In the noisy Penna model of ageing, instead of counting the number of defective loci which eventually kill an
individual, the noise describing the health status of individuals is introduced. This white noise is composed of
two components: the environmental one and the personal one. If the sum of both trespasses the limit set for
the individuals homeodynamics the individual dies. The energy of personal fluctuations depends on the number
of defective loci expressed in the individuals genome. Environmental fluctuations, the same for all individuals
can include some signals, corresponding to the exposition to pathogens which could be dangerous for a fraction
of the organisms. Personal noise and the component of random environmental fluctuations, when superimposed
on the signal can be life threatening if they are stronger than the limit set for individuals homeodynamics.
Nevertheless, some organisms survive the period of dangerous signal and they may remember the signal in the
future, like antigens are remembered by our immune systems. Unfortunately, this memory weakens with time
and, even worse, some additional defective genes are switched on during the ageing. If the same pathogens
(signals) emerge during the lifespan of the population, a fraction of the population could remember it and could
respond by increasing the resistance to it. Again, unfortunately for some individuals, their memory could be too
weak and their own health status has worsened due to the accumulated mutations, they have to die. Though,
a fraction of individuals can survive the pandemics due to the immune memory, but a fraction of population
has no such a memory because they were born after the last pandemic or they didnt notice this pandemic. Our
simple model, by implementing the noise instead of deterministic threshold of genetic defects, describes how the
impact of pandemics on populations depends on the time which elapsed between the two incidents and how the
different age groups of populations can respond for the second pandemic.
We have modified the standard diploid Penna model of ageing in such a way that instead of threshold of defective
loci resulting in genetic death of individuals, the fluctuation of environment and "personal" fluctuations of
individuals were introduced. The sum of the both fluctuations describes the health status of the individual.
While environmental fluctuations are the same for all individuals in the population, the personal component of
fluctuations is composed of fluctuations corresponding to each physiological function (gene, genetic locus). It is
rather accepted hypothesis that physiological parameters of any organism fluctuate highly nonlinearly. Transition
to the synchronized behaviors could be a very strong diagnostic signal of the life threatening disorder. Thus, in
our model, mutations of genes change the chaotic fluctuations representing the function of a wild gene to the
synchronized signals generated by mutated genes. Genes are switched on chronologically, like in the standard
Penna model. Accumulation of defective genes predicted by Medawar's theory of ageing leads to the replacement
of uncorrelated white noise corresponding to the healthy organism by the correlated signals of defective functions.
As a result we have got the age distribution of population corresponding to the human demographic data.