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R scripts used in M Cavallaro, L Dyson, MJ Tildesly, D Todkill & MJ Keeling (2023) Spatio-temporal surveillance and early detection of SARS-CoV-2 variants of concern. J. R. Soc. Interface. 20: 20230410. 20230410.

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mcavallaro/SARS-CoV-2-spatiotemporal-surveillance

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SARS-CoV-2-spatiotemporal-surveillance

This repository contains R scripts used for the analysis presented in the paper Massimo Cavallaro, Louise Dyson, Mike Tildesley, Dan Todkill, and Matt J. Keeling. (2023) Spatio-temporal surveillance and early detection of SARS-CoV-2 variants of concern: a retrospective analysis. J. R. Soc. Interface. 20: 20230410. 20230410. DOI:10.1098/rsif.2023.0410. MedRxiv:https://www.medrxiv.org/content/10.1101/2023.07.06.23292295.

SARS-CoV-2 data were supplied under strict data protection protocols and cannot be redisributed. Here we include synthetic data to run the scripts. Usage:

rm(list=ls())
devtools::install_github("mcavallaro/rancovr")

# Read data
library('readxl')
source('read_data.r)

# Create baseline matrices under the null model from data
source('create_matrices.r')
# source('downsample_matrices.r') # optional

# Generate and dump on file the warning scores with `rancovr`
source('rancover_exceed.r')

# Plot
library(viridisLite)
library(sf)
source("covid_exceed_map.r")

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R scripts used in M Cavallaro, L Dyson, MJ Tildesly, D Todkill & MJ Keeling (2023) Spatio-temporal surveillance and early detection of SARS-CoV-2 variants of concern. J. R. Soc. Interface. 20: 20230410. 20230410.

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