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Delta-analysis

This repo contains the scripts and data used to generate the results in [CITATION]. Note that several data files cannot be shared due to data sharing agreements and some scripts may need to be adjusted depending on the local setup.

GISAID terms of use prohibit our sharing of the sequence data used from GISAID. Instead we provide a the accession IDs used and an acknowledgement table.

Abstract

The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter- regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta’s invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.

Repository structure:

├── analysis
│   ├── UK_continuous_phylogeography
│   │   ├── XMLs
│   │   └── scripts
│   └── global_DTA_analysis
│       ├── outputs
│       │   ├── empirical_trees
│       │   ├── input_trees
│       │   └── transmission_lineages
│       ├── pipeline
│       │   ├── full_run
│       │   └── templates
│       ├── scripts
│       └── xml
└── data
    ├── UK_geog_data
    │   └── UTLA_shapes_final
    └── global_DTA_analysis
        └── trees

Input data

All input data that we are able to share publically is in the data directory.

Analysis

The analysis directory contains subdirectories of the following analyses.

global_DTA_analysis:

Contains scripts and XMLs for generating the global discrete phylogeographic analysis to obtain estimates of importations into the UK

global_epidemiology_analysis:

Scripts and model files for estimating risk factors for delta growth can be found in this separate repository.

UK_continuous_phylogeography:

Contains scripts and XMLs to generate input files, process data and visualise results for the within-uk lineage dynamic analysis

Data availability

UTLA shapefiles from data.gov.uk, England postcode districts from (Addy 2017, https://datashare.ed.ac.uk/handle/10283/2597). UK_map.json originally contains data from gadm.org, but has been edited and customised since.

The O2 aggregated, anonymised mobile data insights dataset is not publicly available owing to stringent licensing agreements. Information on the process of requesting access to the O2 aggregated mobile data insights dataset is available [email protected]. The Google COVID-19 Aggregated Mobility Research Dataset is not publicly available owing to stringent licensing agreements. Information on the process of requesting access to the Google mobility data is available from [email protected].

UK genome sequences used were generated by the COG-UK consortium (https://www.cogconsortium.uk/). Data linking COG-IDs to location have been removed to protect privacy, however if you require this data please visit https://www.cogconsortium.uk/contact/ for information on accessing consortium-only data.

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Contributors

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