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Regional epidemic dynamics and Delta variant diversity resulted in varying rates of spread of Omicron-BA.1 in Mexico
Selene Zárate; Blanca Taboada; Mauricio Rosales-Rivera; Rodrigo García-López; Jose Esteban Muňoz-Medina; Alejandro Sánchez-Flores; Alfredo Herrera-Estrella; Bruno Gómez-Gil; Nelly Selem Mójica; Angel Gustavo Salas-Lais; Joel Armando Vázquez-Pérez; David Alejandro Cabrera-Gaytán; Larissa Fernandes-Matano; Luis Antonio Uribe-Noguez; Juan Bautista Chale-Dzul; Brenda Irasema Maldonado Meza; Fidencio Mejía-Nepomuceno; Rogelio Pérez-Padilla; Rosa María Gutiérrez-Ríos; Antonio Loza; Susana López; Carlos F. Arias.
Affiliation
  • Selene Zárate; Posgrado en Ciencias Genómicas, Universidad Autónoma de la Ciudad de México, Ciudad de México, México.
  • Blanca Taboada; Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
  • Mauricio Rosales-Rivera; Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
  • Rodrigo García-López; Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
  • Jose Esteban Muňoz-Medina; Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Ciudad de México, México
  • Alejandro Sánchez-Flores; Unidad Universitaria de Secuenciación Masiva y Bioinformática, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México.
  • Alfredo Herrera-Estrella; Laboratorio Nacional de Genómica para la Biodiversidad-Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados del IPN, Irapuato 36821, Méx
  • Bruno Gómez-Gil; Centro de Investigación en Alimentación y Desarrollo AC, Mazatlán, Sinaloa, México.
  • Nelly Selem Mójica; Centro de Ciencias Matemáticas, Universidad Nacional Autónoma de Mexico, Morelia, Michoacán, México.
  • Angel Gustavo Salas-Lais; Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Ciudad de México, México
  • Joel Armando Vázquez-Pérez; Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Ciudad de México, México.
  • David Alejandro Cabrera-Gaytán; Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Ciudad de México, México
  • Larissa Fernandes-Matano; Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Ciudad de México, México
  • Luis Antonio Uribe-Noguez; Laboratorio Central de Epidemiología, Instituto Mexicano del Seguro Social, Ciudad de México, México.
  • Juan Bautista Chale-Dzul; Unidad de Investigación Médica Yucatán, Instituto Mexicano del Seguro Social, Mérida, Yucatán, México.
  • Brenda Irasema Maldonado Meza; Centro de Investigación Biomédica del Noreste, Instituto Mexicano del Seguro Social, Monterrey, Nuevo León, México.
  • Fidencio Mejía-Nepomuceno; Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Ciudad de México, México.
  • Rogelio Pérez-Padilla; Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Ciudad de México, México.
  • Rosa María Gutiérrez-Ríos; Departamento de Microbiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México.
  • Antonio Loza; Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
  • Susana López; Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
  • Carlos F. Arias; Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
Preprint in En | PREPRINT-BIORXIV | ID: ppbiorxiv-512746
ABSTRACT
The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In Mexico, this subvariant began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in the country. Unlike previous SARS-CoV-2 variants, BA.1 did not acquire local substitutions nor exhibited a geographically distinct circulation pattern in Mexico. However, a regional difference in the speed of the replacement of the Delta variant was observed, as some northern states showed persistence of Delta lineages well into February 2022. Mexican states were divided into four regions (North, Central North, Central South, and Southeast) based on the lineage circulation before the dominance of BA.1 to study possible causes for this difference. For each region, the time to fixation of BA.1, the diversity of Delta sublineages in the weeks preceding BA.1 entry, the population density, and the level of virus circulation during the inter-wave interval were determined. An association between a faster Omicron spread and lower Delta diversity, as well as fewer COVID-19 cases during the Delta-BA.1.x inter-wave period, was observed. For example, the North region exhibited the slowest spread but had the highest diversity of Delta sublineages and the greatest number of inter-wave cases relative to the maximum amount of the virus circulating in the region, whereas the Southeast region showed the opposite. Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics. Nonetheless, if there is a significant difference in the fitness of the variants or the time allowed for the competition is sufficient, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico. Impact statementThe surveillance of lineage circulation of SARS-CoV-2 has helped identify variants that have a transmission advantage and are of concern to public health and to track the virus dispersion accurately. However, many factors contributing to differences in lineage spread dynamics beyond the acquisition of specific mutations remain poorly understood. In this work, a description of BA.1 entry and dispersion within Mexico is presented, and which factors potentially affected the spread rates of the Omicron variant BA.1 among geographical regions in the country are analyzed, underlining the importance of population density, the proportion of active cases, and viral lineage diversity and identity before the entry of BA.1. Data summaryThis work was carried out using data shared through the GISAID initiative. All sequences and metadate are available through GISAID with the accession EPI_SET_220927gw, accession numbers and metadata are also reported in the supplemental material of this article. Epidemiological data was obtained though the Secretaria de Salud website (https//www.gob.mx/salud/documentos/datos-abiertos-152127),
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Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Language: En Year: 2022 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Language: En Year: 2022 Document type: Preprint