title: The impact of monitoring HIV patients prior to treatment in resource-poor settings: insights from mathematical modelling.
abstract: BACKGROUND
  The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa.
  
  
  RESULTS
  We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (> or = 35 y) and most immune-suppressed patients (CD4(+) cell count < or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART.
  
  
  CONCLUSIONS
  The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.
authors.affiliation: Department of Infectious Disease Epidemiology, Imperial College London, United Kingdom. timothy.hallett@imperial.ac.uk
authors.forename: Timothy B
authors.initials: TB
authors.lastname: Hallett
authors.forename: Simon
authors.initials: S
authors.lastname: Gregson
authors.forename: Sabada
authors.initials: S
authors.lastname: Dube
authors.forename: Geoff P
authors.initials: GP
authors.lastname: Garnett
mesh_terms: D000328:Adult; D044966:Anti-Retroviral Agents / Q000008:administration & dosage*; D018791:CD4 Lymphocyte Count; D018450:Disease Progression; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D008962:Models, Theoretical; D040841:Resource Allocation; D013269:Stochastic Processes
chemical_list: D044966:Anti-Retroviral Agents