title: A stochastic model for primary HIV infection: optimal timing of therapy.
abstract: OBJECTIVE
  To investigate the optimal time point for the initiation of therapy in HIV infection from the perspective of drug resistance.
  
  
  BACKGROUND
  The enormous genetic diversity of HIV within an infected individual represents one of the greatest challenges for effective therapy, because the viral population may harbour drug-resistant mutants that rapidly outgrow the wild-type virus once the patient starts treatment. To determine the optimal timing of therapy it is crucial to know how long it takes for the viral population to build up sufficient diversity to enable the virus to escape from therapy.
  
  
  METHODS
  A stochastic model of the viral diversification during primary infection was used to study the behaviour of small population sizes of mutant virus.
  
  
  CONCLUSIONS
  The simulations suggest that from the perspective of viral diversity, therapy should be started at the viral set-point. Starting treatment earlier involves a risk of the selective outgrowth of drug-resistant mutants, which are transiently present at the viral peak during primary infection.
authors: Welcome Trust Centre for Epidemiology and Infectious Disease, Department of Zoology, University of Oxford, UK.
authors: R M
authors: RM
authors: Ribeiro
authors: S
authors: S
authors: Bonhoeffer
mesh_terms: D019380:Anti-HIV Agents / Q000627:therapeutic use*; D004352:Drug Resistance, Microbial / Q000235:genetics*; D015658:HIV Infections / Q000188:drug therapy* / Q000821:virology; D015497:HIV-1 / Q000187:drug effects / Q000235:genetics*; D006801:Humans; D009154:Mutation; D013269:Stochastic Processes; D013997:Time Factors; D014766:Viremia / Q000821:virology; D014779:Virus Replication
chemical_list: D019380:Anti-HIV Agents