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Biostatistics 3:133-143 (2002)
© 2002 Oxford University Press

A statistical method for the estimation of window-period risk of transfusion-transmitted HIV in donor screening under non-steady state

Yutaka Yasui, Hideki Yanai, Pathom Sawanpanyalert and Hideo Tanaka

Cancer Prevention Research Program, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., MP702, Seattle, WA 98109 USA. yyasui{at}fhcrc.org
Research Institute of Tuberculosis, Japan Anti-TB association, Tokyo, Japan
Bureau of Medical Technical Development, Department of Medical Services, Ministry of Public Health, Nonthaburi, Thailand
Osaka Medical Center for Cancer and Cardiovasucular Diseases, Osaka, Japan

Human immunodeficiency virus (HIV) can be transmitted by transfusion of blood even if the blood unit is test-negative for HIV. This is largely due to a time period following an infection, called the window period, during which antibodies against HIV are not detectable. Window-period risk refers to the probability for a test-negative blood unit to be infectious because of its donation during the window period. Estimation of window-period risk is important in public health for evaluating the safety of donated blood. The standard method for this estimation problem has been based on so-called incidence/window-period (IWP) models in which blood-donation and HIV-infection processes are assumed to be stochastically stationary and independent. Here we propose a new approach in which we relax this key assumption of the IWP models. We estimate window-period risk for each unit of donated blood using a given distribution of window-period risk. The proposed method utilizes the actual observed donation intervals including those of seroconversions, thereby relaxing the assumption that may not be met in practice. Bootstrap is used to compute confidence intervals without specifying the complex dynamics of the donation and infection processes. A simulation study illustrates the usefulness of the proposed method over the IWP method in scenarios where the IWP assumptions do not hold. A real application of the proposed method is presented using blood bank data from a province of northern Thailand. Advantages and limitations of the proposed method are discussed and compared with the IWP models.

Keywords: Blood bank; Blood donation; Blood safety; Bootstrap incidence/window-period models; Stationary assumption


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