The results section is intentionally kept brief, as results will evolve as more research becomes available and will be reported to greater extent on the associated website: http://covid19biblio.com/ The results presented in this study are as of March 23rd, 2020.
Keyword co-occurrence analysis
There were 225 keywords that occurred in three or more manuscripts. These divided into four clusters. These are shown in the keyword co-occurrence network diagram (figure 1a). While the contents of the clusters are likely to develop in future analysis the current clusters seem to represent the following (see figure 1a for colour reference):
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 like 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 Severe Acute Respiratory Syndrome (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.
Four keywords act as bridging words in the keyword co-occurrence network graph, connecting the clusters and graph together to a high degree. These are: China, Betacoronavirus, Viral pneumonia and Coronavirus infection.
Figure 1b illustrates a section of figure 1a, and shows what the graph looks like when it is displayed with the interactive tool, when you select the term “risk assessment”.
Bibliometric coupling analysis
Of the 411 articles available in Scopus, 280 of them included a reference list and were included in the bibliometric coupling analysis. The network graph subsequently comprised of four clusters, as shown in figure 2.
Cluster 1 (red) related to contributions giving an “Overview of the new virus” and included literature on a wide variety of topics like genomic characterization, pathology, diagnosis and treatment, recognition of this pandemic stemming from China, and first lessons from clinical management. The subgroup “Commentaries on the new virus” related to literature on the first cases, the infection being without borders, therapeutics and triage. Another subgroup, “Commentaries on the phenomenon”, included literature on the virus spread and the reproductively of the virus.
Cluster 2 (green) related to contributions to “Clinical medicine”, including topics such as transmission routes, epidemiology, clinical characteristics of patients (age, gender, fever, abdominal symptoms). One subgroup related to “Clinical medical characteristics”, with topics like those mentioned above. Another subgroup consisted of literature on “Endemic areas” such as China, Wuhan, Korea, Thailand and Africa. A smaller subgroup, “Comparisons with SARS”, consisted of literature comparing the current pandemic with SARS.
Cluster 3 (blue) “On the virus” consisted of literature on topics ranging from the origin of the virus, its genome, possible therapeutics and early research on these topics. A major subgroup in this cluster, “the virus’ origin and its genome”, included topics like zoonotic spillover and transmission, but also early literature on the outbreak of the pandemic. Another subgroup, “Possible therapeutics”, included literature on chloroquine, Chinese herbal medicine, anti-viral drugs and the ACE2 receptor. A third large subgroup, “Early research on genome and therapeutics” included literature on receptors, transmission, detection and vaccine.
Cluster 4 (yellow), was by far the smallest cluster. It consisted of literature on “Reproduction rate and spread”, but also covers literature on screening, the pandemic and treatment. While this cluster was less well defined in the present analysis, this may change as the corpus of published work grows in the coming weeks and months.
Accessing this network diagram online, allows the reader to search for articles by author, identify related studies, and directly access the article by clicking on it.