  Accurate estimates of malaria vaccine efficacy require a reliable definition
of a malaria case. However, the symptoms of clinical malaria are unspecific,
overlapping with other childhood illnesses. Additionally, children in endemic
areas tolerate varying levels of parasitemia without symptoms. Together, this
makes finding a gold-standard case definition challenging. We present a method
to identify and estimate malaria vaccine efficacy that does not require an
observable gold-standard case definition. Instead, we leverage genetic traits
that are protective against malaria but not against other illnesses, e.g., the
sickle cell trait, to identify vaccine efficacy in a randomized trial. Inspired
by Mendelian randomization, we introduce Mendelian factorial design, a method
that augments a randomized trial with genetic variation to produce a natural
factorial experiment, which identifies vaccine efficacy under realistic
assumptions. A robust, covariance adjusted estimation procedure is developed
for estimating vaccine efficacy on the risk ratio and incidence ratio scales.
Simulations suggest that our estimator has good performance whereas standard
methods are systematically biased. We demonstrate that a combined estimator
using both our proposed estimator and the standard approach yields significant
improvements when the Mendelian factor is only weakly protective.
