Unveiling the Dynamics of SARS‐CoV‐2 Gamma and Delta Waves in Paraná, Brazil – Delta Displacing a Persistent Gamma Through Alternative Routes of Dispersal

• DOI: 10.1002/jmv.70318
• Publication Date: 2025-04-06T01:32:03Z
• Authors: Emanuele Gustani‐...; Carlos Eduardo Buss; Carlos Alberto Ol...; Isabela Medeiros ...; Kamila Chagas Per...; Glauco Akelinghto...; Bárbara Luisa Fer...; Fernanda Ivanski; Bárbara Mendes Pa...; Felipe Francisco ...; Franciele Ani Cao...; Leia Carolina Lucio; Lirane Elize Defa...; Marcos Pillegi; Jeane Eliete Lagu...; Marcia Edilaine L...; Maria Leandra Ter...; Dennis Armando Be...; Alex Sandro Jorge; Jaime Luis Lopes ...; Bruno Zagonel Pio...; Irina Nastassja R...; Diogo Muller Lacerda; Angélica Regina C...; Marco Antonio Lar...; Álvaro Largura; Patrik André Barcaro; Vitoria Caroline ...; Marcos Aurélio Pe...; Glauco Nonose Negrão; Carla Luiza da Silva; Daniela Frizon Al...; Tony Vinicius Mor...; Andrea Name Colad...; Emerson Carraro; Wilson Araújo Silva; Phillippe Lemey; David Livingstone...

ABSTRACTThe Gamma and Delta variants of concern (VOCs) of SARS‐CoV‐2 drove the second and third wave in Brazil and significantly intensified the number of cases and deaths. In this study, we investigate the timeline and origins of the Gamma and Delta variants using a spatiotemporal analysis based on 1508 genomes collected between March and September 2021 from health administrative regions in Paraná state, Brazil. Our findings indicate that community transmission of Gamma‐P.1 began in late 2020, with substantial contributions from the Northeast and North regions. In contrast, our analysis of the Delta‐AY.101 genomes underscored the crucial role of Paraná in national‐level transmission dynamics beginning in late March 2021. At a local level, the movement estimates inferred from the monophyletic clades showed that the Curitiba health region was the primary source for Gamma‐P.1, with a substantial contribution from Londrina. This health‐region also emerged as an important hub for Delta‐AY.101. Our phylogeographical GLM analysis demonstrates that air travel fluxes and population size at the origin of locations were the strongest predictors of shaping SARS‐CoV‐2 dispersal dynamics within Paraná. In addition, viral load analysis suggests that Gamma‐P.1 and Delta‐AY.101 may have maintained a similarly high transmissibility potential throughout the evaluated months, providing insights into the prolonged co‐circulation dynamics. Our study underscores the relevance of understanding SARS‐CoV‐2 introductions and regional circulation contributions at the country level to enhance public health preparedness and strengthen local surveillance programs.