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

      research-article
      1 , 2 , 3 , 4 , 3 , 5 , 3 , 5 , 4 , 6 , 1 , 1 , 7 , 8 , 9 , 10 , 8 , 11 , 12 , 8 , 8 , 4 , 4 , 2 , 13 , 13 , 8 , 4 , 4 , 14 , 14 , 14 , 15 , 16 , 15 , 17 , 18 , 19 , 19 , 19 , 19 , 7 , 1 , 12 , 8 , 2 , 19 , 3 , 4 , * , 8 , *
      PLoS Neglected Tropical Diseases
      Public Library of Science

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          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 R 0 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.

          Author summary

          Until the end of 2017, Brazil notified the highest number of infections caused by chikungunya virus (CHIKV) in the Americas. We investigated a large CHIKV outbreak in Boa vista municipality in the Brazilian Amazon region. Rapid portable genome sequencing of 20 novel isolates and subsequent genetic analysis revealed that ECSA lineage was introduced from northeastern Brazil to Roraima around July 2016. Epidemiological analyses suggest a basic reproductive number of R 0 of 1.66, which suggests that approximately 39% of Roraima’s population was infected with CHIKV-ECSA. Given the dominance of the CHIKV-Asian genotype in the Americas, our data highlights the rapid spread of a less understood and poorly characterized CHIKV-ECSA genotype in Brazil. Investigations on potential associations between public health impact of CHIKV and genetic diversity of circulating strains are warranted to better evaluate its impact in Brazil and beyond.

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          Most cited references57

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          Smooth skyride through a rough skyline: Bayesian coalescent-based inference of population dynamics.

          Kingman's coalescent process opens the door for estimation of population genetics model parameters from molecular sequences. One paramount parameter of interest is the effective population size. Temporal variation of this quantity characterizes the demographic history of a population. Because researchers are rarely able to choose a priori a deterministic model describing effective population size dynamics for data at hand, nonparametric curve-fitting methods based on multiple change-point (MCP) models have been developed. We propose an alternative to change-point modeling that exploits Gaussian Markov random fields to achieve temporal smoothing of the effective population size in a Bayesian framework. The main advantage of our approach is that, in contrast to MCP models, the explicit temporal smoothing does not require strong prior decisions. To approximate the posterior distribution of the population dynamics, we use efficient, fast mixing Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. In a simulation study, we demonstrate that the proposed temporal smoothing method, named Bayesian skyride, successfully recovers "true" population size trajectories in all simulation scenarios and competes well with the MCP approaches without evoking strong prior assumptions. We apply our Bayesian skyride method to 2 real data sets. We analyze sequences of hepatitis C virus contemporaneously sampled in Egypt, reproducing all key known aspects of the viral population dynamics. Next, we estimate the demographic histories of human influenza A hemagglutinin sequences, serially sampled throughout 3 flu seasons.
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            Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci.

            Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02_AG gene sequences sampled from Cameroon. Our results are consistent with HIV prevalence data and uncover some aspects of the population history that go undetected in Bayesian parametric estimation. Finally, we recover an older and more reconcilable TMRCA for a classic ancient DNA data set.
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              Emergence and potential for spread of Chikungunya virus in Brazil

