Bibliometric analyses of COVID-19 research

Applications for the bibliometric Co-occurrence analysis:

  • Offers an overview of:
    • the structure of topics investigated,
    • the relative focus, as measured by the number of occurrences, shown as the size of nodes.
    • The different colors indicate different general research foci.
  • Identifying the most relevant search terms.
    • The keywords in the map are those commonly used by article authors, with differences across the research areas. Identifying the most relevant terms can help narrow the search to the most relevant articles.

To access the interactive map, you need to open the graph in VosViewer, which allows you to search the map, see what keywords are connected, and the strength of the connection between each node in the graph diagram. To open the map in VosViewer, Please click here, and allow it to download, then open the file and allow Java to run. For a video demonstration of how to do this, please see here.

For more information about what a bibliometric keyword co-occurrence analysis is, please see the About page. The data is downloaded from PubMed.

Insights and trends

Some insights from the weekly bibliometric keyword co-occurrence analyses conducted since March 2020 include that there has been a very rapid increase in COVID-19 literature. From 992 on March 16th, when we initiated this project, to over 50 000 now. Below we refer to some insights and trends. For more details, please read the individual blog posts. 

Early in the pandemic, the research focus, based on 1323 publications on March 23rd, was on topics within “Health and pandemic management,” “The disease and its pathophysiology,” “Clinical epidemiology of the disease,” and “Treatment of the disease”. Please see the preprint for a more detailed description

About a month later, on April 20th, the number of publications had increased with 395%; to 5228. Moreover, the research landscape had changed somewhat. The topics studied can be described as 1) «A global virus pandemic» including topics within “preventive epidemiology” and “care management.” 2) “Disease epidemiology,” 3) “Pathophysiology and origin,” including topics within “viral biology” and “drug treatment”, 4) “Clinical epidemiology”, and 5) a fifth cluster includes topics on mental health and attitudes. The topic of mental health starts to emerge as a research focus within the COVID-19 pandemic research. During March and April, several countries have introduced strict social distancing measures to reduce the spread of the covid-19 virus. New research focuses on how the pandemic affects people’s mental health and feelings of isolation and loneliness.  For more details, click here

On July 23rd, the focus of the most recent literature was on 1) Public health strategies, treatment, and the global impact of COVID-19, 2) the role of existing drugs and vaccines in the current pandemic, 3) demographics and risk factors, 4) literature concentrated on understanding the nature of the virus, and 5) COVID-19 and mental health. For more details, check out this post

For an illustration of the change in research trends across the very early stages of the pandemic and later stages, please see our post from September 23rd: Click here

Growth in number of documents by week:

Date Nr. of docs in PubMed
16th March 992
6th April 2684
04th May 8791
01st June 17356
06th July 28256
03rd August 36201
7th September 48067
05th October 56023
02nd November 64184
4th December 74801
2021  
3rd January 87286
7th February 97147

 

Keyword Co-Occurrence Network Graph for the Overall Research Field on COVID-19 up to April 6th, 2020.

Keyword Co-Occurrence Network Graph for the Overall Research Field on COVID-19 up to April 6th, 2020.

Corpus downloaded from PubMed 6th April: 2684 publications. There were 453 keywords that occurred in three or more manuscripts. These divided into four main clusters.

Cluster descriptions

Cluster descriptions

Cluster 1 (red) relates to “Health and pandemic management”, and include topics like the epidemic, the impact on global health, the public health, infection control and health personnel. Within this cluster, we found the topic of “Global health politics”, which in addition to terms on the epidemic, the impact on global health and public health included terms like population surveillance, civil defense and risk assessment. Further, within this cluster, we found the topic of “Pandemic management”, which in addition to the terms infection control and health personnel included terms like practice guidelines and patient isolation.

Cluster 2 (green) related to “The disease and its treatment”, including topics like its pneumonia and diagnosis, but also topics like antiviral drugs and artificial respiration. Within this cluster, we found the topic of “Clinical picture”, which in addition to terms on pneumonia and diagnosis, included terms like corona virus and infectious disease. Further, within this cluster, we find the topic of “Drug treatment”, which in addition to the terms antiviral drugs and artificial respiration, includes terms like lopinavir, alanine, chloroquine and clinical trials.

Cluster 3 (blue) related to the “The virus and its epidemiology”, including terms like SARS, it being a zoonosis, its genome and the outbreak in Wuhan. Two major topics were identified within this cluster: “Clinical epidemiology”, which in addition to it being a zoonosis and broke out in Wuhan, includes terms like transmission and basic reproduction rate. The other major topic identified is on the “Virus biology”, which in addition to the terms SARS and genome, included terms like phylogeny, glycoproteins and antibodies.

