Dengue is a multi-serotype vector borne viral disease exhibiting complex patterns of serotype dominance, the underlying mechanisms of which remain largely unexplained. While the clinical manifestations of infection with the dengue virus are varied, it can lead to severe dengue hemorrhagic fever (DHF). The risk of DHF is exacerbated by secondary heterotypic infections. Thus, disentangling the immunological, environmental and ecological underpinnings of dengue transmission is a necessary precursor to effective control policies. This is especially timely given the recent licensure of a dengue vaccine. Crucially, ignoring serotype interactions may perversely prime vaccines to severe dengue infections.
We present an approach for identifying the nature and parameters of dengue serotype interactions using a combination of longitudinal epidemiological data, a transmission model and computational statistics. Specifically, we propose to test three competing hypotheses regarding the role of secondary infections on dengue pathogenesis and transmission. In particular, whether heterologous secondary infections cause enhancement of (i) host susceptibility, increasing the risk of infection, (ii) host infectiousness, leading to greater transmission, or (iii) disease severity, reflecting increased virulence. We submit that an empirically validated dengue model will be essential in developing rational vaccination policy.
Results/Conclusions
We have fit a SIR model quantifying the invasion threshhold (R0) for dengue cases observed in San Juan during the epidemic of 1994-95, the season with the largest dengue outbreak. R0 is defined as the number of secondary infections caused due to an index case in a completely susceptible population. We employ a likelihood based statistical inference method for parameter estimation. We compute the R0 to be rougly around 4.6 for total dengue cases. This estimate is comparable to the recent estimates for Dengueas reflected in the literature. We are currently employing SICR compartmental models with serotype interactions that encode short and long-term consequences of co-circulating serotypes on the epidemiology of the disease.