Pandemics and immune memory in the noisy Penna model

In the noisy Penna model of ageing, instead of counting the number of defective loci which eventually kill anindividual, the noise describing the health status of individuals is introduced. This white noise is composed oftwo components: the environmental one and the personal one. If the sum of both trespasses the limit set forthe individuals homeodynamics the individual dies. The energy of personal ”uctuations depends on the numberof defective loci expressed in the individuals genome. Environmental ”uctuations, the same for all individualscan include some signals, corresponding to the exposition to pathogens which could be dangerous for a fractionof the organisms. Personal noise and the component of random environmental ”uctuations, when superimposedon 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 thefuture, like antigens are remembered by our immune sy stems. Unfortunately, this memory weakens with timeand, 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 couldrespond by increasing the resistance to it. Again, unfortunately for some individuals, their memory could be tooweak 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 populationhas no such a memory because they were born after the last pandemic or they didnt notice this pandemic. Oursimple model, by implementing the noise instead of determi nistic threshold of genetic defects, describes how theimpact of pandemics on populations depends on the time which elapsed between the two incidents and how thedierent age groups of populations can respond for the second pandemic.Keywords: Pandemics, ageing, Monte Carlo simulation, population evolution.