              Background In December 2013, an outbreak of Chikungunya virus (CHIKV) caused by the Asian genotype was notified in the Caribbean. The outbreak has since spread to 38 regions in the Americas. By September 2014, the first autochthonous CHIKV infections were confirmed in Oiapoque, North Brazil, and in Feira de Santana, Northeast Brazil. Methods We compiled epidemiological and clinical data on suspected CHIKV cases in Brazil and polymerase-chain-reaction-based diagnostic was conducted on 68 serum samples from patients with symptom onset between April and September 2014. Two imported and four autochthonous cases were selected for virus propagation, RNA isolation, full-length genome sequencing, and phylogenetic analysis. We then followed CDC/PAHO guidelines to estimate the risk of establishment of CHIKV in Brazilian municipalities. Results We detected 41 CHIKV importations and 27 autochthonous cases in Brazil. Epidemiological and phylogenetic analyses indicated local transmission of the Asian CHIKV genotype in Oiapoque. Unexpectedly, we also discovered that the ECSA genotype is circulating in Feira de Santana. The presumed index case of the ECSA genotype was an individual who had recently returned from Angola and developed symptoms in Feira de Santana. We estimate that, if CHIKV becomes established in Brazil, transmission could occur in 94% of municipalities in the country and provide maps of the risk of importation of each strain of CHIKV in Brazil. Conclusions The etiological strains associated with the early-phase CHIKV outbreaks in Brazil belong to the Asian and ECSA genotypes. Continued surveillance and vector mitigation strategies are needed to reduce the future public health impact of CHIKV in the Americas. Electronic supplementary material The online version of this article (doi:10.1186/s12916-015-0348-x) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Role: Data curationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: SupervisionRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Supervision
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Supervision
                Role: Formal analysisRole: InvestigationRole: Methodology
                Role: Formal analysisRole: InvestigationRole: Methodology
                Role: InvestigationRole: Project administrationRole: ResourcesRole: Validation
                Role: Data curationRole: InvestigationRole: MethodologyRole: Validation
                Role: Formal analysisRole: InvestigationRole: Methodology
                Role: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: InvestigationRole: ValidationRole: Writing – review & editing
                Role: InvestigationRole: Methodology
                Role: ConceptualizationRole: MethodologyRole: Project administrationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Validation
                Role: Formal analysisRole: Investigation
                Role: ConceptualizationRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: Validation
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: Supervision
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: Project administrationRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                plosntds
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                7 March 2019
                March 2019
                : 13
                : 3
                : e0007065
                Affiliations
                [1 ] Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, FIOCRUZ, Manaus, Brazil
                [2 ] Instituto de Medicina Tropical e Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
                [3 ] Laboratório de Flavivírus, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
                [4 ] Laboratório de Genética Celular e Molecular, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
                [5 ] Laboratório de Patologia Experimental, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil
                [6 ] Laboratório Central de Saúde Pública, Instituto Octávio Magalhães, FUNED, Belo Horizonte, Minas Gerais, Brazil
                [7 ] Laboratório de Virologia Molecular, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
                [8 ] Department of Zoology, University of Oxford, South Parks Road, Oxford, United Kingdom
                [9 ] Harvard Medical School, Department of Pediatrics, Boston, MA, United States of America
                [10 ] Computational Health Informatics Program, Boston Children’s Hospital, Boston, MA, United States of America
                [11 ] Computational Epidemiology Lab, Boston Children’s Hospital, Boston, MA, United States of America
                [12 ] Institute of Microbiology and Infection, University of Birmingham, Birmingham, United Kingdom
                [13 ] Evandro Chagas Institute, Brazilian Ministry of Health, Ananindeua, Brazil
                [14 ] Laboratório Central de Saúde Pública, Boa Vista, Roraima, Brazil
                [15 ] Superintendência de Vigilância em Saúde, Secretaria Municipal de Saúde de Boa Vista, Roraima, Brazil
                [16 ] Departamento de Virologia, Fundação de Medicina Tropical Doutor Heitor Vieira Dourado, Manaus, Amazonas, Brazil
                [17 ] Laboratório Central de Saúde Pública do Amazonas, Manaus, Amazonas, Brazil
                [18 ] Organização Pan—Americana da Saúde/Organização Mundial da Saúde—(OPAS/OMS), Brasília-DF, Brazil
                [19 ] Secretaria de Vigilância em Saúde, Ministério da Saúde (SVS/MS), Brasília-DF, Brazil
                Louisiana State University, UNITED STATES
                Author notes

                The authors declare no competing interests.

                Author information
                http://orcid.org/0000-0003-3916-2018
                http://orcid.org/0000-0002-3629-8529
                http://orcid.org/0000-0002-9318-2581
                http://orcid.org/0000-0003-1271-8549
                http://orcid.org/0000-0002-6769-9931
                http://orcid.org/0000-0001-8839-2798
                Article
                PNTD-D-18-01912
                10.1371/journal.pntd.0007065
                6424459
                30845267
                db2bc92d-d3ef-4913-8b43-f2f3f7bcf73f
                © 2019 Naveca et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 December 2018
                : 1 February 2019
                Page count
                Figures: 4, Tables: 1, Pages: 21
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 204311/Z/16/Z
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award ID: 440685/2016-8
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100002322, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
                Award ID: 88887.130716/2016-00
                Award Recipient :
                The ZIBRA-2 project is funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (grant 440685/2016-8) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (grant 88887.130716/2016-00). FGN is funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico ( http://www.cnpq.br, grant 440856/2016-7) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior ( http://www.capes.gov.br, grants 88881.130825/2016-00 and 88887.130823/2016-00). L.C.J.A. is supported by the EU’s Horizon 2020 Programme through ZIKAlliance (grant PRES-005-FEX-17-4-2-33). N.R.F. is funded by a Royal Society and Wellcome Trust Sir Henry Dale Fellowship (204311/Z/16/Z), internal GCRF grant 005073, and John Fell Research Fund grant 005166. This research received funding from the ERC (grant agreement 614725-PATHPHYLODYN). MS was partially supported by the National Institute of General Medical Sciences of the NIH (USA) under award number R01GM130668. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
                Categories
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                Organisms
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                Alphaviruses
                Chikungunya Virus
                Biology and Life Sciences
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                Custom metadata
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                2019-03-19
                XML files and datasets analysed in this study are available in the GitHub respository ( https://github.com/arbospread/chik-amazon). New sequences have been deposited in GenBank under accession numbers MK121891-MK121908 (CHIKV-ECSA) and MK134712-MK134713 (CHIKV-Asian).

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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