Biomedical subjects

Gregory S Zaric

Publications and source records attributed to Gregory S Zaric.

7 recordsLinked to original sources

PubMed2006

Reducing mortality from anthrax bioterrorism: strategies for stockpiling and dispensing medical and pharmaceutical supplies.

A critical question in planning a response to bioterrorism is how antibiotics and medical supplies should be stockpiled and dispensed. The objective of this work was to evaluate the costs and benefits of alternative strategies for maintaining and dispensing local and regional inventories of antibiotics and medical supplies for responses to anthrax bioterrorism. We modeled the regional and local supply chain for antibiotics and medical supplies as well as local dispensing capacity. We found that mortality was highly dependent on the local dispensing capacity, the number of individuals requiring prophylaxis, adherence to prophylactic antibiotics, and delays in attack detection. For an attack exposing 250,000 people and requiring the prophylaxis of 5 million people, expected mortality fell from 243,000 to 145,000 as the dispensing capacity increased from 14,000 to 420,000 individuals per day. At low dispensing capacities (<14,000 individuals per day), nearly all exposed individuals died, regardless of the rate of adherence to prophylaxis, delays in attack detection, or availability of local inventories. No benefit was achieved by doubling local inventories at low dispensing capacities; however, at higher dispensing capacities, the cost-effectiveness of doubling local inventories fell from 100,000 US dollars to 20,000 US dollars/life year gained as the annual probability of an attack increased from 0.0002 to 0.001. We conclude that because of the reportedly rapid availability of regional inventories, the critical determinant of mortality following anthrax bioterrorism is local dispensing capacity. Bioterrorism preparedness efforts directed at improving local dispensing capacity are required before benefits can be reaped from enhancing local inventories.

Anthrax↗

PubMed2005

Analysis of a pharmaceutical risk sharing agreement based on the purchaser's total budget.

Many public and private healthcare payers use formularies as a tool for controlling drug costs and quality. Although the price per dose is often negotiated as part of the formulary listing, payers may still face unlimited financial risk if demand is much greater than expected at the time of listing. The requirement for drug manufacturers to submit a budget impact analysis as part of the drug approval process suggests that payers are concerned not only with the cost effectiveness of a proposed drug but also with the potential increase in total expenditures that may result from new formulary listings. In this paper we define and analyze a model for financial risk sharing based on the total budget. Our analysis focuses on optimal decision making by manufacturers in the presence of a specific risk sharing agreement. We derive a manufacturer's optimal statement of budget impact and discuss several properties of the optimal solution.

Cost-Benefit Analysis↗

PubMed2005

Improved allocation of HIV prevention resources: using information about prevention program production functions.

To allocate HIV prevention resources effectively, it is important to have information about the effectiveness of alternative prevention programs as a function of expenditure. We refer to this relationship as the "production function" for a prevention program. Few studies of HIV prevention programs have reported this relationship. This paper demonstrates the value of such information. We present a simple model for allocating HIV prevention resources, and apply the model to an illustrative HIV prevention resource allocation problem. We show that, without sufficient information about prevention program production functions, suboptimal decisions may be made. We show that epidemiologic data, such as estimates of HIV prevalence or incidence, may not provide enough information to support optimal allocation of HIV prevention resources. Our results suggest that good allocations can be obtained based on fairly basic information about prevention program production functions: an estimate of fixed cost plus a single estimate of cost and resulting risk reduction. We find that knowledge of production functions is most important when fixed cost is high and/or when the budget is a significantly constraining factor. We suggest that, at the minimum, future data collection on prevention program effectiveness should include fixed and variable cost estimates for the intervention when implemented at a "typical" level, along with a detailed description of the intervention and detailed description of costs by category.

Canada↗

PubMed2003

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.

Communicable Disease Control↗

PubMed2002

Random vs. nonrandom mixing in network epidemic models.

In this paper we compare random and nonrandom mixing patterns for network epidemic models. Several of studies have examined the impact of different mixing patterns using compartmental epidemic models. We extend the work on compartmental models to the case of network epidemic models. We define two nonrandom mixing patterns for a network epidemic model and investigate the impact that these mixing patterns have on a number of epidemic outcomes when compared to random mixing. We find that different mixing assumptions lead to small but statistically significant differences in disease prevalence, cumulative number of new infections, final population size, and network structure. Significant differences in outcomes were more likely to be observed for larger populations and longer time horizons. Sensitivity analysis revealed that greater differences in outcomes between random and nonrandom mixing were associated with a larger incremental mortality rate among infected individuals, a larger average number of partners, and a greater probability of forming new partnerships. When adjusted for the initial population size, differences between random and nonrandom mixing models were approximately constant across all population sizes considered. We also considered the impact that differences between mixing models might have on the cost effectiveness ratio for epidemic control interventions.

Computer Simulation↗

PubMed2002

Dynamic resource allocation for epidemic control in multiple populations.

We develop a dynamic resource allocation model in which a limited budget for epidemic control is allocated over multiple time periods to interventions that affect multiple populations. For certain special cases with two time periods, multiple independent populations, and a linear relationship between investment in a prevention programme and the resulting change in risky behaviour, we demonstrate that the optimal solution involves investing in each period as much as possible in some of the populations and nothing in all the other populations. We present heuristic algorithms for solving the general problem, and present numerical results. Our computational analyses suggest that good allocations can be made based on some fairly simple heuristics. Our analyses also suggest that allowing for some reallocation of resources over the time horizon of the problem, rather than allocating resources just once at the beginning of the time horizon, can lead to significant increases in health benefits. Allowing for reallocation of funds may generate more health benefits than use of a sophisticated model for one-time allocation of resources.

Communicable Disease Control↗

PubMedDate not supplied

The impact of ignoring population heterogeneity when Markov models are used in cost-effectiveness analysis.

Many factors related to the spread and progression of diseases vary throughout a population. This heterogeneity is frequently ignored in cost-effectiveness analyses by using average or representative values or by considering multiple risk groups. The author explores the impact that such simplifying assumptions may have on the results and interpretation of cost-effectiveness analyses when Markov models are used to calculate the costs and health impact of interventions. A discrete-time Markov model for a disease is defined, and 5 potential interventions are considered. Health benefits, costs, and incremental cost-effectiveness ratios are calculated for each intervention. It is assumed that the population is heterogeneous with respect to the probability of becoming sick. Ignoring this heterogeneity may lead to optimistic or pessimistic estimates of cost-effectiveness ratios, depending on the intervention and, in some cases, the parameter values. Implications are discussed of this finding on the use of league tables and on comparisons of cost-effectiveness ratios versus commonly accepted threshold values.

Cost-Benefit Analysis↗