Genomic, epidemiological and digital surveillance of Chikungunya virus in the Brazilian Amazon

Abstract

Background: Since its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country.

Methodology/principal findings: We report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraima's state, located in the Brazilian Amazon region. We generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraima's population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima.

Conclusions/significance: This study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region.

Fig 1. Context of this study.

A. Map showing municipalities of Roraima state, including Boa Vista, bordering countries (Venezuela and French Guiana) and bordering Brazilian federal states (Amazonas and Pará). B. Map of Brazilian states, showing the states from which CHIKV sequence data in this study was analysed (Bahia, Alagoas, Pernambuco, Paraíba, Amazonas and Roraima). C. Barplot showing the annual number of notified CHIKV cases in selected states of Brazil (data obtained from the Brazilian Ministry of Health). Map was made with Natural Earth. Free vector and raster map data at naturalearthdata.com.

Fig 2. Sequencing statistics, temporal signal and evolutionary rates of the CHIKV-ECSA lineage.

A. Genome coverage plotted against RT-qPCR CT-values for the newly generated sequence data. B. Genetic divergence regressed against dates of sample collection for dataset 2 (CHIKV-ECSA-Br lineage). C. Evolutionary rate estimates for the CHIKV-ECSA-Br lineage obtained by this study (circle number 1) compared to published evolutionary rates obtained for other lineages. Circles numbered 2 to 8 represent point estimates reported in [1, 9, 80]. Horizontal bars represent 95% highest posterior density credible intervals for evolutionary rates.

Fig 3. Genetic analysis of the CHIKV-ECSA genotype.

A. Maximum likelihood phylogeny depicting the monophyletic clade containing all the Brazilian ECSA isolates (ECSA-Br lineage). B. Time-calibrated phylogeny of all available CHIKV-ECSA whole genome sequences from Brazil, including 18 novel genomes from Roraima and Amazonas states. Colours correspond to state of sample collection. Violin plots show 95% Bayesian credible intervals for associated node heights [39].

Fig 4. Digital surveillance of chikungunya in the Brazilian Brazil.

Notified (orange) and confirmed (purple) cases in the central public health laboratories in Roraima state (a) and the Amazonas state (c) from January 2016 to January 2018. Dashed grey lines in (a) and (c) represent Google Trends activity for the term “chikungunya” in Roraima and Amazonas, respectively. Panels b and d show the correlation between Google Trends activity and cases notified in Roraima and Amazonas, respectively. Strength of the association was measured using the Spearman’s rank correlation coefficient (in panel b: p-value < 0.001; panel d: p-value = 5.183e-09).