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. 2017 Jul 25;11(7):e0005653.
doi: 10.1371/journal.pntd.0005653. eCollection 2017 Jul.

Tracking the return of Aedes aegypti to Brazil, the major vector of the dengue, chikungunya and Zika viruses

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Tracking the return of Aedes aegypti to Brazil, the major vector of the dengue, chikungunya and Zika viruses

Panayiota Kotsakiozi et al. PLoS Negl Trop Dis. .

Abstract

Background: Aedes aegypti, commonly known as "the yellow fever mosquito", is of great medical concern today primarily as the major vector of dengue, chikungunya and Zika viruses, although yellow fever remains a serious health concern in some regions. The history of Ae. aegypti in Brazil is of particular interest because the country was subjected to a well-documented eradication program during 1940s-1950s. After cessation of the campaign, the mosquito quickly re-established in the early 1970s with several dengue outbreaks reported during the last 30 years. Brazil can be considered the country suffering the most from the yellow fever mosquito, given the high number of dengue, chikungunya and Zika cases reported in the country, after having once been declared "free of Ae. aegypti".

Methodology/principal findings: We used 12 microsatellite markers to infer the genetic structure of Brazilian Ae. aegypti populations, genetic variability, genetic affinities with neighboring geographic areas, and the timing of their arrival and spread. This enabled us to reconstruct their recent history and evaluate whether the reappearance in Brazil was the result of re-invasion from neighboring non-eradicated areas or re-emergence from local refugia surviving the eradication program. Our results indicate a genetic break separating the northern and southern Brazilian Ae. aegypti populations, with further genetic differentiation within each cluster, especially in southern Brazil.

Conclusions/significance: Based on our results, re-invasions from non-eradicated regions are the most likely scenario for the reappearance of Ae. aegypti in Brazil. While populations in the northern cluster are likely to have descended from Venezuela populations as early as the 1970s, southern populations seem to have derived more recently from northern Brazilian areas. Possible entry points are also revealed within both southern and northern clusters that could inform strategies to control and monitor this important arbovirus vector.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Collection sites and preliminary STRUCTURE analysis.
Collection sites for all the Ae. aegypti populations used in this study (A). Populations studied previously [7] are indicated as blue dots whereas the new collections as red squares. Three newly added populations that exhibited signs of admixed ancestry in STRUCTURE are indicated with green squares. The area included in the dashed line shows the northern genetic Cluster identified by Monteiro et al. [7] and confirmed in this study as indicated by STRUCTURE (B). Code numbers are as in S1 Table. STRUCTURE bar plot for all Ae. aegypti populations used in this study (B). Population names are reported on its X axis, with numbers as in Fig 1A and S1 Table. The Y axis reports the probability of each individual (Q-value) assigned to one of the two genetic groups identified by STRUCTURE, which are represented by different colors (blue and orange). Each bar represents an individual. Individuals with 100% assignment to one group are identified by a single color. Individuals with mixed ancestry are represented by bars with different percentages of the two colors. The thick black lines within the plots indicate population limits.
Fig 2
Fig 2. Evolutionary scenarios of Aedes aegypti re-invasion in Brazil.
Evolutionary scenarios evaluated using Approximate Bayesian Computation (ABC) inference as implemented by the DIYABC software [46]. Scenarios tested included five groups: USA, Venezuela, Dominica, Cluster 2 (northern Brazilian populations), and Cluster 1 (southern Brazilian populations). The time scale on the right of each scenario is the relative time (in generations) with t0 representing the most recent time point and increasing values going back in time. Posterior probabilities (PP) are shown for each scenario. The best supported scenario is indicated by an asterisk (*).
Fig 3
Fig 3. Genetic structure analysis for Cluster 1.
STRUCTURE bar plots for Ae. aegypti populations of southern Brazil-Dominica data set (A). See legend of Fig 1B for details. The genetic clusters as indicated by the Evanno method are plotted. Populations’ code numbers in brackets are referred to the map codes in B and as in S1 Table. The distribution of the Clusters populations (Cluster 1; squares and Cluster 2; dots) as indicated by the preliminary STRUCTURE analysis with focus on the sub-clusters (sub-clusters 1A; light blue and 1B; orange) found within Cluster 1 populations is presented (B). The main rivers in the area are presented.
Fig 4
Fig 4. Genetic structure analysis for Cluster 2.
STRUCTURE bar plots for the Ae. aegypti populations of Cluster 2 data set (A). See legend of Fig 1B and Fig 3 for details. The distribution of the major Clusters with focus on the two sub-clusters (sub-clusters 2A; light blue and 2B; orange) found within Cluster 2 populations is presented (B).

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