OR Modeling and AIDS Policy: From Theory to Practice

Abstract

The AIDS epidemic is a serious, growing public health problem worldwide, but resources for treating HIV-infected patients and for combating the spread of the virus are limited. Governments, public-health agencies, and health-care providers must determine how best to allocate scarce resources for HIV treatment and prevention among different programs and populations. OR-based models have influenced—and can influence—AIDS policy decisions. Mathematical modeling has had an effect on AIDS policy in a number of areas, including estimating HIV prevalence and incidence in the United States, understanding the pathophysiology of HIV, evaluating costs and benefits of HIV-screening programs, evaluating the effects of needle-exchange programs, and determining policies for HIV/AIDS care in California. Further work is needed to model a range of programs using comparable methods, to model overall epidemic control strategy, and to improve the usefulness of OR-based models for policy making.

Resource allocation for HIV/AIDS control programs: a model-based policy analysis

“…General surveys of mathematical and statistical models for HIV transmission and AIDS were given by (see e.g., [4,39,72]). An overview of AIDS policy models that help policymakers in determining the appropriate policy decision to curb the spread of the epidemic can be found in [7,8,37,47,68]. We refer the reader especially to the work of Rauner and Brandeau [69], where key issues in AIDS policy modeling for the twenty-first century are illustrated by examples from the past and current literature.…”

“…Our AIDS policy model is embedded in the simulation part of our DSS for resource allocation of HIV/AIDS control programs, while most other AIDS policy models are not embedded in a DSS [37,47,68]. Our DSS supports policy makers in the overall analysis process consisting of the data entry for scenarios (under Microsoft Excel/Visual Basic), the simulation of scenarios (under Borland Delphi), and the outcome analysis of scenarios (under Microsoft Excel/Visual Basic).…”

“…In addition, the compartments for vaccination can be seen as innovative model components because no effective vaccine is currently on the market yet our model anticipates this evolution. No model have allowed for five test history compartments to simultaneously investigate the efficiency and effectiveness of HIV testing in combination with the administration of therapies and vaccinations at such a level of specification [37,47,68,69].…”

“…As our model allows for a variety of infection paths and HIV/AIDS control programs, many transitions take place among compartments compared to other AIDS policy models [37,47,69]. In this sub-section we will present examples for the abstract formulas for demographic-related and risk-related movements, while in the next two sub-sections we will give examples for the abstract formulas of infection-related, disease-progression-related, and control-program-related movements.…”

Planning for HIV Screening, Testing, and Care at the Veterans Health Administration

“…Optimization based models have been used to evaluate prevention and treatment policies for HIV at different decision making levels (Kahn et al 1998;Rauner et al 2001). Population level studies evaluate the cost effectiveness of policy interventions (Zaric et al 2000;Long et al 2010), while studies at an individual patient level optimize clinical decision making to maximize patient welfare (Shechter et al 2008;Roberts et al 2010).…”