Cluster 4 (yellow) related to “Clinical epidemiology”, with terms relating to age, gender, and basic clinical signs and procedures (like x-ray, CT, fever).

Table of ten most central keywords in each cluster

(Centrality measure used is weighted degree centrality)

Cluster 1 (Red)
Cluster 2 (Green)
Cluster 3 (Blue)
Cluster 4 (Yellow)
coronavirus infection pneumonia sars female
viral pneumonia antiviral agents animals male
betacoronavirus viral vaccines epidemiology adult
china pregnancy genome, viral middle aged
pandemic influenza, human outbreak aged
disease outbreaks respiration, artificial zoonosis young adult
travel lopinavir phylogeny adolescent
public health ritonavir chiroptera tomography, x-ray computed
epidemic alanine wuhan children
infection control chloroquine spike glycoprotein, coronavirus fever

VOSViewer files:

To open the map directly in VOSviewer, please use these two files.

CoOccurrance3Inst1Resol_6April20MAP

CoOccurrance3Inst1Resol_6April20NET

The maps are created with the following “thesaurus” to clean the data:  Thesaurus6April

Keyword Co-Occurrence Network Graph for the Overall Research Field on COVID-19 up to March 30th, 2020.

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 descriptions

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)
disease outbreaks sars female pneumonia
travel animals male antiviral agents
pandemic epidemiology adult lopinavir
public health genome, viral middle aged respiration, artificial
epidemic phylogeny aged ritonavir
global health outbreak young adult diagnosis, differential
infection control zoonosis children influenza, human
population surveillance wuhan tomography, x-ray computed novel coronavirus pneumonia
united states chiroptera fever alanine
risk assessment communicable diseases, emerging adolescent diagnosis

VOSViewer files:

To open the map directly in VOSviewer, please use these two files.

CoOccurrance3Inst1Resol30March20MAP

CoOccurrance3Inst1Resol30March20NET

The maps are created with the following “thesaurus” to clean the data:  Thesaurus 23 March

Keyword Co-Occurrence Network Graph for the Overall Research Field on COVID-19 up to March 23rd, 2020.

Corpus downloaded from PubMed 23rd March: 1323 publications. There were 225 keywords that occurred in three or more manuscripts. These divided into four clusters.

 

Table of ten most central keywords in each cluster

(Centrality measure used is weighted degree centrality)

Health and pandemic management
(Red)

The disease and its pathophysiology
(Yellow)

Clinical epidemiology of the disease
(Blue)

Treatment of the disease
(Green)

coronavirus infection pneumonia female sars
viral pneumonia outbreak adult animals
betacoronavirus epidemiology male genome, viral
china antiviral agents middle aged phylogeny
disease outbreaks viruses aged zoonosis
travel republic of korea young adult wuhan
pandemic lopinavir fever chiroptera
global health transmission tomography, x-ray computed communicable diseases, emerging
infection control ritonavir children disease reservoirs
public health mortality lung peptidyl-dipeptidase a

VOSViewer files:

To open the map directly in VOSviewer, please use these two files.

CoOccurrance3Inst1Resol23March20MAP

CoOccurrance3Inst1Resol23March20NET

The maps are created with the following “thesaurus” to clean the data:  Thesaurus 23 March

Keyword Co-Occurrence Network Graph for the Overall Research Field on COVID-19 up to March 16th, 2020.


Corpus downloaded from PubMed 16th March: 992 publications)

The table below provides an overview of the most central keywords from each of the clusters in the keyword co-occurrence network graph above.

Table of most central keywords in each cluster from the network graph:

Cluster Red
Cluster GREEN
Cluster BLUE
Cluster YELLOW
Cluster PURPLE
Cluster TEAL

Clinical analysis and treatment

Categorization of epidemic

Epidemiology and Global spread

Prognosis for population groups

Origin and definition

Social prevention measures

pneumonia sars epidemiology adult china coronavirus infection
infection mers australia female outbreak betacoronavirus
novel coronavirus pneumonia epidemic case definition middle aged viruses disease outbreaks
public health pregnancy emerging infectious diseases male wuhan united states
diagnosis infant acute respiratory disease viral pneumonia zoonosis centers for disease control and prevention, u.s.
treatment bat importation aged respiratory infections contact tracing
infectious diseases pandemic travel children transmission travel-related illness
clinical characteristics ace2 isolation radiography, thoracic respiratory disease risk assessment
influenza wuhan pneumonia quarantine young adult cluster practice guidelines as topic
clinical features exposure migration prognosis mathematical model infection control