Models of the impact of dengue vaccines: a review of current research and potential approaches

Abstract

Vaccination reduces transmission of pathogens directly, by preventing individual infections, and indirectly, by reducing the probability of contact between infected individuals and susceptible ones. The potential combined impact of future dengue vaccines can be estimated using mathematical models of transmission. However, there is considerable uncertainty in the structure of models that accurately represent dengue transmission dynamics. Here, we review models that could be used to assess the impact of future dengue immunization programmes. We also review approaches that have been used to validate and parameterize models. A key parameter of all approaches is the basic reproduction number, R(0), which can be used to determine the critical vaccination fraction to eliminate transmission. We review several methods that have been used to estimate this quantity. Finally, we discuss the characteristics of dengue vaccines that must be estimated to accurately assess their potential impact on dengue virus transmission.

Figure 1

Schematics of multiple dengue models. a. Basic Susceptible-Infectious-Recovered (SIR) model that forms the basis of most infectious disease modeling. b. An expansion of the SIR model to include primary infections, secondary infections, and individuals that have encountered only one serotype, the primary recovered individuals (1°R). The red arrow distinguishes the rate at which individuals with immunity to a single serotype acquire second infections from the rate at which people with no immunity acquire their first. c. Model including a short-term cross-immune class (1°CI). d. Model assuming that secondary infections have higher rates of mortality. e. Model explicitly including a vector population.

Figure 2

The effect of R₀ on the critical vaccination fraction. Median estimates for each published R₀ estimate are indicated.