title: The Potential Impact of Vaccination on the Dynamics of Dengue Infections.
abstract: Dengue, classified as a 'neglected topical disease', is currently regarded globally as the most important mosquito-borne viral disease, which inflicts substantial socioeconomic and health burden in many tropical and subtropical regions of the world. While efforts continue towards developing and improving the efficacy of a tetravalent vaccine to protect individuals against all dengue virus serotypes, the long-term epidemiological impact of vaccination remains elusive. We develop a serotype-specific, vector-host compartmental model to evaluate the effect of vaccination in the presence of antibody-dependent enhancement and cross-protection following recovery from primary infection. Reproducing the reported multi-annual patterns of dengue infection, our model projects that vaccination can dramatically reduce the overall incidence of the disease. However, if the duration of vaccine-induced protection is shorter than the average lifetime of the human population, vaccination can potentially increase the incidence of severe infection of dengue haemorrhagic fever due to the effects of antibody-dependent enhancement. The magnitude and timelines for this increase depend strongly on the efficacy and duration of the vaccine-induced protection. Corresponding to the current estimates of vaccine efficacy, we show that dengue eradication is infeasible using an imperfect vaccine. Furthermore, for a vaccine that induces lifetime protection, a nearly full coverage of infant vaccination is required for dengue elimination. Our findings suggest that other vector control measures may still play a significant role in dengue prevention even when a vaccine with high protection efficacy becomes available.
authors.affiliation: Agent-Based Modelling Laboratory, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada. knipl@yorku.ca.|MTA-SZTE Analysis and Stochastic Research Group, University of Szeged, Aradi vértanúk tere 1, Szeged, 6720, Hungary. knipl@yorku.ca.
authors.forename: Diána
authors.initials: D
authors.lastname: Knipl
authors.affiliation: Agent-Based Modelling Laboratory, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada. moghadas@yorku.ca.
authors.forename: Seyed M
authors.initials: SM
authors.lastname: Moghadas
mesh_terms: D000818:Animals; D003198:Computer Simulation; D003715:Dengue / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission; D053059:Dengue Vaccines / Q000494:pharmacology*; D003716:Dengue Virus / Q000145:classification; D006801:Humans; D007303:Insect Vectors / Q000821:virology; D055641:Mathematical Concepts; D008954:Models, Biological; D012703:Serotyping; D014611:Vaccination
chemical_list: D053059:Dengue Vaccines
keywords: Antibody-dependent enhancement; Dengue fever; Epidemic modelling; Simulation; Vaccination