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SARS-CoV-2 variant transition dynamics are associated with vaccination rates, number of co-circulating variants, and natural immunity
Lauren J Beesley; Kelly R Moran; Kshitij Wagh; Lauren Castro; James Theiler; Hyejin Yoon; Will Fischer; Nicholas W Hengartner; Bette Korber; Sara Del Valle.
Afiliação
  • Lauren J Beesley; Los Alamos National Laboratory
  • Kelly R Moran; Los Alamos National Laboratory
  • Kshitij Wagh; Los Alamos National Laboratory
  • Lauren Castro; Los Alamos National Laboratory
  • James Theiler; Los Alamos National Laboratory
  • Hyejin Yoon; Los Alamos National Laboratory
  • Will Fischer; Los Alamos National Laboratory
  • Nicholas W Hengartner; Los Alamos Nationa Lab
  • Bette Korber; Los Alamos National Laboratory
  • Sara Del Valle; Los Alamos National Laboratory
Preprint em En | PREPRINT-BIORXIV | ID: ppbiorxiv-517139
ABSTRACT
BackgroundThroughout the COVID-19 pandemic, the SARS-CoV-2 virus has continued to evolve, with new variants outcompeting existing variants and often leading to different dynamics of disease spread. MethodsIn this paper, we performed a retrospective analysis using longitudinal sequencing data to characterize differences in the speed, calendar timing, and magnitude of 13 SARS-CoV-2 variant waves/transitions for 215 countries and sub-country regions, between October 2020 and October 2022. We then clustered geographic locations in terms of their variant behavior across all Omicron variants, allowing us to identify groups of locations exhibiting similar variant transitions. Finally, we explored relationships between heterogeneity in these variant waves and time-varying factors, including vaccination status of the population, governmental policy, and the number of variants in simultaneous competition. FindingsThis work demonstrates associations between the behavior of an emerging variant and the number of co-circulating variants as well as the demographic context of the population. We also observed an association between high vaccination rates and variant transition dynamics prior to the Mu and Delta variant transitions. InterpretationThese results suggest the behavior of an emergent variant may be sensitive to the immunologic and demographic context of its location. Additionally, this work represents the most comprehensive characterization of variant transitions globally to date. FundingLaboratory Directed Research and Development (LDRD), Los Alamos National Laboratory Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSARS-CoV-2 variants with a selective advantage are continuing to emerge, resulting in variant transitions that can give rise to new waves in global COVID-19 cases and changing dynamics of disease spread. While variant transitions have been well studied individually, more work is needed to better understand how variant transitions have occurred in the past and how properties of these transitions may relate to vaccination rates, natural immunity, and population demographics. Added value of this studyOur retrospective study integrates metadata based on 12.8 million SARS-CoV-2 sequences available through the Global Initiative on Sharing All Influenza Data (GISAID) with clinical and demographic data to characterize heterogeneity in variant waves/transitions across the globe throughout the COVID-19 pandemic. We demonstrate that properties of the variant transitions (e.g., speed, timing, and magnitude of the transition) are associated with vaccination rates, prior COVID-19 cases, and the number of co-circulating variants in competition. Implications of all the available evidenceOur results indicate that there is substantial heterogeneity in how an emerging variant may compete with other viral variants across locations, and suggest that each locations contemporaneous immunologic landscape may play a role in these interactions.
Licença
cc_by_nc_nd
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-BIORXIV Tipo de estudo: Experimental_studies / Observational_studies / Prognostic_studies / Rct Idioma: En Ano de publicação: 2022 Tipo de documento: Preprint
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-BIORXIV Tipo de estudo: Experimental_studies / Observational_studies / Prognostic_studies / Rct Idioma: En Ano de publicação: 2022 Tipo de documento: Preprint