A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

Abstract

Background Québec was the Canadian province most impacted by COVID-19, with 401,462 cases as of September 24th, 2021, and 11,347 deaths due mostly to a very severe first pandemic wave. In April 2020, we assembled the Coronavirus Sequencing in Québec (CoVSeQ) consortium to sequence SARS-CoV-2 genomes in Québec to track viral introduction events and transmission within the province. Methods Using genomic epidemiology, we investigated the arrival of SARS-CoV-2 to Québec. We report 2921 high-quality SARS-CoV-2 genomes in the context of > 12,000 publicly available genomes sampled globally over the first pandemic wave (up to June 1st, 2020). By combining phylogenetic and phylodynamic analyses with epidemiological data, we quantify the number of introduction events into Québec, identify their origins, and characterize the spatiotemporal spread of the virus. Results Conservatively, we estimated approximately 600 independent introduction events, the majority of which happened from spring break until 2 weeks after the Canadian border closed for non-essential travel. Subsequent mass repatriations did not generate large transmission lineages (> 50 sequenced cases), likely due to mandatory quarantine measures in place at the time. Consistent with common spring break and “snowbird” destinations, most of the introductions were inferred to have originated from Europe via the Americas. Once introduced into Québec, viral lineage sizes were overdispersed, with a few lineages giving rise to most infections. Consistent with founder effects, the earliest lineages to arrive tended to spread most successfully. Fewer than 100 viral introductions arrived during spring break, of which 7–12 led to the largest transmission lineages of the first wave (accounting for 52–75% of all sequenced infections). These successful transmission lineages dispersed widely across the province. Transmission lineage size was greatly reduced after March 11th, when a quarantine order for returning travellers was enacted. While this suggests the effectiveness of early public health measures, the biggest transmission lineages had already been ignited prior to this order. Conclusions Combined, our results reinforce how, in the absence of tight travel restrictions or quarantine measures, fewer than 100 viral introductions in a week can ensure the establishment of extended transmission chains.

Patient health records and whole viral genomes from an early SARS-CoV-2 outbreak in a Quebec hospital reveal features associated with favorable outcomes

“…The phylogenetic diversity of SARS-CoV-2 genomes we report in this local outbreak is consistent with the genomic diversity observed across Quebec at the time, specifically subclades B and B.1 [ 33 ]. However, we found that different lineage assignment methods we employed (Pangolin, NextClade, phylogeny, dominant haplogroups and PHATE dimensionality reduction) produced disparate results.…”

Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis

“…For each candidate species, the animal-derived sequences, and their closest relative human-derived sequence were combined with ten random sub-samplings of human-derived sequences (n ≈ 50 per subtree per month of the pandemic), from which we inferred ten replicate phylogenies per species, providing an assessment of phylogenetic uncertainty. Using ancestral state reconstruction as previously described (Murall et al 2021), we counted the most basal animal-to-human ( Figure 1a-d ) and human-to-animal transitions on each tree ( Supplementary Table S2 ). To determine a lower bound for the transmission counts, we excluded transition branches with <75% bootstrap support (Methods).…”

Population Genomics Approaches for Genetic Characterization of SARS-CoV-2 Lineages

“…Overall, correlating Tajima's D values with epidemiological data at finer geographical scale might improve its explanatory power and inform public health agencies about the epidemiological trends. Essentially, Tajima's D can be used in combination with effective reproductive numbers (R) to estimate the spread of an expanding population in a given region ( 13 ). More recently a Genomic Identity (GENI) score (a genome diversity metric) was formulated from SARS-CoV-2 genomic data to estimate outbreak trends that lead to the emergence of new variants ( 50 ).…”

“…Currently, effective reproductive number (R) is a widely used metric to define outbreaks and to measure COVID19 disease spread ( 11 ). Tajima's D ( 12 ), a classical population genetics approach, can also be used to investigate SARS-CoV-2 lineage expansions ( 13 ). Dimensionality reduction techniques summarizing genetic diversity are also widely employed to investigate population structure in various species, and in particular, principal component analysis (PCA) has been proposed to investigate the population structure of SARS-CoV-2 virus early in the pandemic ( 14 ).…”