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Modeling COVID-19 Transmission Dynamics: A Bibliometric Review.

ABSTRACT: A good amount of research has evolved just in three years in COVID-19 transmission, mortality, vaccination, and some socioeconomic studies. A few bibliometric reviews have already been performed in the literature, especially on the broad theme of COVID-19, without any particular area such as transmission, mortality, or vaccination. This paper fills this gap by conducting a bibliometric review on COVID-19 transmission as the first of its kind. The main aim of this study is to conduct a bibliometric review of the literature in the area of COVID-19 transmission dynamics. We have conducted bibliometric analysis using descriptive and network analysis methods to review the literature in this area using RStudio, Openrefine, VOSviewer, and Tableau. We reviewed 1103 articles published in 2020-2022. The result identified the top authors, top disciplines, research patterns, and hotspots and gave us clear directions for classifying research topics in this area. New research areas are rapidly emerging in this area, which needs constant observation by researchers to combat this global epidemic.

SUBMITTER: Goswami GG

PROVIDER: S-EPMC9655715 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Modeling COVID-19 Transmission Dynamics: A Bibliometric Review.

Goswami Gour Gobinda GG Labib Tahmid T

International journal of environmental research and public health 20221029 21

A good amount of research has evolved just in three years in COVID-19 transmission, mortality, vaccination, and some socioeconomic studies. A few bibliometric reviews have already been performed in the literature, especially on the broad theme of COVID-19, without any particular area such as transmission, mortality, or vaccination. This paper fills this gap by conducting a bibliometric review on COVID-19 transmission as the first of its kind. The main aim of this study is to conduct a bibliometr ...[more]

PMID: 36361019

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Project description:BackgroundDuring the COVID-19 pandemic, the vulnerabilities of certain groups of people have been highlighted, such as people with intellectual disability (ID). Although related research on ID has developed rapidly during the COVID-19 pandemic, the quantitative analysis of those research results has not been systematically performed through bibliometric analysis. Bibliometric analysis is a useful and rigorous method to explore large volumes of research data, and it allows researchers to extract quantitative information on distribution by author, time, country, and journal.AimThe aim of the present study is to comprehensively analyze the current status and developing trends in publications on ID research related to and conducted during the COVID-19 pandemic.MethodsA bibliometric analysis was performed using the Web of Science database. Biblioshiny software was used to analyze and visualize the following information: main information of dataset, annual scientific production, journals which published the most relevant sources, most-cited authors, most-cited countries, most-cited global documents, word-cloud of keywords authors have used, and both the co-occurrence and co-citation networks.ResultsA total of 450 publications were included. The average number of citations per document was 5.104. Among the top three journals, Journal of Applied Research in Intellectual Disabilities published 32 articles, Journal of Intellectual Disability Research published 29 articles, and British Journal of Learning Disabilities published 17 articles. The article with the title COVID-19 and People with Intellectual Disability: Impact of a Pandemic was the most cited with total 144 citations The United Kingdom had the most publications and had strong cooperative relationships with the United States, Canada, and Australia. The most popular keywords included mental health, autism, developmental disability, and lockdown. Thematic map analysis identified several possible clusters, including telemedicine, physical activities, and mental health.ConclusionThe present study provides a better understanding in this research field and may help clinicians, researchers and stakeholders to obtain more comprehensive view of ID and COVID-19. The insights gained from this analysis could inform future research.

Project description:BackgroundUganda has a unique set up comprised of resource-constrained economy, social-economic challenges, politically diverse regional neighborhood and home to long-standing refuge crisis that comes from long and protracted conflicts of the great lakes. The devastation of the on-going global pandemic outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is likely to be escalated by these circumstances with expectations of the impact of the disease being severe.Materials and methodsIn this study, we formulate a mathematical model that incorporates the currently known disease characteristics and tracks various intervention measures that the government of Uganda has implemented since the reporting of the first case in March 2020. We then evaluate these measures to understand levels of responsiveness and adherence to standard operating procedures and quantify their impact on the disease burden. Novel in this model was the unique aspect of modeling the trace-and-isolate protocol in which some of the latently infected individuals tested positive while in strict isolation centers thereby reducing their infectious period.ResultsThe study findings show that even with elimination of all imported cases at any given time it would take up to nine months to rid Uganda of the disease. The findings also show that the optimal timing of easing of lockdowns while mitigating the possibility of re-emergence of a second epidemic wave requires avoiding the scenario of releasing too-many-too-soon. It is even more worrying that enhancing contact tracing would only affect the magnitude and timing of the second wave but cannot prevent it altogether.ConclusionWe conclude that, given the prevailing circumstances, a phased-out lifting of lockdown measures, minimization of COVID-19 transmissibility within hospital settings, elimination of recruitment of infected individuals as well as enhanced contact tracing would be key to preventing overwhelming of the healthcare system that would come with dire consequences.

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Modeling COVID-19 Transmission Dynamics: A Bibliometric Review.

Publications

Modeling COVID-19 Transmission Dynamics: A Bibliometric Review.

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