Hyperendemicity associated with increased dengue burden

Abstract

Over 105 million dengue infections are estimated to occur annually. Understanding the disease dynamics of dengue is often difficult due to multiple strains circulating within a population. Interactions between dengue serotype dynamics may result in complex cross-immunity dynamics at the population level and create difficulties in terms of formulating intervention strategies for the disease. In this study, a nationally representative 16-year time series with over 43 000 serotyped dengue infections was used to infer the long-run effects of between and within strain interactions and their impacts on past outbreaks. We used a novel identification strategy incorporating sign-identified Bayesian vector autoregressions, using structural impulse responses, historical decompositions and counterfactual analysis to conduct inference on dengue dynamics post-estimation. We found that on the population level: (i) across-serotype interactions on the population level were highly persistent, with a one time increase in any other serotype associated with long run decreases in the serotype of interest (range: 0.5-2.5 years) and (ii) over 38.7% of dengue cases of any serotype were associated with across-serotype interactions. The findings in this paper will substantially impact public health policy interventions with respect to dengue.

Keywords: Bayesian statistics; dengue; hyperendemicity; modelling; serotypes.

Figure 1.

Impulse response functions for each serotype given a standard deviation shock in another. Dark solid coloured lines represent the posterior median impulse response for 0–100 weeks after an initial shock in another serotype. Lighter coloured lines represent the 16th and 84th posterior quantile impulse response for 0–100 weeks after an initial shock in another serotype. Fine lines represent posterior impulse response draws for 0–100 weeks after an initial shock in another serotype.

Figure 2.

(a) Time series plot of DENV-1 case counts with historical decompositions of DENV-1 and all other serotypes. (b) Summary of weekly case contribution from DENV-1 and all other serotypes from historical decompositions. (c) Time series plot of DENV-2 case counts with historical decompositions of DENV-2 and all other serotypes. (d) Summary of weekly case contribution from DENV-2 and all other serotypes from historical decompositions. (e) Time series plot of DENV-3 case counts with historical decompositions of DENV-3 and all other serotypes. (f) Summary of weekly case contribution from DENV-3 and all other serotypes from historical decompositions. (g) Time series plot of DENV-4 case counts with historical decompositions of DENV-4 and all other serotypes. (h) Summary of weekly case contribution from DENV-4 and all other serotypes from historical decompositions.

Figure 3.

Summary boxplot for historical decompositions within and between serotypes. Boxplots from left to right represent: the historical contributions of DENV-1 to DENV-1,2,3,4, DENV-2 to DENV-1,2,3,4, DENV-3 to DENV-1,2,3,4 and DENV-4 to DENV-1,2,3,4.