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[Preprint]. 2023 Apr 17:2023.04.16.23288635.
doi: 10.1101/2023.04.16.23288635.

Rapid epidemic expansion of chikungunya virus-ECSA lineage in Paraguay

Affiliations

Rapid epidemic expansion of chikungunya virus-ECSA lineage in Paraguay

Marta Giovanetti et al. medRxiv. .

Update in

  • Rapid Epidemic Expansion of Chikungunya Virus East/Central/South African Lineage, Paraguay.
    Giovanetti M, Vazquez C, Lima M, Castro E, Rojas A, Gomez de la Fuente A, Aquino C, Cantero C, Fleitas F, Torales J, Barrios J, Ortega MJ, Gamarra ML, Villalba S, Alfonzo T, Xavier J, Adelino T, Fritsch H, Iani FCM, Pereira GC, de Oliveira C, Schuab G, Rodrigues ES, Kashima S, Leite J, Gresh L, Franco L, Tegally H, Van Voorhis WC, Lessels R, de Filippis AMB, Ojeda A, Sequera G, Montoya R, Holmes EC, de Oliveira T, Rico JM, Lourenço J, Fonseca V, Alcantara LCJ. Giovanetti M, et al. Emerg Infect Dis. 2023 Sep;29(9):1859-1863. doi: 10.3201/eid2909.230523. Epub 2023 Jul 25. Emerg Infect Dis. 2023. PMID: 37488810 Free PMC article.

Abstract

The spread of vector-borne viruses, such as CHIKV, is a significant public health concern in the Americas, with over 120,000 cases and 51 deaths in 2023, of which 46 occurred in Paraguay. Using a suite of genomic, phylodynamic, and epidemiological techniques, we characterized the ongoing large CHIKV epidemic in Paraguay.

Article summary line: Genomic and epidemiological characterization of the ongoing Chikungunya virus epidemic in Paraguay.

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Figures

Figure 1.
Figure 1.. Spatial and temporal distribution of CHIKV cases in Paraguay.
A) Temperature trends in Paraguay between 1981 and 2022. The yearly mean (red full line), yearly minimum and maximum (grey full lines), yearly 50% quantiles (dark grey area) and min, max and mean temperature in 1981 (dashed grey and red lines, respectively) are shown; B) Map of Paraguay showing the number of CHIKV genome sequences by departments. The size of the circles indicates the number of new genomes generated in this study; C) Weekly notified chikungunya cases (grey), incidence normalized per 100 K individuals (blue) and cumulative deaths (green) in 2022-2023 (until EW11), red bars at the bottom highlight the dates of sample collection of the genomes generated in this study; D) Boxplot of the patient’s (representing the study population) age and clinical outcomes value distribution. The Kruskal-Wallis non-parametric approach was used to determine the strength of association within the different clinical outcomes. E) Time-resolved maximum likelihood tree including the newly complete genome sequence from Paraguay (n=179) generated in this study combined with publicly available sequences (n=715) from GenBank collected up to March 30, 2023. Colors indicate geographic location of sampling. Support for branching structure is shown by bootstrap values at key nodes.
Figure 2.
Figure 2.. Expansion of the CHIKV-ECSA epidemic in Paraguay.
A) Maximum Likelihood (ML) phylogeny constructed using n=174 CHIKV genome sequences from the PY clade 2 associated with the 2022-2023 epidemic. The tips were colored based on the clinical outcomes. Neurological and neonatal cases have been highlighted in the tree using blue and red borders, respectively. The length of a branch indicates the amount of sequence evolution; B) Regression of root-to-tip genetic distances and sampling dates estimated using TempEst v.1.5.3, buffers (shaded area) representing 90% confidence intervals. Colors indicate geographic location of sampling; C) Spatiotemporal reconstruction of the spread of CHIKV-ECSA in Paraguay. Circles represent nodes of the maximum clade credibility phylogeny, colored according to their inferred time of occurrence (scale shown). Shaded areas represent the 80% highest posterior density interval and depict the uncertainty of the phylogeographic estimates for each node. Solid curved lines denote the links between nodes and the directionality of movement. Differences in population density are shown on a grey-white scale.

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