Climatic-driven seasonality of emerging dengue fever in Hanoi, Vietnam

Abstract

Background: Dengue fever (DF) has been emerging in Hanoi over the last decade. Both DF epidemiology and climate in Hanoi are strongly seasonal. This study aims at characterizing the seasonality of DF in Hanoi and its links to climatic variables as DF incidence increases from year to year.

Methods: Clinical suspected cases of DF from the 14 central districts of Hanoi were obtained from the Ministry of Health over a 8-year period (2002-2009). Wavelet decompositions were used to characterize the main periodic cycles of DF and climatic variables as well as the mean phase angles of these cycles. Cross-wavelet spectra between DF and each climatic variables were also computed. DF reproductive ratio was calculated from Soper's formula and smoothed to highlight both its long-term trend and seasonality.

Results: Temperature, rainfall, and vapor pressure show strong seasonality. DF and relative humidity show both strong seasonality and a sub-annual periodicity. DF reproductive ratio is increasing through time and displays two clear peaks per year, reflecting the sub-annual periodicity of DF incidence. Temperature, rainfall and vapor pressure lead DF incidence by a lag of 8-10 weeks, constant through time. Relative humidity leads DF by a constant lag of 18 weeks for the annual cycle and a lag decreasing from 14 to 5 weeks for the sub-annual cycle.

Conclusion: Results are interpreted in terms of mosquito population dynamics and immunological interactions between the different dengue serotypes in the human compartment. Given its important population size, its strong seasonality and its dengue emergence, Hanoi offers an ideal natural experiment to test hypotheses on dengue serotypes interactions, knowledge of prime importance for vaccine development.

Figure 1

The reproductive ratio, time series and wavelet power spectrum of DF in Hanoi (14 districts) from 2002 to 2009. (A) The reproductive ratio was estimated from equation 2 (see text) and smoothed by lowest regressions with smoothing factors equal to 0.05 (blue) and 0.90 (red). The shaded areas around the lines represent the 95% confidence intervals calculated assuming a normal distribution of errors. (B) Time series of the square-root transformed weekly DF incidence. (C) Wavelet power spectrum of the square-root transformed weekly DF incidence. The black contour lines show the regions of power significant at the alpha-risk of 0.05. The paled region of the spectrum delineates the cone of influence due to the zero-padding of the time series. The power increases from dark blue to dark red.

Figure 2

Time series and wavelet power spectra of mean temperature, cumulative rainfall and mean absolute and relative humidities in Hanoi, from 2002 to 2009. The black contour lines show the regions of power significant at the alpha-risk of 0.05. The paled region of the spectrum delineates the cone of influence due to the zero-padding of the time series. The power increases from dark blue to dark red.

Figure 3

Cross-correlation between the 4 climatic variables: mean temperature, rainfall, vapor pressure and relative humidity. Horizontal blue dotted lines materialize the significativity thresholds at p = 0.05.

Figure 4

Cross-wavelet power spectra between DF and mean temperature (A), rainfall (B) and absolute (C) and relative (D) humidities in Hanoi from 2002 to 2009 (left column). The right column shows the phase angles of the climatic variables (blue, left y-axis) and DF (red, left y-axis), as well as their difference (black, right y-axis). These phase angles are calculated on signals that have been filtered around the period of maximal power in the spectra of the left column, i.e. annual periodicity for all the climatic variables, as well as also the semi-annual periodicity for the relative humidity. In spectra of the left column, the black contour lines show the regions of power significant at the alpha-risk of 0.05, the paled region of the spectrum delineates the cone of influence due to the zero-padding of the time series, and the power increases from dark blue to dark red.