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A Mathematical Model for Assessing Genetic Damage on HIV Populations after Anti-Retroviral Therapy

AZT, an anti-retroviral drug, kills a large proportion of HIV in a patient's body. Those killed tend to be "highly fit"; that is, they are well adapted to the environment of the body and those that survive are poorly fit. As time passes by, the small proportion of strains that survive the medication have a chance of mutating into strains of higher fitness. From this phenomenon, we find a unique angle to analyze these dynamics. Instead of the perspective of the population of HIV strains. Combining genetic algorithms and difference equations, we attempt to assess the genetic damage of one drug on the future generations of survivors. We use the model of difference equations to compare the viral load of the current generation to its predecessors. The genetic algorithms allow us to analyze strains of DNA in terms of binary sequences instead of nucleotides. In the simulations we can analyze the long term behavior of the population against a drug. The goal is to describe a therapy that prevents the population of HIV from exploding.

  • Poster session award recipient at the 1998 National SACNAS Convention in Washington DC

Article Number:
BU-1506-M

Year:
1998

Authors:
Ileana Borjas, Universidad Nacional Autónoma de México
Meera Lea Pradhan, University of Texas
Magnon Ivan Reyes, Florida International University
Kenneth Jeremy Spencer, Texas A&M University

mathematical_model_for_assessing_genetic_damage_on_hiv_populations.pdf