense, Avenida Litorânea, s/n Boa Viagem, 24210-340, Niterói, Rio de Janeiro, Brazil.
authors.forename: V
authors.initials: V
authors.lastname: Schwämmle
authors.forename: S
authors.initials: S
authors.lastname: Moss de Oliveira
mesh_terms: D000375:Aging / Q000235:genetics*; D000818:Animals; D003198:Computer Simulation; D005260:Female; D005828:Genetics, Population / Q000379:methods*; D006801:Humans; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D011157:Population Dynamics; D012725:Sexual Behavior / Q000502:physiology* / Q000706:statistics & numerical data; D016019:Survival Analysis; D015996:Survival Rate