Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

Abstract

The UK’s COVID-19 epidemic during early 2020 was one of world’s largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country’s first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, while lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

Estimating dates of origin and end of COVID-19 epidemics

“…The problem is that there is an identifiability issue because it is impossible to estimate both the number of initial infected cases and the time to threshold of 100 deaths with incidence data only. However, some estimates made in the UK from phylogenetic data as well as the combination of prevalence and travel data show that the estimated number of importation events is less than 5 per day before the end of February, when the virus was beginning to circulate at higher levels throughout Europe [19]. Assuming that the dynamic was similar in France, we could verify that the dynamic was only sensitive to the importation events within the first days after the beginning of the epidemic wave.…”

Increased hazard of mortality in cases compatible with SARS-CoV-2 variant of concern 202012/1 - a matched cohort study

“…Sequencing of VOC-202012/1 revealed 14 genetic mutations, 8 of which occurred in parts of the genome that code for the spike protein, responsible for cell binding [10], and which influence S-gene detection. These mutations appear to have imparted a phenotypic change to the cell binding mechanism [11,7–9,2], with the potential for increased infectivity [12,13]. The impact of the change on clinical presentation, patient outcome and, most importantly mortality, remains poorly understood.…”

The early dynamics of the SARS-CoV-2 epidemic in Portugal

“…In order to control the virus arrival and spread, many countries adopted rigid public health measures, including complete border closures and general lockdowns, with tremendous consequences at economic and social levels. At the early stages of an epidemic, the success of public health measures is particularly dependent on their timely implementation, which requires comprehensive diagnosis/surveillance systems that are able to efficiently trace where the virus is being introduced and circulating ( Alm et al, 2020; Nadeau et al, 2020; Gámbaro et al, 2020; du Plessis et al, 2021 ). Taking advantage of the recent extraordinary advances in sequencing technologies, modern surveillance systems are progressively relying on genomic epidemiology as a crucial tool for outbreak investigation and for tracking virus evolution and spread ( Fauver et al, 2020; Lemieux et al, 2020; du Plessis et al, 2021 ).…”

“…At the early stages of an epidemic, the success of public health measures is particularly dependent on their timely implementation, which requires comprehensive diagnosis/surveillance systems that are able to efficiently trace where the virus is being introduced and circulating ( Alm et al, 2020; Nadeau et al, 2020; Gámbaro et al, 2020; du Plessis et al, 2021 ). Taking advantage of the recent extraordinary advances in sequencing technologies, modern surveillance systems are progressively relying on genomic epidemiology as a crucial tool for outbreak investigation and for tracking virus evolution and spread ( Fauver et al, 2020; Lemieux et al, 2020; du Plessis et al, 2021 ). Genomic surveillance of SARS-CoV-2 can be particularly useful for: i) understanding the contribution of “new introductions” versus “local transmission” to the number of new cases at continent/country/regional levels; ii) evaluating the impact of non-pharmaceutical interventions on the outcomes of transmission chains; iii) characterizing the genetic variability that may negatively affect molecular diagnostic tests; iv) identifying and monitoring genetic variability affecting antigens and targets of antiviral drugs with potential impact on the development/effectiveness of prophylactic (vaccines) and therapeutic measures; v) investigating potential associations between genetic variants and infectious load, patient immunological status, clinical outcomes (e.g., infection duration, disease severity, etc) ( Alm et al, 2020 ).…”