Data · dataset · 2020
COVID-19 reproduction number data calculated from the datasets of COVID-19 infection in a few countries
Listed in Teesside University Research Data Repository
Raw data have been collected for the USA, Denmark, China, Italy , Germany, France, Singapore (from 22 January, 2020 to 26 April, 2020) and India (upto 2 May, 2020) and produced in log-log scale for power law fitting.
Description
The fitted data for different power law exponents are also submitted here. The new number of observed cases per day in these countries has been extracted from the raw data for application of Farr's law.
The fitted Gaussian curve is also submitted here. The temporal dynamics of the reproduction number R0 is calculated from these data using Farr's law and IDEA model and compared for three different countries-the USA, Italy and India. The details can be seen in medrxiv.org/content/10.1101/2020.05.04.20090233v1.
Read the rest (1 more)
The detailed paper will be submitted in peer reviewed journal Epidemics . The raw data have been collected from github.com/CSSEGISandData/COVID-19, coronavirus.jhu.edu/map.html and mohfw.gov.in/.
Links
Where it is published
- DOI doi.org/10.17632/64ywngvfz2.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Mathematics & Statistics · Medicine & Health · Social Science
- Inferred from text
- Epidemiology 70%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/64ywngvfz2.1 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4202 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:mathematics-statistics | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |