covid-npi

Analysis code for:

A viral perspective on worldwide non-pharmaceutical interventions against COVID-19

Jean-Philippe Rasigade, Anaïs Barray, Julie Teresa Shapiro, Charlène Coquisart, Yoann Vigouroux, Antonin Bal, Grégory Destras, Philippe Vanhems, Bruno Lina, Laurence Josset, Thierry Wirth.

medRXiv preprint manuscript

Requirements

R software (tested on Windows 10 with v3.6.1).

Packages

• ape
• data.table
• lubridate
• survival
• coxme
• stringr
• beeswarm
• plotrix
• wordcloud

A workstation with at least 24 CPU cores is recommended to run scripts involving mixed-effect models. Use the special flag rebuild = FALSE to bypass these computations.

Usage

Scripts should be run individually in the following order:

Pre-treatment scripts

These scripts perform alignment operations, especially between country identifiers; and extraction of branch length data.

• S1_dataprep_countries.R
• S2_dataprep_tree.R
• S3_dataprep_branch_lengths.R
• S4_dataprep_npis.R

Analysis scripts

These scripts generate the results and figures of the study.

• A1_descriptive_stats_by_country.R
• A2_branch_length_distribution.R
• A3_divergence_rates_per_country.R
• A4_npi_timing.R
• A5_npi_univariate.R
• A6_npi_multivariate.R
• A7_SIR_models.R

Flowchart of selection steps

• Z1_flowchart.R