title: Achieving NHAS 90/90/80 Objectives by 2020: An Interactive Tool Modeling Local HIV Prevalence Projections.
abstract: BACKGROUND
  Tools using local HIV data to help jurisdictions estimate future demand for medical and support services are needed. We present an interactive prevalence projection model using data obtainable from jurisdictional HIV surveillance and publically available data.
  
  
  METHODS
  Using viral load data from Georgia's enhanced HIV/AIDS Reporting System, state level death rates for people living with HIV and the general population, and published estimates for HIV transmission rates, we developed a model for projecting future HIV prevalence. Keeping death rates and HIV transmission rates for undiagnosed, in care/viral load >200, in care/viral load<200, and out of care (no viral load for 12 months) constant, we describe results from simulations with varying inputs projecting HIV incidence and prevalence from 2014 to 2024.
  
  
  RESULTS
  In this model, maintaining Georgia's 2014 rates for diagnosis, transitions in care, viral suppression (VS), and mortality by sub-group through 2020, resulted in 85% diagnosed, 59% in care, and 44% VS among diagnosed (85%/58%/44%) with a total of 67 815 PLWH, 33 953 in care, and more than 1000 new cases per year by 2020. Neither doubling the diagnosis rate nor tripling rates of re-engaging out of care PLWH into care alone were adequate to reach 90/90/80 by 2020. We demonstrate a multicomponent scenario that achieved NHAS goals and resulted in 63 989 PLWH, 57 546 in care, and continued annual prevalence increase through 2024.
  
  
  CONCLUSIONS
  Jurisdictions can use this HIV prevalence prediction tool, accessible at https://dph.georgia.gov/hiv-prevalence-projections to assess local capacity to meet future HIV care and social services needs. In this model, achieving 90/90/80 by 2020 in Georgia slowed but did not reverse increases in HIV prevalence, and the number of HIV-infected persons needing care and support services more than doubled. Improving the HIV care infrastructure is imperative.
authors.affiliation: Georgia Department of Public Health, Division of Health Protection, HIV/AIDS Epidemiology, Atlanta, Georgia, United States of America.
authors.forename: Jane M
authors.identifier: http://orcid.org/0000-0001-7946-7049
authors.initials: JM
authors.lastname: Kelly
authors.affiliation: Department of Mechanical Engineering and Engineering Science, University of North Carolina at Charlotte, Charlotte, United States of America.
authors.forename: Scott D
authors.initials: SD
authors.lastname: Kelly
authors.affiliation: Georgia Department of Public Health, Division of Health Protection, HIV/AIDS Epidemiology, Atlanta, Georgia, United States of America.
authors.forename: Pascale M
authors.initials: PM
authors.lastname: Wortley
authors.affiliation: Georgia Department of Public Health, Division of Health Protection, HIV/AIDS Epidemiology, Atlanta, Georgia, United States of America.
authors.forename: Cherie L
authors.initials: CL
authors.lastname: Drenzek
mesh_terms: D000465:Algorithms; D005845:Georgia / Q000453:epidemiology; D015658:HIV Infections / Q000453:epidemiology* / Q000635:transmission / Q000821:virology; D006801:Humans; D015994:Incidence; D008962:Models, Theoretical; D009026:Mortality; D011159:Population Surveillance / Q000379:methods; D015995:Prevalence; D040442:Public Health Informatics / Q000379:methods*; D012984:Software; D019562:Viral Load; D064878:Web Browser