title: Optima: A Model for HIV Epidemic Analysis, Program Prioritization, and Resource Optimization.
abstract: Optima is a software package for modeling HIV epidemics and interventions that we developed to address practical policy and program problems encountered by funders, governments, health planners, and program implementers. Optima's key feature is its ability to perform resource optimization to meet strategic HIV objectives, including HIV-related financial commitment projections and health economic assessments. Specifically, Optima allows users to choose a set of objectives (such as minimizing new infections, minimizing HIV-related deaths, and/or minimizing long-term financial commitments) and then determine the optimal resource allocation (and thus program coverage levels) for meeting those objectives. These optimizations are based on the following: calibrations to epidemiological data; assumptions about the costs of program implementation and the corresponding coverage levels; and the effects of these programs on clinical, behavioral, and other epidemiological outcomes. Optima is flexible for which population groups (specified by behavioral, epidemiological, and/or geographical factors) and which HIV programs are modeled, the amount of input data used, and the types of outputs generated. Here, we introduce this model and compare it with existing HIV models that have been used previously to inform decisions about HIV program funding and coverage targets. Optima has already been used in more than 20 countries, and there is increasing demand from stakeholders to have a tool that can perform evidence-based HIV epidemic analyses, revise and prioritize national strategies based on available resources, set program coverage targets, amend subnational program implementation plans, and inform the investment strategies of governments and their funding partners.
authors: *The Kirby Institute, University of New South Wales, Sydney, Australia; †School of Physics, University of Sydney, Sydney, Australia; ‡Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark; §Global HIV/AIDS Program, World Bank Group, Washington, DC; ‖Harvard School of Public Health, Harvard University, Boston, MA; ¶The Global Fund, Geneva, Switzerland; and #Sudan National HIV/AIDS Control Programme, Khartoum, Sudan.
authors: Cliff C
authors: CC
authors: Kerr
authors: Robyn M
authors: RM
authors: Stuart
authors: Richard T
authors: RT
authors: Gray
authors: Andrew J
authors: AJ
authors: Shattock
authors: Nicole
authors: N
authors: Fraser-Hurt
authors: Clemens
authors: C
authors: Benedikt
authors: Markus
authors: M
authors: Haacker
authors: Maxim
authors: M
authors: Berdnikov
authors: Ahmed Mohamed
authors: AM
authors: Mahmood
authors: Seham Abdalla
authors: SA
authors: Jaber
authors: Marelize
authors: M
authors: Gorgens
authors: David P
authors: DP
authors: Wilson
mesh_terms: D000293:Adolescent; D000328:Adult; D019380:Anti-HIV Agents / Q000627:therapeutic use*; D002648:Child; D003198:Computer Simulation; D003365:Costs and Cost Analysis; D058872:Epidemics / Q000706:statistics & numerical data*; D005260:Female; D015658:HIV Infections / Q000188:drug therapy / Q000191:economics / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D008954:Models, Biological; D009010:Monte Carlo Method; D012984:Software; D013397:Sudan / Q000453:epidemiology; D035501:Uncertainty; D055815:Young Adult
chemical_list: D019380:Anti-HIV Agents