An agent-based model of dengue virus transmission shows how uncertainty about breakthrough infections influences vaccination impact projections

Abstract

Prophylactic vaccination is a powerful tool for reducing the burden of infectious diseases, due to a combination of direct protection of vaccinees and indirect protection of others via herd immunity. Computational models play an important role in devising strategies for vaccination by making projections of its impacts on public health. Such projections are subject to uncertainty about numerous factors, however. For example, many vaccine efficacy trials focus on measuring protection against disease rather than protection against infection, leaving the extent of breakthrough infections (i.e., disease ameliorated but infection unimpeded) among vaccinees unknown. Our goal in this study was to quantify the extent to which uncertainty about breakthrough infections results in uncertainty about vaccination impact, with a focus on vaccines for dengue. To realistically account for the many forms of heterogeneity in dengue virus (DENV) transmission, which could have implications for the dynamics of indirect protection, we used a stochastic, agent-based model for DENV transmission informed by more than a decade of empirical studies in the city of Iquitos, Peru. Following 20 years of routine vaccination of nine-year-old children at 80% coverage, projections of the proportion of disease episodes averted varied by a factor of 1.76 (95% CI: 1.54–2.06) across the range of uncertainty about breakthrough infections. This was equivalent to the range of vaccination impact projected across a range of uncertainty about vaccine efficacy of 0.268 (95% CI: 0.210–0.329). Until uncertainty about breakthrough infections can be addressed empirically, our results demonstrate the importance of accounting for it in models of vaccination impact.

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“…Our model was calibrated to data from Iquitos, which has a population of about 450,000 people in the Peruvian Amazon [49,50] and where all four DENV serotypes are endemic. We calibrated the initial level of population immunity, number of imported infections, and the absolute mosquito abundance using a particle filtering approach to an estimate of the serotypespecific number of infections based on a longitudinal cohort study in Iquitos [51].…”

“…We calibrated the initial level of population immunity, number of imported infections, and the absolute mosquito abundance using a particle filtering approach to an estimate of the serotypespecific number of infections based on a longitudinal cohort study in Iquitos [51]. Results of this calibration procedure are shown in S1 Fig [49]. Several other components of the model were independently calibrated to data from Iquitos, including the spatiotemporal pattern in mosquito abundance [52] and human movement [53].…”

“…We simulated outbreak response strategies using an established agent-based model of dengue virus dynamics in Iquitos (Fig 1B). This model has been shown to accurately recreate the dynamics of all four DENV serotypes in Iquitos, and has previously been used to answer questions relating to DENV vaccination [49,50,56]. Human agents in the model move according to realistic movement patterns in Iquitos [53].…”

“…The rate of introduction of each DENV serotype into the population was calibrated so that serotype-specific incidence of infection matched that predicted for Iquitos in a previous study [51]. All features of the model have been thoroughly described in a prior publication [49], and further details are described in the S1 Text.…”

“…They do not affect the model calibration. Moreover, as the model was calibrated to serotype-specific estimates of infections based on serology from longitudinal cohort studies, the calibration was unaffected by surveillance underreporting and delays [49,51].…”