A comparison of methods for estimating the incidence of human immunodeficiency virus infection in repeat blood donors

Abstract

BACKGROUND HIV incidence in repeat blood donors has been estimated by 7 methods. While incidence is always calculated as cases/person-time, approaches to selecting cases and calculating person-time vary. Incidence estimates have not been compared among methods. STUDY DESIGN AND METHODS The methods were compared in a simulation study. Because three methods use information from donations made before an estimation interval, 8 years of donation and infection history were simulated, with years 7 and 8 treated as the estimation interval for all methods. An exponential random variate was assigned to each donor to simulate time to infection. Infection risk was constant over 8 years in one scenario but increased at various rates in 7 others. The infection risk scenarios were combined with 4 mixes of donation frequency to generate 32 test conditions. RESULTS Three methods produced biased estimates under all conditions. Three others were biased under most conditions. Bias from most methods increased as donation frequency declined. The single method that consistently produced unbiased estimates was the only method that involved the standard epidemiological approach of tabulating all interdonation intervals (IDIs) within the estimation interval. Bias was eliminated from one of the consistently biased methods by a simple modification that involved the average IDI in a sample of donors. CONCLUSION The standard epidemiological approach is recommended if required data are available. Otherwise, the modified method involving the estimated average IDI should be considered. Investigators should use caution when comparing incidence estimates among studies with different estimation methods and/or donation frequencies.

HIV, HCV, and HBV incidence and residual risk in US blood donors before and after implementation of the 12‐month deferral policy for men who have sex with men

“…For this study, the classic method was used for repeat donors as it is direct, simple, stable, and uses stand-alone estimation intervals with no need for data before the time period being analyzed. 5,9 To estimate incidence among first-time donors and the overall population, we used the NAT yield approach, which is simple and derived directly from available data. 4,7 However, it was developed before the use of biomarkers for recent infection.…”

“…The classic method was used to determine which donors were incident cases (converted from negative to confirmed positive during the estimation interval) and the persontime of both negative and positive donors within the same estimation interval. 9,10 Thus, a repeat donor must have two or more tested donations within the estimation interval to be eligible either to contribute person-time and/or to be considered an incident case. Incidence in repeat donors was calculated as the number of incident cases divided by the total person-time of negative donors plus one-half the person-time of incident donors.…”

Estimating the incidence of HIV infection in repeat blood donors with low average donation frequency

“…We generated simulated donation and infection histories over an 8‐year span, treating the last 2 years as the estimation interval, as we did in our previous work 1 . The assumption of constant risk that underlies incidence calculations implies that time to infection follows an exponential distribution.…”

“…In a previous simulation study, we evaluated seven published methods for estimating HIV infection incidence in repeat blood donors 1 . Only the standard method first described by Schreiber and colleagues 2 produced unbiased estimates of incidence under all combinations of incidence rates and donation frequencies considered in that study.…”

10‐year analysis of human immunodeficiency virus incidence in first‐time and repeat donors in Brazil

“…Calculating incidence in repeat donors relies on classical methods [2]. However, incidence can also be calculated in first‐time donors using cross‐sectional approaches that rely on measures of HIV antibody maturation.…”