4.1 Introduction

A safe supply of blood for transfusion is a critical component of the healthcare system in high-, middle-, and low-income countries alike [118]. In most health systems, the risk of transfusion-transmissible infections (TTIs) is managed through a portfolio of blood safety interventions. These portfolios consist of three types of interventions. Donor deferral policies turn away potential donors who have characteristics associated with increased risk for harboring a TTI. Disease marker tests are used to screen out donations with detectable disease markers and to defer donors from future donation. Risk-reducing modifications like pathogen inactivation or leukoreduction reduce the likelihood that a TTI, if present in a transfused donation, is transmitted to a recipient. Blood safety portfolios should be periodically reassessed because of shifting epidemiological conditions, emerging infectious diseases, and new technologies. However, the number of available blood safety portfolios grows exponentially with the number of available interventions, making it impossible for policymakers to systematically enumerate, much less evaluate, all feasible portfolios without the assistance of a computer model.

Decision analytic modeling has played a limited role in consistently informing decisions regarding blood safety portfolios. Because the health and economic consequences of a blood safety intervention depend on local epidemiological conditions, the existing blood safety portfolio, and the larger healthcare system, analyses that have been conducted for blood safety interventions are limited to specific jurisdictions at specific times. Most studies have been cost-utility analyses that incorporate relevant risks, costs, and health consequences. These studies typically consider adding or changing one intervention while keeping others constant. Such analyses have been conducted to evaluate disease marker tests [8,9,15–17,36,37], pathogen inactivation technologies (a new category of risk-reducing modifications) [10,11,18,19], and donor deferral policies [20]. Methods have recently been proposed to systematically select a portfolio of disease marker tests for a specific context, assuming that deferral and modification interventions are held constant [119–121]. These optimization-based frameworks are designed to ensure that risk is sufficiently reduced but are not designed to evaluate changes in deferral or modification interventions and may not be consistent with finding the optimal policy from a cost-utility perspective.

In this chapter, we develop a new framework for evaluating blood safety portfolios that uses a definition of optimality that is consistent with standard cost-utility analysis methods [122]. In this framework, health outcomes are expressed as costs, and the optimal set of blood safety interventions minimizes the net present monetary cost of the blood safety portfolio and of any infectious donations that are released. Unlike currently available methods, this framework enables the systematic comparison of all feasible portfolios of deferral, testing, and modification interventions to identify the portfolio that is preferred from a cost-utility perspective.

In the following sections, we derive our model by first introducing a simple model and progressively adding complexity. The model is a binary integer program (whether to implement each possible blood safety intervention). We present structural properties that reduce the state space and required computation time to find an optimal solution in certain cases, and we suggest a heuristic solution approach for problems that are too large to be solved exactly. We apply the model to retrospectively analyze U.S. policies for two TTIs that have been difficult to manage due to geographical and seasonal variations in prevalence and infectiousness, Zika virus and West Nile virus. We conclude with a discussion of implications and potential extensions of our modeling framework.