Background and Objectives Accurate HIV incidence estimates among blood donors are necessary to assess the effectiveness of programs aimed at limiting transfusion‐transmitted HIV. We assessed the impact of undisclosed HIV status and antiretroviral (ARV) use on HIV recency and incidence estimates using increasingly comprehensive recent infection testing algorithms. Materials and Methods Using 2017 donation data from first‐time and lapsed donors, we populated four HIV recency algorithms: (1) serology and limiting‐antigen avidity testing, (2) with individual donation nucleic amplification testing (ID‐NAT) added to Algorithm 1, (3) with viral load added to Algorithm 2 and (4) with ARV testing added to Algorithm 3. Algorithm‐specific mean durations of recent infection (MDRI) and false recency rates (FRR) were calculated and used to derive and compare incidence estimates. Results Compared with Algorithm 4, progressive algorithms misclassified fewer donors as recent: Algorithm 1: 61 (12.1%); Algorithm 2: 14 (2.8%) and Algorithm 3: 3 (0.6%). Algorithm‐specific MDRI and FRR values resulted in marginally lower incidence estimates: Algorithm 1: 0.19% per annum (p.a.) (95% confidence interval CI: 0.13%–0.26%); Algorithm 2: 0.18% p.a. (95% CI: 0.13%–0.22%); Algorithm 3: 0.17% p.a. (95% CI: 0.13%–0.22%) and Algorithm 4: 0.17% p.a. (95% CI: 0.13%–0.21%). Conclusion We confirmed significant misclassification of recent HIV cases when not including viral load and ARV testing. Context‐specific MDRI and FRR resulted in progressively lower incidence estimates but did not fully account for the context‐specific variability in incidence modelling. The inclusion of ARV testing, in addition to viral load and ID‐NAT testing, did not have a significant impact on incidence estimates.