Modeling the Impact of a Future Dengue Vaccine
Statistical and Mathematical Modeling of Dengue Transmission and Control with Vaccines
By Dr. Ira Longini
This article originally appeared in the February 2013 Dengue Vaccine Initiative Newsletter
As part of the DVI program, a team has been working to develop and advance a model for the impact of dengue vaccine immunization on infection and disease, one that allows the simulation of a wide range of scenarios, including the impact of vector control. The team has been analyzing dengue transmission and control with vaccines using statistical and mathematical models.
The work includes the eventual statistical analysis of Phase 1-4 vaccine trial data to better understand how dengue vaccines protect against infection, disease and transmission. Additionally, dengue cohort data from Thailand, Colombia and Nicaragua are being analyzed to better understand the infection and immune process of the four dengue serotypes.
Based on this information and a good deal of epidemiological and demographic data, an individual-level (including both humans and mosquitoes), stochastic simulation model for dengue transmission and control in a semi-rural area in Thailand has been developed. The model is calibrated to dengue serotype-specific infection, illness and hospitalization data from Thailand. Simulations show that a realistic roll-out plan, starting with young children then covering progressively older individuals in following seasons, could reduce local transmission of dengue to low levels. They also indicate that this strategy could avert about 7,700 uncomplicated dengue fever cases and 220 dengue hospitalizations per 100,000 people at risk over a ten-year period. In the model, potential dengue vaccines that may not be efficacious against all four dengue serotypes are also evaluated. The model shows that such a vaccine could still be effective, but is conditional on the mix of dengue serotypes circulating. This work was published in the journal PLoS Neglected Tropical Diseases in October 2012.
The team has also developed statistical and modeling approaches to evaluate dengue vaccine effectiveness in coming community trials and during the large scale rollout of dengue vaccines in the future. This includes work with field sites in the State of the Yucatan, Mexico, where the team is helping to develop dengue cohort and community-wide epidemiological studies. The ultimate goal of this work will be to estimate the community level effectiveness of the large-scale introduction of dengue vaccines in the Yucatan. This work should serve as a template for developing similar efforts in other countries and regions.
This statistical and mathematical work has shown that dengue vaccination will have an important role in controlling dengue. According to modeling results, small children should be prioritized to receive vaccine first, but vaccination catch-up campaigns in older children and sometimes adults will be needed to control dengue. The precise rate and inclusion of vaccination of older age groups will depend on the epidemiology, age structure, and dengue immune structure in the target population.
Dr. Ira Longini is a professor of biostatistics at the University of Florida and co-director of the Center for Statistics and Quantitative Infectious Diseases (CSQUID) at the Emerging Pathogens Institute at the University of Florida.
Top Photo: CDC/ Robert S. Craig