Journal article Open Access
Anti-clustering in the national SARS-CoV-2 daily infection counts
Roukema, Boudewijn F.
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<dcat:keyword>Epidemic curve</dcat:keyword>
<dcat:keyword>Poisson point process</dcat:keyword>
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<dct:description><p>Produced and source files for &quot;Anti-clustering in the national SARS-CoV-2 daily infection counts&quot;, 2020, by B. F. Roukema</p> <ul> <li>subpoisson-252cf1c.pdf - article in pdf format</li> <li>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</li> <li>WHO_vs_WP_jumps.dat - plain text table comparing jumpiness of WHO to C19CCTF national case count data</li> <li>phi_N_full.dat - results: clustering parameter phi_i for full national daily infection counts above a threshold of 50 per day</li> <li>phi_N_28days.dat - as for phi_N_full.dat, for the least noisy 28-day subsequence for each country</li> <li>phi_N_14days.dat - as for phi_N_28days.dat, for 14-day subsequences</li> <li>phi_N_07days.dat - as for phi_N_28days.dat, for 7-day subsequences</li> <li>subpoisson-252cf1c-git.bundle - git source package that can be unbundled with &#39;git clone subpoisson-252cf1c-git.bundle&#39; and used for reproducibility: to download data, do calculations, analyse them, plot them and produce the article pdf</li> <li>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</li> <li>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</li> </ul> <p>Associated resources:</p> <ul> <li>ArXiv preprints: <a href="https://arXiv.org/abs/2007.11779">arXiv:2007.11779</a></li> <li>Software Heritage (swh): <a href="https://archive.softwareheritage.org/swh:1:dir:fcc9d6b111e319e51af88502fe6b233dc78d5166">swh:1:dir:fcc9d6b111e319e51af88502fe6b233dc78d5166</a></li> <li>Pop-science description: <a href="https://codeberg.org/boud/subpoisson/src/branch/subpoisson/README-popular-science.md">What is noisiness in SARS-CoV-2 daily infection counts?</a></li> </ul> <p>All the materials here are free-licensed, as stated in the individual files and packages.</p></dct:description>
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Indexed in
- Publication date:
- July 23, 2020
- DOI:
-
- Keyword(s):
- COVID-19 Epidemic curve Poisson point process
- Related identifiers:
- Supplement to
- arXiv:2007.11779 (Preprint)
- Supplementary material
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International