Spatio-temporal dynamics of dengue in Brazil: Seasonal travelling waves and determinants of regional synchrony

Abstract

Dengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years. Here, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterise the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondônia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapá) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period. We also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence. This study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.

Fig 1. Summary of the spatio-temporal dynamics of dengue in Brazil.

(A) Average annual dengue risk per 10,000 inhabitants in 2001–2016 for each state. Administrative boundaries were obtained from GADM (https://gadm.org). (B) Heat map of log-normalised average number of monthly cases in 2001–2016 for Brazilian states sorted by longitude: west (top) to east (bottom). (C) Log of monthly dengue cases per 10,000 inhabitants in Brazil. (D) Heat map of log-normalised case series for Brazilian states sorted by longitude: west (top) to east (bottom). Colours were scaled for each state independently so that yellow indicates the lowest number of dengue cases and red indicates the maximum.

Fig 2. Average phase lags of seasonal dengue between Brazilian states.

(A) For each state, median and 95% range of annual phase lags from other states over the study period. States were ordered by their median phase lag. (B) Map of the relative timing of annual dengue waves, which was defined using the average annual phase lag of each state from every other state. Administrative boundaries were obtained from GADM (https://gadm.org).

Fig 3. Epidemic synchrony and annual phase coherence between Brazilian Urban-2 regions.

Epidemic synchrony (A) and annual phase coherence (B) summarised using nonparametric spline covariance function. Solid blue line describes the mean pairwise correlation from the data and the dotted lines represent the 95% envelope for bootstrapped correlations of case and annual phase angle time series, respectively. Red line indicates global countrywide correlation.

Fig 4. Variance explained for models of epidemic synchrony and annual phase coherence.

R² for epidemic synchrony (A) and annual phase coherence (B) predicted by models 4–10 depending on the spatial scale considered.