Decoupling between SARS-CoV-2 transmissibility and population mobility associated with increasing immunity from vaccination and infection in South America

Comparative spatial-temporal analysis of SARS-CoV-2 lineages B.1.1.33 and BQ.1.1 Omicron variant across pandemic phases

The evolution of COVID-19 pandemic has been characterized by the rapid emergence of new SARS-CoV-2 variants, each of which poses unique challenges to public health. This study analyzes the dispersion profiles during the Pre-Omicron and Post-Omicron phases in different epidemiological contexts. The Brazilian state of Espirito Santo, despite its low population density, plays a critical role as a commercial hub due to its intense port activity, which may have contributed to COVID-19 cases and mortality rates being higher than the national average. The state recorded 34,000 confirmed cases and 377 deaths per 100,000 inhabitants. Genomic surveillance revealed that the Pre-Omicron phase was dominated by the B.1.1.33 lineage, characterized by localized intraregional circulation. In contrast, the Post-Omicron phase, dominated by the BQ.1.1 lineage, exhibited greater diversity in circulating lineages, increased international interactions, and rapid viral dissemination, highlighting distinct transmission dynamics between such periods. This study highlights the need for adaptive public health strategies that account for both viral behavior and regional socioeconomic factors, while highlighting the strategic importance of Espirito Santo in monitoring SARS-CoV-2 evolution.

Dispersion patterns of SARS-CoV-2 variants Gamma, Lambda and Mu in Latin America and the Caribbean

Latin America and Caribbean (LAC) regions were an important epicenter of the COVID-19 pandemic and SARS-CoV-2 evolution. Through the COVID-19 Genomic Surveillance Regional Network (COVIGEN), LAC countries produced an important number of genomic sequencing data that made possible an enhanced SARS-CoV-2 genomic surveillance capacity in the Americas, paving the way for characterization of emerging variants and helping to guide the public health response. In this study we analyzed approximately 300,000 SARS-CoV-2 sequences generated between February 2020 and March 2022 by multiple genomic surveillance efforts in LAC and reconstructed the diffusion patterns of the main variants of concern (VOCs) and of interest (VOIs) possibly originated in the Region. Our phylogenetic analysis revealed that the spread of variants Gamma, Lambda and Mu reflects human mobility patterns due to variations of international air passenger transportation and gradual lifting of social distance measures previously implemented in countries. Our results highlight the potential of genetic data to reconstruct viral spread and unveil preferential routes of viral migrations that are shaped by human mobility patterns.

The Pandemic in Words: Tracking Fast Semantic Changes via a Large-Scale Word Association Task

Most words have a variety of senses that can be added, removed, or altered over time. Understanding how they change across different contexts and time periods is crucial for revealing the role of language in social and cultural evolution. In this study we aimed to explore the collective changes in the mental lexicon as a consequence of the COVID-19 pandemic. We performed a large-scale word association experiment in Rioplatense Spanish. The data were obtained in December 2020, and compared with responses previously obtained from the Small World of Words database (SWOW-RP, Cabana et al., 2023). Three different word-association measures detected changes in a word's mental representation from Precovid to Covid. First, significantly more new associations appeared for a set of pandemic-related words. These new associations can be interpreted as incorporating new senses. For example, the word 'isolated' incorporated direct associations with 'coronavirus' and 'quarantine'. Second, when analyzing the distribution of responses, we observed a greater Kullback-Leibler divergence (i.e., relative entropy) between the Precovid and Covid periods for pandemic words. Thus, some words (e.g., 'protocol', or 'virtual') changed their overall association patterns due to the COVID-19 pandemic. Finally, using semantic similarity analysis, we evaluated the changes between the Precovid and Covid periods for each cue word's nearest neighbors and the changes in their similarity to certain word senses. We found a larger diachronic difference for pandemic cues where polysemic words like 'immunity' or 'trial' increased their similarity to sanitary/health words during the Covid period. We propose that this novel methodology can be expanded to other scenarios of fast diachronic semantic changes.

Comparative epidemic expansion of SARS-CoV-2 variants Delta and Omicron in the Brazilian State of Amazonas

The SARS-CoV-2 variants of concern (VOCs) Delta and Omicron spread globally during mid and late 2021, respectively. In this study, we compare the dissemination dynamics of these VOCs in the Amazonas state, one of Brazil's most heavily affected regions. We sequenced the virus genome from 4128 patients collected in Amazonas between July 1st, 2021, and January 31st, 2022, and investigated the viral dynamics using a phylodynamic approach. The VOCs Delta and Omicron BA.1 displayed similar patterns of phylogeographic spread but different epidemic dynamics. The replacement of Gamma by Delta was gradual and occurred without an upsurge of COVID-19 cases, while the rise of Omicron BA.1 was extremely fast and fueled a sharp increase in cases. Thus, the dissemination dynamics and population-level impact of new SARS-CoV-2 variants introduced in the Amazonian population after mid-2021, a setting with high levels of acquired immunity, greatly vary according to their viral phenotype.

Measuring the mobility impact on the COVID-19 pandemic

This assessment aims at measuring the impact of different location mobility on the COVID-19 pandemic. Data over time and over the 27 Brazilian federations in 5 regions provided by Google's COVID-19 community mobility reports and classified by place categories (retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences) are autoregressed on the COVID-19 incidence in Brazil using generalized linear regressions to measure the aggregate dynamic impact of mobility on each socioeconomic category. The work provides a novel multicriteria approach for selecting the most appropriate estimation model in the context of this application. Estimations for the time gap between contagion and data disclosure for public authorities' decision-making, estimations regarding the propagation rate, and the marginal mobility contribution for each place category are also provided. We report the pandemic evolution on the dimensions of cases and a geostatistical analysis evaluating the most critical cities in Brazil based on optimized hotspots with a brief discussion on the effects of population density and the carnival.