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 |
| 7th March | 106888 |
| 7th April | 116545 |
Keyword Co-Occurrence Network Graph for the Overall Research Field on COVID-19 up to April 20th, 2020.
Corpus downloaded from PubMed 20th April: 5228 publications. There were 853 keywords that occurred in three or more manuscripts. These divided into four main clusters.
Cluster descriptions
Cluster 1 could be called «A global virus pandemic» and includes terms like (beta)coronavirus infection, viral pneumonia, disease outbreak and public health. This cluster contains 2 major topics: a) “preventive epidemiology”, which in addition to the terms like disease outbreak and public health includes terms like travel, global heath and civil defence and b) “care management” which includes terms like infection control, practice guidelines and health personnel
Cluster 2 could be called “disease epidemiology” and includes terms like epidemiology, outbreak, infection, infectious diseases, novel coronavirus pneumonia, treatment and transmission. This is a small cluster with only this major topic
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, phylogeny and chiroptera includes terms like spike glycoprotein and peptidyl-dipeptidase a and b) “drug treatment” which in addition to the term antiviral agent 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.
Cluster 5 could be named “related topics” and contains terms like mental health and anxiety and depression one side , but also terms like surveys and questionnaires, cross-sectional studies and health knowledge; attitudes and practice on the other. This is the smallest cluster with only one topic
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) | Cluster 5 (Purple) |
| coronavirus infection | pneumonia | sars | female | mental health |
| viral pneumonia | epidemiology | animals | male | health knowledge, attitudes, practice |
| betacoronavirus | outbreak | zoonosis | adult | anxiety |
| pandemic | infection | antiviral agents | middle aged | depression |
| china | infectious diseases | genome, viral | aged | fear |
| disease outbreaks | novel coronavirus pneumonia | phylogeny | clinical laboratory techniques | social support |
| public health | treatment | chiroptera | young adult | anxiety disorders |
| travel | transmission | spike glycoprotein, coronavirus | children | emotions |
| epidemic | prevention | peptidyl-dipeptidase a | adolescent | health status |
| global health | inflammation | viral vaccines | tomography, x-ray computed | resilience, psychological |
VOSViewer files:
To open the map directly in VOSviewer, please use these two files.
CoOccurrance3Inst1Resol20thApril20NET
CoOccurrance3Inst1Resol20thApril20MAP
The maps are created with the following “thesaurus” to clean the data: Thesaurus13thApril
Keyword Co-Occurrence Network Graph for the Overall Research Field on COVID-19 up to April 13th, 2020.
Corpus downloaded from PubMed 13th April: 3683 publications. There were 607 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 | male |
| viral pneumonia | epidemiology | animals | female |
| betacoronavirus | zoonosis | genome, viral | adult |
| pandemic | outbreak | antiviral agents | middle aged |
| china | wuhan | phylogeny | aged |
| disease outbreaks | viruses | chiroptera | young adult |
| travel | infection | spike glycoprotein, coronavirus | adolescent |
| public health | novel coronavirus pneumonia | peptidyl-dipeptidase a | children |
| infection control | infectious diseases | viral vaccines | tomography, x-ray computed |
| global health | transmission | antibodies, viral | fever |
VOSViewer files:
To open the map directly in VOSviewer, please use these two files.
CoOccurrance3Inst1Resol13thApril20MAP
CoOccurrance3Inst1Resol13thApril20NET
The maps are created with the following “thesaurus” to clean the data: Thesaurus13thApril
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
|
The disease and its pathophysiology
|
Clinical epidemiology of the disease
|
Treatment of the disease
|
| 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 |