Gregory S. Zaric

Dynamic transmission modeling: A report of the ISPOR-SMDM modeling good research practices task force-5

Abstract The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the population, will change over time, and will feed back into the future force of infection. These nonlinear interactions produce transmission dynamics that require specific consideration when modeling an intervention that has an impact on the transmission of a pathogen. Best practices for designing and building these models are set out in this article.

Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis.

Traditional cost-effectiveness analysis (CEA) assumes that program costs and benefits scale linearly with investment-an unrealistic assumption for epidemic control programs. This paper combines epidemic modeling with optimization techniques to determine the optimal allocation of a limited resource for epidemic control among multiple noninteracting populations. We show that the optimal resource allocation depends on many factors including the size of each population, the state of the epidemic in each population before resources are allocated (e.g. infection prevalence and incidence), the length of the time horizon, and prevention program characteristics. We establish conditions that characterize the optimal solution in certain cases.

The cost-effectiveness of Vancouver's supervised injection facility

Background: The cost-effectiveness of Canadas only supervised injection facility has not been rigorously evaluated. We estimated the impact of the facility on survival, rates of HIV and hepatitis C virus infection, referral to methadone maintenance treatment and associated costs. Methods: We simulated the population of Vancouver, British Columbia, including injection drug users and persons infected with HIV and hepatitis C virus. The model used a time horizon of 10 years and the perspective of the health care system. We compared the situation of the supervised injection facility with one that had no facility but that had other interventions, such as needle-exchange programs. The effects considered were decreased needle sharing, increased use of safe injection practices and increased referral to methadone maintenance treatment. Outcomes included life-years gained, costs, and incremental cost-effectiveness ratios discounted at 5% per year. Results: Focusing on the base assumption of decreased needle sharing as the only effect of the supervised injection facility, we found that the facility was associated with an incremental net savings of almost

ISPOR Task Force reportDynamic Transmission Modeling: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-5

14 million and 920 life-years gained over 10 years. When we also considered the health effect of increased use of safe injection practices, the incremental net savings increased to more than

Optimal Investment in a Portfolio of HIV Prevention Programs

20 million and the number of life-years gained to 1070. Further increases were estimated when we considered all 3 health benefits: the incremental net savings was more than

Dynamic Transmission Modeling: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-5

18 million and the number of life-years gained 1175. Results were sensitive to assumptions related to injection frequency, the risk of HIV transmission through needle sharing, the frequency of safe injection practices among users of the facility, the costs of HIV-related care and of operating the facility, and the proportion of users who inject in the facility. Interpretation: Vancouvers supervised injection site is associated with improved health and cost savings, even with conservative estimates of efficacy.

Modeling the Logistics of Response to Anthrax Bioterrorism

Abstract The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the population, will change over time, and will feed back into the future force of infection. These nonlinear interactions produce transmission dynamics that require specific consideration when modeling an intervention that has an impact on the transmission of a pathogen. Best practices for designing and building these models are set out in this article.

Multi-level resource allocation for HIV prevention: A model for developing countries

Objectives . In this article, the authors determine the optimal allocation of HIV prevention funds and investigate the impact of different allocation methods on health outcomes. Methods . The authors present a resource allocation model that can be used to determine the allocation of HIV prevention funds that maximizes quality-adjusted life years (or life years) gained or HIV infections averted in a population over a specified time horizon. They apply the model to determine the allocation of a limited budget among 3 types of HIV prevention programs in a population of injection drug users and nonusers: needle exchange programs, methadone maintenance treatment, and condom availability programs. For each prevention program, the authors estimate a production function that relates the amount invested to the associated change in risky behavior. Results . The authors determine the optimal allocation of funds for both objective functions for a high-prevalence population and a low-prevalence population. They also consider the allocation of funds under several common rules of thumb that are used to allocate HIV prevention resources. It is shown that simpler allocation methods(e.g., allocation based on HIV incidence or notions of equity among population groups) may lead to allocations that do not yield the maximum health benefit. Conclusions . The optimal allocation of HIV prevention funds in a population depends on HIV prevalence and incidence, the objective function, the production functions for the prevention programs, and other factors. Consideration of cost, equity, and social and political norms may be important when allocating HIV prevention funds. The model presented in this article can help decision makers determine the health consequences of different allocations of funds.

The impact of delays to admission from the emergency department on inpatient outcomes

The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the population, will change over time, and will feed back into the future force of infection. These nonlinear interactions produce transmission dynamics that require specific consideration when modeling an intervention that has an impact on the transmission of a pathogen. Best practices for designing and building these models are set out in this paper.

Withholding stereotactic radiotherapy in elderly patients with stage I non-small cell lung cancer and co-existing COPD is not justified: Outcomes of a markov model analysis

Background. A bioterrorism attack with an agent such as anthrax will require rapid deployment of medical and pharmaceutical supplies to exposed individuals. How should such a logistical system be organized? How much capacity should be built into each element of the bioterrorism response supply chain? Methods. The authors developed a compartmental model to evaluate the costs and benefits of various strategies for preattack stockpiling and postattack distribution and dispensing of medical and pharmaceutical supplies, as well as the benefits of rapid attack detection. Results. The authors show how the model can be used to address a broad range of logistical questions as well as related, nonlogistical questions (e.g., the cost-effectiveness of strategies to improve patient adherence to antibiotic regimens). They generate several key insights about appropriate strategies for local communities. First, stockpiling large local inventories of medical and pharmaceutical supplies is unlikely to be the most effective means of reducing mortality from an attack, given the availability of national and regional supplies. Instead, communities should create sufficient capacity for dispensing prophylactic antibiotics in the event of a large-scale bioterror attack. Second, improved surveillance systems can significantly reduce deaths from such an attack but only if the local community has sufficient antibiotic-dispensing capacity. Third, mortality from such an attack is significantly affected by the number of unexposed individuals seeking prophylaxis and treatment. Fourth, full adherence to treatment regimens is critical for reducing expected mortality. Conclusions. Effective preparation for response to potential bioterror attacks can avert deaths in the event of an attack. Models such as this one can help communities more effectively prepare for response to potential bioterror attacks.