Anti-clustering in the national SARS-CoV-2 daily infection counts (original) (raw)
Published August 26, 2021 | Version 086b149
Journal article Open
- 1. Nicolaus Copernicus University
Description
Produced and source files for "Anti-clustering in the national SARS-CoV-2 daily infection counts", 2021, PeerJ, 9:e11856, by B. F. Roukema
- subpoisson-086b149.pdf - article in pdf format
- WP_C19CCTF_SARSCoV2.dat - Wikipedia COVID-19 Case Count Task Force (C19CCTF) medical cases chart data on national daily SARS-CoV-2 infections in csv format; URLs of the specific versions of the source pages are included
- WHO_vs_WP_jumps.dat - plain text table comparing jumpiness of WHO to C19CCTF national case count data
- phi_N_full.dat - results: clustering parameter phi_i for full national daily infection counts above a threshold of 50 per day
- phi_N_28days.dat - as for phi_N_full.dat, for the least noisy 28-day subsequence for each country
- phi_N_14days.dat - as for phi_N_28days.dat, for 14-day subsequences
- phi_N_07days.dat - as for phi_N_28days.dat, for 7-day subsequences
- AIC_BIC_full.dat - Akaike and Bayesian information criteria for primary and alternative analyses
- pfi_correlations_table.dat - Kendall tau statistic and its significance for non-parametric ranked correlation between clustering parameters and the Reporters sans frontières Press Freedom Index
- six files *_jhu.dat which are equivalent to the main tables, but for the JHU CSSE data, as listed in the appendix of the article
- subpoisson-086b149-git.bundle - git source package that can be unbundled with 'git clone subpoisson-086b149-git.bundle' and used for reproducibility: to download data, do calculations, analyse them, plot them and produce the article pdf
- subpoisson-086b149-journal.tar.gz - source package for producing the article pdf, together with the reproducibility package, but without the git history; appropriate for ArXiv
- software-086b149.tar.gz - this should contain all the software sources, apart from a minimal POSIX-compatible system, needed for compiling and installing the software used in producing this paper (big file)
Associated resources:
- ArXiv preprints: arXiv:2007.11779
- Software Heritage (swh): swh:1:rev:086b14906401f8484258cead5bc7152439a686ee
- Pop-science description: What is noisiness in SARS-CoV-2 daily infection counts?
All the materials here are free-licensed, as stated in the individual files and packages.
Clarification of IDs in data files: The files in Zenodo record 5262698 correctly state in their headers that they were calculated using git commit eb46500. However, they incorrectly state the older Zenodo ID 4765705 instead of 5262698.
Files
subpoisson-086b149.pdf
Files (546.7 MB)