Anti-clustering in the national SARS-CoV-2 daily infection counts

Produced and source files for "Anti-clustering in the national SARS-CoV-2 daily infection counts", 2020, by B. F. Roukema

• subpoisson-252cf1c.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
• subpoisson-252cf1c-git.bundle - git source package that can be unbundled with 'git clone subpoisson-252cf1c-git.bundle' and used for reproducibility: to download data, do calculations, analyse them, plot them and produce the article pdf
• subpoisson-252cf1c-arXiv.tar.gz - source package for producing the article pdf, together with the reproducibility package, but without the git history; appropriate for ArXiv
• software-252cf1c.tar.gz - this should contain all the software, apart from a minimal POSIX-compatible system, needed for compiling and installing the software used in producing this paper

Associated resources:

• ArXiv preprints: arXiv:2007.11779
• Software Heritage (swh): swh:1:dir:fcc9d6b111e319e51af88502fe6b233dc78d5166
• 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.