4.6 Article

Retrospective Genomic Surveillance of Chikungunya Transmission in Minas Gerais State, Southeast Brazil

Journal

MICROBIOLOGY SPECTRUM
Volume -, Issue -, Pages -

Publisher

AMER SOC MICROBIOLOGY
DOI: 10.1128/spectrum.01285-22

Keywords

CHIKV; genomic monitoring; southeast Brazil; Nanopore sequencing

Categories

Funding

  1. U.S. National Institutes of Health [U01 AI151698]
  2. Brazilian Ministry of Health [SCON2021-00180]
  3. Fundacao de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ) [E-26/202.248/2018 (238504), E26/202.665/2019 (247400)]
  4. Brazilian National Council for Scientific and Technological Development [CNPq-141861/2020-7]
  5. PON grant Ricerca e Innovazione (2014 to 2020)
  6. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil (CAPES) [001]

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Arbovirus infections in Brazil, such as chikungunya, dengue, yellow fever, and Zika, are major public health concerns. However, the limited availability of genomic data hinders our understanding of these outbreaks. This study combines epidemiological analysis and portable genome sequencing to retrospectively describe the CHIKV epidemic in Minas Gerais between 2017 and 2021. The results show multiple introductions of CHIKV into the state, likely from other regions of Brazil, and highlight the importance of genomic surveillance in infectious disease control.
Arbovirus infections in Brazil, including chikungunya, dengue, yellow fever, and Zika, result in considerable morbidity and mortality and are pressing public health concerns. However, our understanding of these outbreaks is hampered by the limited availability of genomic data. Brazil accounted for a total number of 1,276,194 reported cases of chikungunya fever between 2014 and 2022. Additionally, since 2015, the country has experienced an increasing death toll, in which the Northeast and Southeast regions appear to report the worst scenarios. Although the CHIKV transmission dynamics have been studied in many parts of the country since its introduction in 2014, little is still known about chikungunya virus (CHIKV) transmission and genetic diversity in the state of Minas Gerais, located in southeast Brazil. Moreover, no studies have been published characterizing CHIKV genomic surveillance in this state. Thus, to retrospectively explore the CHIKV epidemic in Minas Gerais, we generated 40 genomes from clinical samples using Nanopore sequencing. Phylogenetic analysis indicated that multiple introductions of CHIKV occurred, likely from the northeastern Brazilian states, with the most recent common ancestral strain dating to early March 2016, which is in agreement with local epidemiological reports. Additionally, epidemiological data reveals a decline in the number of reported cases from 2017 to 2021, indicating that population immunity or changes in vector activity may have contributed to the decreasing waves of CHIKV infection. Together, our results shed light on the dispersion dynamics of CHIKV and show that infections decreased from March 2017 to January 2021 despite multiple introductions into Minas Gerais State. In conclusion, our study highlights the importance of combining genomic and epidemiological data in order to assist public health laboratories in monitoring and understanding the patterns and diversity of mosquito-borne viral epidemics. IMPORTANCE Arbovirus infections in Brazil, including chikungunya, dengue, yellow fever, and Zika, result in considerable morbidity and mortality and are pressing public health concerns. However, our understanding of these outbreaks is hampered by the limited availability of genomic data. In this study, we combine epidemiological analysis and portable genome sequencing to retrospectively describe the CHIKV epidemic in Minas Gerais between 2017 and 2021. Our results indicate that the East/Central/South African (ECSA) CHIKV lineage was introduced into Minas Gerais by three distinct events, likely from the North and Northeast regions of Brazil. Our study provides an understanding of how CHIKV initiates transmission in the region and illustrates that genomics in the field can augment traditional approaches to infectious disease surveillance and control.

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