We consider the network of 5416537 articles of English Wikipedia of 2017. Using the recent reduced Google matrix (REGOMAX) method we construct the reduced network of 230 articles (nodes) of infectious diseases and 195 articles of world countries. This method generates the reduced directed network between all 425 nodes taking into account all direct and indirect links with pathways via the huge global network. PageRank and CheiRank algorithms are used to determine the most influential diseases
with the top PageRank diseases being Tuberculosis, HIV/AIDS and Malaria. From the reduced Google matrix we determine the sensitivity of world countries to specific diseases integrating their influence over all their history including the times of ancient Egyptian mummies. The obtained results are compared with the World Health Organization (WHO) data demonstrating that the Wikipedia network analysis provides reliable results with up to about 80 percent overlap between WHO and REGOMAX analyses.
Data acquisition : from 1 May 2017 to 31 May 2017
Data provision : 21 Jun 2018
Metadata record :
Creation : 10 Jan 2019
Update : 18 Mar 2019
General, Research, Stakeholder, Policy maker
Formats : application/pdf, image/png, image/x-eps, text/csv, text/html
Data acquisition methods :
- Derived or compiled data :
Web crawling of Wikipedia editions (May 2017) to retrieve information.
- Simulation or computational data :
PageRank, CheiRank and 2DRank algorithms have been used to rank articles of the English Wikipedia language edition (May 2017).
Reduced Google matrix method has been used to infer interaction between articles.