Global research activity on mathematical modeling of transmission and control of 23 selected infectious disease outbreak

Sweileh, Waleed M.

doi:10.1186/s12992-022-00803-x

“…The data of this study were derived from the Scopus database. For numerous reasons, the current analysis was performed using the SciVerse Scopus database [34][35][36]. First, compared to other databases such as PubMed or Web of Science, Scopus has a much larger number and diversity of indexed publications.…”

Section: Sources Of Literature Datamentioning

confidence: 99%

“…This comprises mapping and statistical analysis. Finally, Scopus is the database most commonly used to search for bibliometric studies and obtain articles on various scientific topics [35,[38][39][40][41][42]. The literature data search was conducted on February 18, 2022.…”

Section: Sources Of Literature Datamentioning

confidence: 99%

Global research trends on the links between insulin resistance and obesity: a visualization analysis

Zyoud

¹

,

Shakhshir

²

,

Abushanab

³

et al. 2022

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Background Obesity increases the chance of developing insulin resistance. Numerous inflammatory markers have been linked to an increased risk of insulin resistance in obese individuals. Therefore, we performed a bibliometric analysis to determine global research activity and current trends in the field of obesity and insulin resistance. Methods Scopus was used between 2002 and 2021 to retrieve publications related to terms related to obesity and insulin resistance. Data were exported to Microsoft Excel. Additionally, we use VOSviewer software to create visualization maps that describe international collaborations and research hotspots. Results We identified 6626 publications, including 5754 journal articles, 498 review articles, and 109 letters to the editor. The most productive countries were the United States (n = 995, 30.11%), followed by China (n = 650, 9.81%), Italy (n = 412, 6.22%) and Spain (n = 386, 5.83%). Previously to 2012, this field was mainly focused on ‘adipocyte dysfunctions that link obesity with insulin resistance”; and ‘relationship between obesity, insulin resistance, and risk of cardiovascular disease’. ‘Supplements improve insulin sensitivity‘, and ‘obesity-induced inflammation and insulin resistance’ were found more recently (after 2014), indicating that research in this field has acquired significant interest and emphasis in recent years. Conclusions This is the first bibliometric study to focus on publications related to insulin resistance and obesity at the global level. Our reporting of quantifiable knowledge in this field may be useful in providing evidence and direction for future research, clinical practice, and educational initiatives.

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“…The documents in the current study were obtained and downloaded from the Scopus database on January 29, 2022 to prevent bias caused by the database’s daily updates. With more than 36000 titles from around 11678 publishers, of which 34346 were peer-reviewed journals, Scopus is one of the most extensive and authoritative databases for collecting academic information[ 14 , 15 ]. Unfortunately, only one database may be utilized in bibliometric analyses because data from many databases cannot be integrated and analyzed.…”

Section: Methodsmentioning

confidence: 99%

Mapping the global research landscape on insulin resistance: Visualization and bibliometric analysis

Zyoud¹,

Shakhshir²,

Koni³

et al. 2022

WJD

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BACKGROUND Insulin resistance is a risk factor for metabolic syndromes and is associated with a wide variety of metabolic illnesses, including obesity, type 2 diabetes, and cardiovascular disease. AIM To investigate and map global insulin resistance studies. METHODS A bibliometric methodology was applied to the literature retrieved from the Scopus database and Reference Citation Analysis ( ) by using a validated search strategy. The study period was limited from 2002 to 2021. Bibliometric indicators and mapping were presented. RESULTS A total of 26808 articles on the topic of insulin resistance were included in the Scopus database. The articles included research articles ( n = 21918; 81.76%), review articles ( n = 2641; 9.85%), and letters ( n = 653; 2.44%). During the study period, 136 countries contributed to the research on insulin resistance. The highest number of articles was from the United States ( n = 7360; 27.45%), followed by China ( n = 3713; 13.85%), Japan ( n = 1730, 6.45%), Italy ( n = 1545; 5.54%), and the United Kingdom ( n = 1484; 5.54%). The retrieved articles identified two main research themes: “inflammatory mechanisms in the regulation of insulin resistance” and “mechanisms linking obesity to insulin resistance”. CONCLUSION Our data show that insulin resistance has steadily gained interest from researchers, as evidenced by the number of citations and yearly publications. Publications have grown significantly in the last decade, while low-income countries with greater burdens continue to produce fewer publications in this field. This approach might assist researchers in choosing new research areas and recognizing research hotspots and frontiers. In the future, perhaps high-quality clinical evidence will be acquired.

