Abstract
Vaccine efficacy (VE) estimates are crucial for assessing the suitability of dengue vaccine candidates for public health implementation, but efficacy trials are subject to a known bias to estimate VE toward the null if heterogeneous exposure is not accounted for in the analysis of trial data. In light of many well-characterized sources of heterogeneity in dengue virus (DENV) transmission, our goal was to estimate the potential magnitude of this bias in VE estimates for a hypothetical dengue vaccine. To ensure that we realistically modeled heterogeneous exposure, we simulated city-wide DENV transmission and vaccine trial protocols using an agent-based model calibrated with entomological and epidemiological data from long-term field studies in Iquitos, Peru. By simulating a vaccine with a true VE of 0.8 in 1,000 replicate trials each designed to attain 90% power, we found that conventional methods underestimated VE by as much as 21% due to heterogeneous exposure. Accounting for the number of exposures in the vaccine and placebo arms eliminated this bias completely, and the more realistic option of including a frailty term to model exposure as a random effect reduced this bias partially. We also discovered a distinct bias in VE estimates away from the null due to lower detectability of primary DENV infections among seronegative individuals in the vaccinated group. This difference in detectability resulted from our assumption that primary infections in vaccinees who are seronegative at baseline resemble secondary infections, which experience a shorter window of detectable viremia due to a quicker immune response. This resulted in an artefactual finding that VE estimates for the seronegative group were approximately 1% greater than for the seropositive group. Simulation models of vaccine trials that account for these factors can be used to anticipate the extent of bias in field trials and to aid in their interpretation.
Highlights
An estimated 390 million people worldwide experience dengue virus (DENV) infections each year, with approximately 96 million of those showing clinically apparent symptoms [1]
In an attempt to account for heterogeneous exposure within the trial, we considered the addition of a frailty expression—in which heterogeneity in exposure was defined as a random effect by a gamma distribution—to the Cox-regression model and estimated vaccine efficacy for susceptibility (VES),frailty using the same coxph function in R with an additional frailty term specified as frailty(ID, distribution = "gamma")
Under the assumption of a leaky vaccine, VES is consistently underestimated by standard measures that do not account for the repeated, heterogeneous nature of DENV exposure
Summary
An estimated 390 million people worldwide experience dengue virus (DENV) infections each year, with approximately 96 million of those showing clinically apparent symptoms [1]. One dengue vaccine (Dengvaxia, Sanofi Pasteur) has been licensed to date, safety concerns have limited its rollout [2]. Beyond Dengvaxia, 22 investigational dengue vaccines are at various stages of development, with six of them in clinical trials [3]. Two tetravalent vaccines have advanced to phase-III clinical trials to evaluate vaccine efficacy against symptomatic, virologically-confirmed dengue disease [4,5]. 14 investigational Zika vaccines are under development, some of which may advance to late-phase trials [6]. Late-phase vaccine trials for dengue, Zika, and chikungunya—three viruses with a common mosquito vector in Aedes aegypti—share a number of common challenges
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