Four randomized placebo-controlled efficacy trials of a candidate vaccine or passively infused monoclonal antibody for prevention of HIV-1 infection are underway (HVTN 702 in South African men and women; HVTN 705 in sub-Saharan African women; HVTN 703/HPTN 081 in sub-Saharan African women; HVTN 704/HPTN 085 in U.S., Peruvian, Brazilian, and Swiss men or transgender persons who have sex with men). Several challenges are posed to the optimal design of the sequel efficacy trials, including: (1) how to account for the evolving mosaic of effective prevention interventions that may be part of the trial design or standard of prevention; (2) how to define viable and optimal sequel trial designs depending on the primary efficacy results and secondary “correlates of protection” results of each of the ongoing trials; and (3) how to define the primary objective of sequel efficacy trials if HIV-1 incidence is expected to be very low in all study arms such that a standard trial design has a steep opportunity cost. After summarizing the ongoing trials, I discuss statistical science considerations for sequel efficacy trial designs, both generally and specifically to each trial listed above. One conclusion is that the results of “correlates of protection” analyses, which ascertain how different host immunological markers and HIV-1 viral features impact HIV-1 risk and prevention efficacy, have an important influence on sequel trial design. This influence is especially relevant for the monoclonal antibody trials because of the focused pre-trial hypothesis that potency and coverage of serum neutralization constitutes a surrogate endpoint for HIV-1 infection. Another conclusion is that while assessing prevention efficacy against a counterfactual placebo group is fraught with risks for bias, such analysis is nonetheless important and study designs coupled with analysis methods should be developed to optimize such inferences. I draw a parallel with non-inferiority designs, which are fraught with risks given the necessity of making unverifiable assumptions for interpreting results, but nevertheless have been accepted when a superiority design is not possible and a rigorous/conservative non-inferiority margin is used. In a similar way, counterfactual placebo group efficacy analysis should use rigorous/conservative inference techniques that formally build in a rigorous/conservative margin to potential biases that could occur due to departures from unverifiable assumptions. Because reliability of this approach would require new techniques for verifying that the study cohort experienced substantial exposure to HIV-1, currently it may be appropriate as a secondary objective but not as a primary objective.