TY - JOUR

T1 - Optima

T2 - A Model for HIV Epidemic Analysis, Program Prioritization, and Resource Optimization.

AU - Kerr, Cliff C

AU - Stuart, Robyn Margaret

AU - Gray, Richard T

AU - Shattock, Andrew J.

AU - Fraser-Hurt, Nicole

AU - Benedikt, Clemens

AU - Haacker, Markus

AU - Berdnikov, Maxim

AU - Mahmood, Ahmed Mohamed

AU - Jaber, Seham Abdalla

AU - Gorgens, Marelize

AU - Wilson, David P.

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

UR - http://www.ncbi.nlm.nih.gov/pubmed/?term=Gray%20RT%5BAuthor%5D&cauthor=true&cauthor_uid=25803164

U2 - 10.1097/QAI.0000000000000605

DO - 10.1097/QAI.0000000000000605

M3 - Journal article

C2 - 25803164

VL - 69

SP - 365

EP - 376

JO - J A I D S

JF - J A I D S

SN - 1525-4135

IS - 3

ER -