Corpus downloaded from PubMed 30th March: 1788 publications. There were 308 keywords that occurred in three or more manuscripts. These divided into four clusters.
Cluster 1 (red) relates to “Health and pandemic management”, and include topics like the pandemic, the impact on global health, the disease outbreak, infection control and travel. Within this cluster, we found the topic of “Global health politics”, which in addition to terms on the pandemic and the impact on global health included terms on countries, public health, disease transmission and health planning. Further, within this cluster, we found the topic of “Pandemic politics”, which in addition to the terms disease outbreak and infection control included terms like mass screening and health personnel.
Cluster 2 (green) related to “The disease and its pathophysiology” of COVID-19, including topics like its genome and its relationship with SARS, but also topics like epidemiology and its outbreak and that it is a zoonosis. Within this cluster, we found the topic of “Viral biology”, which in addition to terms on its genome and SARS, included terms like phylogeny and disease reservoirs. Further, within this cluster, we find the topic of “Viral spread”, which in addition to the term epidemiology, includes terms like quarantine, importation and incubation period. Lastly, this cluster contained the topic “Basic clinical medicine”, which in addition to the terms outbreak and zoonosis, included terms like transmission and mortality.
Cluster 3 (blue) related to the “Clinical epidemiology of the disease”, including topics like age (aged, children, adolescent) and gender (male and female), risk factor, population surveillance and pregnancy. Only one major topic was identified within this cluster: “Clinical characteristics”. In addition to the terms on age and gender, this topic included terms like prognosis, myalgia, biomarkers and laboratory medicine.
Cluster 4 (yellow) related to “Treatment of the disease”, with terms like antiviral agents, diagnosis, ritonavir and drug combinations.
Table of ten most central keywords in each cluster
(Centrality measure used is weighted degree centrality)
Cluster 1 (Red)
Cluster 2 (Green)
Cluster 3 (lBlue)
Cluster 4 (Yellow)
|public health||genome, viral||middle aged||respiration, artificial|
|global health||outbreak||young adult||diagnosis, differential|
|infection control||zoonosis||children||influenza, human|
|population surveillance||wuhan||tomography, x-ray computed||novel coronavirus pneumonia|
|risk assessment||communicable diseases, emerging||adolescent||diagnosis|
To open the map directly in VOSviewer, please use these two files.
The maps are created with the following “thesaurus” to clean the data: Thesaurus 23 March