Reconstruction of a large-scale outbreak of SARS-CoV-2 infection in Iceland informs vaccination strategies
This repository contains the code for the creation and analysis of the model presented in the manuscript Reconstruction of a large-scale outbreak of SARS-CoV-2 infection in Iceland informs vaccination strategies. The model is created with the script run_model.R, which accepts the following command line arguments:
[--nr_iter N] (int) the number of MCMC iterations to be run.
[--chain N] (int) the chain number, if running more than one chain.
[--head N] (int) only the first N data points will be modeled.
[--mu_init X] (float) the initial value of mu, the mutation rate.
[--move_mu] indicates whether mu should be a parameter or fixed.
[--normalize] indicates whether truncated time distributions should be normalized.
[--imputation] indicates whether low-coverage and missing haplotypes should be imputed.
The resulting model will be stored in results/full_model. The vaccination strategy simulations can be run via run_vaccination_simulation.R, which accepts the following command line arguments:
--model_name (str) name of the outbreaker model.
--sim_nr (int) the number of the batch of simulations (for parallelising).
-N (int) the number of simulations to perform.
--first_dose_efficacy (float) efficacy of first dose to use in the simulation.
--second_dose_efficacy (float) efficacy of second dose to use in the simulation.
--out_dir (str) path to output directory.
[--init_size X] (int) size of initial outbreak.
[--step_size X] (float) percentage interval at which to simulate.
[--replay] indicates whether to replay de facto vaccinations or start from zero.
[--subtrees] indicates whether we should run the simulation on subtrees or the whole tree.
The dataset should be located in data/dat.tsv and contains the following fields:
Wave (int) denotes the wave of infections
t_id (str) unique identifier per person
sam_id (str) unique identifier per sample
seq (str) denotes whether sequenced via ONT or Illumina
mutations_full (str) semicolon-delimited list of all mutations, LOCUS-REF-ALT
mutations (str) semicolon-delimited list of all mutations, LOCUS
REF (str) semicolon-delimited list of all mutations, REF
ALT (str) semicolon-delimited list of all mutations, ALT
clade (str) denotes the clade
mutations_full_extra (str) semicolon-delimited list of mutations on top of the clade, LOCUS-REF-ALT
mutations_extra (str) semicolon-delimited list of mutations on top of the clade, LOCUS
REF_extra (str) semicolon-delimited list of mutations on top of the clade, REF
ALT_extra (str) semicolon-delimited list of mutations on top of the clade, ALT
ct (float) the ct-value of the sample
score (float) the ratio of called bases in the sequence
connected_to_revised (str) comma-delimited list of the t_ids of reported contacts
TYPE (str) the type of infection, one of ["border", "family", "healthcare", "none", "school", "social", "travel", "work"]
age_at_diag (int) age at diagnosis
birth_year (int) birth year
child (bool) denotes whether person is a child or not
date (str) diagnosis date, YYYY-MM-DD
date_isolation (str) date when person isolated, YYYY-MM-DD
date_exposure (str) date of reported exposure, YYYY-MM-DD
date_symptoms (str) date of onset of symptoms, YYYY-MM-DD
date_q (str) date at the start of quarantine, YYYY-MM-DD
date_registered (str) date when the person was first registered in the contact tracing system, YYYY-MM-DD
date_ref (str) min(date, date_symptoms)
shows_symptoms (bool) denotes whether person was symptomatic at diagnosis
q_type_binary (str) denotes whether person was in quarantine at diagnosis, one of ['outside_q', 'in_q']
q_type (str) denotes how long the person was in quarantine, one of ['outside_q', 'short_q', 'long_q']
household_id (int) which curated household the person belongs to
The files data/depth_miseq_dat.tsv and data/depth_ont_dat.tsv should contain the loci per sample with a sequencing depth of 30x or lower.
seq (str) one of ["MISEQ", "ONT"]
sam_id (str) the unique sample id
Pos (int) locus
depth (int) sequencing depth
The file data/vaccination_data.xlsx consists of a header containing the columns age, dose, and one column for each date of vaccinations. Rows 1-9 contain the number of people who received the first dose on the corresponding date in the age groups "0-15", "16-29", "30-39", "40-49", "50-59", "60-69", "70-79", "80-89", and "90+". Rows 11-18 contain the number of people in the same age groups who received the second dose on the corresponding date. Rows 19-27 contain the number of people in the same age groups who received a single-dose vaccine on the corresponding date.
The file data/age_groups.tsv contains a header age_group, second, first, none and denotes how many people in the age groups detailed above had received two doses, one dose, and zero doses of a vaccine as of April 28, 2021.