Corpus downloaded from PubMed 27th April: 6958 publications. There were 1082 keywords that occurred in three or more manuscripts. These divided into four main clusters.
This week’s rapport confirms what we suspected last week, that the clusters and topics seem to vary less. Clusters 1, 3 and 4 were quite stable, while cluster 2 saw a bit of change, mostly in the addition of a new topic (“inpatient care”). New from this week is that we in cluster 4 mention 3 upcoming topics with increasing number of publications. Finally, the last cluster (cluster 5) seemed to take a bit different course, mostly because most of the terms here moved to be included in cluster 1 in a new topic. Cluster 5 now is more about the disease.
Cluster 1 could be called «global virus pandemic» and includes terms like (beta)coronavirus infection, viral pneumonia, disease outbreak and public health. This cluster contains 3 major topics: a) “preventive epidemiology”, which in addition to the terms like disease outbreak and public health includes terms like travel, epidemic, global heath and civil defence, b) “care management” which includes terms like infection control, practice guidelines and health personnel and c) “vulnerability” that contains terms like mental health, psychological stress and health service accessibility.
Cluster 2 could be called “disease epidemiology” and includes terms like pneumonia, epidemiology, outbreak, infection, infectious diseases, novel coronavirus pneumonia, treatment and transmission. This cluster contains 2 major topics: a) the main term “the disease” which in addition to the above mentioned terms, but also b) “inpatient care” which contains terms like ARDS, critical illness and airway management. In this cluster some smaller topics are also present.
Cluster 3 could be called “pathophysiology and origin” and includes terms like SARS, animals, zoonosis, antiviral agents, viral genome, phylogeny and chiroptera. This cluster contains to major topics: a) “viral biology” which in addition to terms like SARS, animals, viral genome and phylogeny includes terms like spike glycoprotein and peptidyl-dipeptidase a and b) “drug treatment” which in addition to the term antiviral agent and chiroptera contains terms like traditional Chinese medicine, chloroquine and lopinavir.
Cluster 4 could be named “clinical epidemiology” and contains terms like mortality, age, gender, clinical laboratory techniques and fever. Also in this cluster, there is only this major topic. Smaller topics include “population care”, “serology” and “pregnancy”.
Cluster 5 could be named “clinical issues” and contains terms like cardiovascular diseases, hypertension, angiotensin-converting enzyme inhibitors and diabetes mellitus. This is the smallest cluster with only one topic.
Table of the most central keywords in each cluster
(Centrality measure used is weighted degree centrality)
|Cluster 1||Cluster 2||Cluster 3||Cluster 4||Cluster 5|
|coronavirus infection||pneumonia||sars||male||cardiovascular diseases|
|betacoronavirus||outbreak||antiviral agents||adult||angiotensin-converting enzyme inhibitors|
|pandemic||viruses||zoonosis||middle aged||diabetes mellitus|
|china||infection||peptidyl-dipeptidase a||clinical laboratory techniques||angiotensin receptor antagonists|
|disease outbreaks||infectious diseases||spike glycoprotein, coronavirus||aged||renin-angiotensin system|
|public health||respiratory infections||genome, viral||young adult||diabetes complications|
|travel||critical illness||phylogeny||tomography, x-ray computed||heart failure|
|epidemic||novel coronavirus pneumonia||viral vaccines||adolescent||antihypertensive agents|
|global health||diagnosis||middle east respiratory syndrome coronavirus||fever||diabetes mellitus, type 2|
|quarantine||transmission||antibodies, viral||risk factor||heart diseases|
|united states||prevention||wuhan||lung||angiotensin ii|
|italy||ards||receptors, virus||retrospective studies||myocarditis|
|practice guidelines as topic||influenza||clinical trials as topic||cough||cardiovascular system|
To open the map directly in VOSviewer, please use these two files.
The maps are created with the following “thesaurus” to clean the data: