Synchronized seasonal excretion of multiple coronaviruses coincides with high rates of coinfection in immature bats: Code.

Synchronized seasonal excretion of multiple coronaviruses coincides with high rates of coinfection in immature bats.

This repo contains instructions and source code for reproducing the statistical analyses in the manuscript.

Repo Contents

• scripts: contains the source .R and .stan files to reproduce the anaysis. Each file is detailed below in the specific sections corresponding to the statistical analyses.
• data: contains the raw source data and model generated output.
• figures: contains the final output figures from the manuscript. These can be recreated with the CovOZ_Figures_Submission_Clean.R script.

1. System Requirements

Hardware Requirements

Our source code requires only a standard computer. Much of the Markov chain Monte Carlo code is run in parallel so a computer with ample memory and multiple cores can be advantageous. The runtimes below are generated using a macbook with the recommended specs (64 GB RAM, 8 cores at 2.7 GHz). The code will also work on linux or windows computer.

Software Requirements

Reproducing the statistical analyses requires a current version of R and stan. We use version 4.4.1 of R and version 2.32.2 of stan.

Package dependencies and versions

Users will need the following packages install the following packages to execute the code. Our versions are effective October 1, 2024

tidyverse 2.0.0
lubridate 1.9.3
stringr 1.5.1
rstan 2.32.6
cowplot 1.1.3
ggtext 0.1.2
jpeg 0.1-10
scales 1.3.0
tictoc 1.2.1

2. Installation Guide

Running the analysis requires:

• installing R. Depending on wifi speeds, installing R usually takes a few minutes.
• installing stan. Depending on wifi speeds, installing stan usually takes a few minutes.
• installing the necessary R packages (listed above). Depending on wifi speeds, installing packages usually takes about 30 seconds per package.

3. Demo

This source code is not an R package with a formal demo, but rather source code is included for the various analyses in section 4.

4. Instructions for Use

4.1 Coinfection Analysis

Runs chi-squared tests on coinfections of beta 2d.iv and beta 2d.v. Generates summary statistics, test statistics, and p-values from manuscript.

• input files: individual_variant_covariates.csv
• script file: coinfection_final.R
• run time: approximately 1 second

4.2 Individual Level Dynamics of Infection: Dynamic Binary Regression

Runs individual level dynamic binary regression models. Produces output file that can recreate figures.

• input files: individual_variant_covariates.csv
• script files:
  • logistic_curves_final.R
  • GP_regression.stan
• output files: logistic_curve_out.RData
• run time: approximately 66 minutes

4.3 Dynamics of Circulation at the Population Level

Runs combined (individual and pooled data) dynamic models. Produces output file that can recreate figures.

• input files: combined_out_variant.csv
• script files:
  • cluster_curves_final.R
  • GP_withLL.stan
• output files: cluster_curves.csv
• run time: approximately 25 minutes

4.4 Manuscript Figures

Combined script that uses output files created by previous scripts to recreate all figures in the manuscript.

• input files:

  • model_output/cluster_curves.csv
  • combined_out_variant.csv
  • individual_variant_covariates.csv
  • model_output/logistic_curve_out.RData

• script files:

  • CovOZ_Figures_Submission_Clean.R

• run time: approximately 16 seconds

4.5 Model Comparison Integrated

Compares LOOIC values for sets of model frameworks.

• input files: combined_out_variant.csv
• script files:
  • Pred_Comparisons.R
  • GP_withLL.stan
• output files: preds.RData
• run time: approximately 2 hours

4.6 Model Comparison Individual

Compares LOOIC values for sets of model frameworks.

• input files: combined_out_variant.csv
• script files:
  • logistic_curves_loo.R
  • GP_regression.stan
  • GP_regression_add.stan
  • GP_regression_interact.stan
• output files:
  • logistic_curve_loo_age.RData
  • logistic_curve_loo_age_add_sex.RData
  • logistic_curve_loo_age_interact_sex.RData
• run time: approximately 6:45 hours