Published: 23 October 2020| Version 1 | DOI: 10.17632/wt7nd5jv6s.1
Luis Braga


Data In this study the data sources are WHO, CDC, ECDC, NHC, DXY, 1point3acres,, BNO, the COVID Tracking Project (testing and hospitalizations), State and National Government Health Departments, and local media reports. A layer in the package ArcGis(Arc Gis 2020) was created and maintained by the Center for Systems Science and Engineering (CSSE) at the John Hopkins University (CSSE 2020). This feature layer is supported by ESRI Living Atlas team, JHU APL and JHU Data Services. This layer is opened to the public and free to share. The cases data set was downloaded from that repository on the 6th of September, 2020, and includes the following attributes: Country Name, Deaths(D), Recovered(R) and Active(A) patients. Note that the second and the third are cumulative figures until that day and the last one is the value available on that day. For each frequency (Deaths, Recovered, Active) proportions of the population were calculated in the acomp scale, entries with null values were converted to Below Detection Limits (BDL). The original attributes will now be named in the acomp scale: PD: cumulative relative frequency of deaths PR: cumulative relative frequency of recovered PA: relative frequency of active* Pc: frequency (cumulative and 6th of September) of confirmed cases** *People still being treated **People that caught the Covid-19 Table I Absolute frequencies per country on the 6th September 2020 source: John Hopkins University(JHU) – Center for Systems Science and Engineering (CSSE) link: G – Gray: Active dominant and Recovery subdominant Y – Yellow: Recovery Dominant and Active subdominant B – Black: Recovery Dominant and Deaths subdominant or Active Dominant and Deaths subdominant (just two samples fall into this cathegory) Table II Closure with c=1, acomp scale PD: deaths PR: recovered PA: active



Universidade Federal do Rio de Janeiro


Clustering, Data Analysis, COVID-19