Arquivo para October 1st, 2020

Work on pandemic network analysis

01 Oct

Chinese scientists have proposed a method of visually showing, in a simple way, the risk of a pandemic in regions with different degrees of connection, from the databases of infection cases (reported and confirmed by COVID-19) using network analysis, in article published by Elsevier in Journal of Disaster of Infections.

Network analysis has already been used in medical research for studies on gene coexpression, disease co-occurrence and topologies of the dynamics of the spread of infectious diseases.

The study looked at confirmed cases of COVID-19 in China from late January to March 2020 and these cases were divided into 9 time periods.

The graphs of networks constructed based on the correlation of changes in the number of confirmed cases between two geographic areas (for example, in the provinces of China), if the correlation was greater than 0.5 meant that the connected areas were in a network.

The pandemic risk was analyzed based on the frequencies in different regions connected in the network graphs, with this it was possible to assess the levels of co-evolution between the regions and, with this, to take measures according to each case.

What the study demonstrated was not just relying on reported and confirmed cases of COVID-19, network analysis provides data for a powerful and clear view of pandemic risk and network analysis can complement traditional modeling techniques, and seconds the authors of this data can provide more timely evidence to inform future preparation plans.

Future work quantifying the network connection should be considered in research and pandemic plans.

Soa, M.P.K; Tiwarib, Agnes; Chud, Amanda M.Y.; Tsangd , Jenny T.Y.; Chan, Jacky N. L.. Visualizing COVID-19 pandemic risk through network connectedness Mike. International Journal of Infectious Diseases, 96, 2020, p. 558-561.   Available in: , Access: sept. 2020.