Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence

Abstract

Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.

Fig. 1.. Human mobility and spatial expansion of B.1.1.7 across the UK.

(A) Map at the UTLA level of arrival dates of lineage B.1.1.7. Darker colors indicate earlier dates, and lighter colors indicate later dates. Arrival time is defined as the earliest sampling date of a B.1.1.7 genomic sequence in each UTLA. (B) Cumulative number of UTLAs in which B.1.1.7 has been detected, in 7-day intervals. The blue shaded area indicates the period of the second lockdown in England. (C) Relationship between the arrival time of B.1.1.7 and estimated number of movements from Kent and London during February 2020 for each UTLA (Pearson’s r = –0.73; 95% CI: –0.61, –0.81; P < 0.001) (materials and methods). (D) Human mobility at the UK local authority district level (LAD) (table S2) during the epidemiological week 29 November to 5 December 2020. Thicker lines (edges) indicate more movements between regions. Nodes with larger absolute incoming movements are indicated with darker colors. Red lines indicate movements from Greater London. (Insets I, II, and III) Mobility within three UK metropolitan areas. (E) Trends in human mobility across the UK (indicating movements between but not within LADs). The blue shaded areas indicate the period of the first, second, and third lockdown in England. Dark red indicates the timing (20 December 2020) of the Tier 4 restrictions imposed in southeast England, including London (56).

Fig. 2.. Spatial emergence dynamics of SARS-CoV-2 lineage B.1.1.7 in England.

(A and B) Continuous phylogeographic reconstruction with phylogeny nodes colored according to their time of occurrence and dispersal direction of phylogeny branches indicated by edge curvature (counterclockwise). From left to right, data to 5 November, 1 December, and 20 December 2020, respectively. (B) Map of the entire reconstruction, up to 19 January 2021. (C) Estimated number of weekly exports of lineage B.1.1.7 from the Greater London area, inferred from the continuous phylogeographic analysis (red), and estimated from mobility and prevalence survey data (black). (D) Estimated number of cumulative B.1.1.7 introductions inferred from phylogeographic analysis into each administrative area (UTLA) by 12 December 2020.

Fig. 3.. Spatial structure of B.1.1.7 lineage dispersal in England from phylogeographic reconstruction.

(A) Curved arrows and line thicknesses indicate the direction and intensity of B.1.1.7 lineage flows among regions. Red circles indicate, for a given location, the ratio of inferred local movements to inferred importations into that location. Four time periods are shown (left to right) and roughly correspond to (i) before second lockdown, (ii) second lockdown, (iii) after second lockdown, and (iv) implementation of Tier 4 restrictions in southeast England. (B) Distribution of the geographic distances of phylogenetic lineage movement events (>50 km). Those from Greater London are in red, and those from other locations are in gray.

Fig. 4.. Case growth rates of B.1.1.7 are correlated with human mobility and attack rates across the UK.

(A) Seven-day rolling average number of cases reported that had the SGTF (green) and cases reported with non-SGTF (red) for three selected LTLAs, Birmingham, Liverpool, and Manchester (table S2). The black line indicates the weekly number of independent introductions estimated from the phylogeographic analysis. The gray shaded area indicates the timing of the second (5 November to 1 December) and start of the third (5 January) English lockdown. (B) Rolling 7-day average growth rates of SGTF cases in Greater London (red line) and outside of Greater London (blue line). (C) Association between per-region (LTLA) difference between SGTF and non-SGTF case growth rates (corrected to account for differences through time in sampling intensity of SGTF cases) and number of B.1.1.7 importations into that region, as estimated from prevalence surveys and human mobility (gray dots) (Fig. 2C and materials and methods). The gray area shows the time of the second English lockdown. Modeling results for SGTF growth rates are shown in fig. S9, and regression results under different assumptions about the frequency of SGTF are shown in fig. S10.

Fig. 5.

(A) Frequency of B.1.1.7 at the UTLA level at different sampling times. Pre-lockdown, dates before 5 November; lockdown, 5 to 30 November; post-lockdown, 1 to 15 December; Tier 4, 16 to 31 December; and the most recent sampling point, 1 to 12 January(materials and methods). (B) Increase in the frequency of B.1.1.7 sampled genomes between 2 and 16 December 2020 is associated with mobility from Greater London. (C) Increase in the frequency of B.1.1.7 sampled genomes at the UTLA level is associated with previous attack rates in each location. Results for equivalent analyses of SGTF data are similar and are provided in the supplementary materials.