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“…Sensitivity analysis helps to identify the most influential parameters on the basic reproduction number so efforts to control the problem are directed to these parameters. Mathematically, we compute the sensitivity analysis of our model system of equations based on the classical definition [ 14 , 15 ] defined as the normalized forward sensitivity index of a variable R 0 , which depends differentiably on a parameter p , given by △ p R 0 = p / R 0 × ∂R 0 / ∂p .…”

Section: Model Analysismentioning

confidence: 99%

“…Mathematical model is a mathematical equation that describes changes in the system with time, and it is useful to accurately predict the evolution of infectious disease (COVID-19), and this in turn helps to give an insight for health workers and government to deal on the most influential parameters in COVID-19 transmission [ 15 ]. Since COVID-19 outbreak, different scholars studied the transmission dynamics of the disease (COVID-19) by considering different scenarios [ 1 , 2 , 5 , 9 – 11 , 14 – 21 ] to curb its spread with the help of epidemiological mathematical model.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Model and Analysis on the Impact of Awareness Campaign and Asymptomatic Human Immigrants in the Transmission of COVID‐19

Anteneh

¹

,

Bazezew

²

,

Palanisamy

³

2022

BioMed Research International

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In this study, an autonomous type deterministic nonlinear mathematical model that explains the transmission dynamics of COVID-19 is proposed and analyzed by considering awareness campaign between humans and infectives of COVID-19 asymptomatic human immigrants. Unlike some of other previous model studies about this disease, we have taken into account the impact of awareness c between humans and infectives of COVID-19 asymptomatic human immigrants on COVID-19 transmission. The existence and uniqueness of model solutions are proved using the fundamental existence and uniqueness theorem. We also showed positivity and the invariant region of the model system with initial conditions in a certain meaningful set. The model exhibits two equilibria: disease (COVID-19) free and COVID-19 persistent equilibrium points and also the basic reproduction number, R 0 which is derived via the help of next generation approach. Our analytical analysis showed that disease-free equilibrium point is obtained only in the absence of asymptomatic COVID-19 human immigrants and disease (COVID-19) in the population. Moreover, local stability of disease-free equilibrium point is verified via the help of Jacobian and Hurwitz criteria, and the global stability is verified using Castillo-Chavez and Song approach. The disease-free equilibrium point is both locally and globally asymptotically stable whenever R 0 < 1 , so that disease dies out in the population. If R 0 > 1 , then disease-free equilibrium point is unstable while the endemic equilibrium point exists and stable, which implies the disease persist and reinvasion will occur within a population. Furthermore, sensitivity analysis of the basic reproduction number, R 0 with respect to model parameters, is computed to identify the most influential parameters in transmission as well as in the control of COVID-19. Finally, some numerical simulations are illustrated to verify the theoretical results of the model.

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Global research activity on mathematical modeling of transmission and control of 23 selected infectious disease outbreak

Cited by 59 publications

References 75 publications

Global research trends on the links between insulin resistance and obesity: a visualization analysis

Global research trends on the links between insulin resistance and obesity: a visualization analysis

Mapping the global research landscape on insulin resistance: Visualization and bibliometric analysis

Mathematical Model and Analysis on the Impact of Awareness Campaign and Asymptomatic Human Immigrants in the Transmission of COVID‐19

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