Transmission Dynamics of the Four Dengue Serotypes in Southern Vietnam and the Potential Impact of Vaccination

BACKGROUND With approximately 2.5 billion people at risk, dengue is a major international public health concern. Dengue vaccines currently in development should help reduce the burden associated with this disease but the most efficient way of using future dengue vaccines remains to be defined. Mathematical models of transmission can provide insight into the expected impact of different vaccination strategies at a population level and contribute to this definition. METHODS AND FINDINGS We developed and analyzed an age-structured, host-vector and serotype-specific compartmental model, including seasonality. We first used this transmission model to identify the immunological interactions between serotypes that affect the risks and consequences of secondary infections (cross-protection, increased susceptibility, increased severity, and increased infectiousness) and reproduce the observed epidemiology of dengue. For populating this model, we used routine surveillance data from Southern Vietnam and the results of a prospective cohort study conducted in the same area. The model provided a good fit to the observed data for age, severity of cases, serotype distribution, and dynamics over time, using two scenarios of immunological interaction : short term cross-protection alone (6-17 months) or a combination of short term cross-protection with cross-enhancement (increased susceptibility, severity and infectiousness in the case of secondary infections). Finally, we explored the potential impact of vaccination for these two scenarios. Both highlighted that vaccination can substantially decrease dengue burden by reducing the magnitude and frequency of outbreaks. CONCLUSION Our model suggests that seasonality and short term cross-protection are key factors for explaining dengue dynamics in Southern Vietnam. Vaccination was predicted to significantly reduce the disease burden, even in the situation where immunological cross-enhancement affects the risks and consequences of secondary infections.