Co-Occurrence Analysis of COVID-19 Publications with an Emphasis on the Global Health Governance (GHG)

Abstract

Abstract Background: Analyzing co-occurrence is an effective way to monitor the overview of topic spreading. The present study aimed to conduct a co-occurrence analysis of scientific publications related to COVID-19, emphasizing Global Health Governance (GHG). Materials and Methods: This applied research with an analytical approach was carried out on all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The research population consisted of all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The data were analyzed using BibExcel, UCINET, Excel, and SPSS software, and Spearman’s test was used to confirm correlations. Results: The co-word network of the thematic area of COVID-19 includes 226 nodes and 7292 edges. COVID-19 and the pandemic formed the most co-word pairs with 2224 connections. The COVID-19* mental health and COVID-19* anxiety, with 1019 and 925 connections, are ranked next, respectively. The term COVID-19 is ranked first with a centrality index of 225. The keywords of pandemic and public health are ranked second and third with the centrality index of 217 and 206, respectively. Conclusion: The global approach of studies related to COVID-19 is more inclined to the epidemiological and public health fields. Assuming the GHG, detailed and comprehensive planning should be performed to strengthen these studies and pave the way for international cooperation, determining research requisites, and developing applied research studies.