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Human Vaccines & Immunotherapeutics Volume 18, 2022 - Issue 1
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Novel Vaccines – Research Paper

HIV-1 genetic diversity a challenge for AIDS vaccine development: a retrospective bibliometric analysis

Abdur Rashida School of Medicine, Nankai University, Tianjin, China;b State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaView further author information
,
Kang Lib State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China;c Key Laboratory of Molecular Microbiology and Technology, Ministry of Education, College of Life Sciences, Nankai University, Tianjin, ChinaView further author information
,
Yi Fengb State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaView further author information
,
Tauseef Ahmadd Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-8793-273XView further author information
ORCID Icon,
Yimam Getanehb State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaView further author information
,
Yueyang Yua School of Medicine, Nankai University, Tianjin, China;b State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaView further author information
,
Xiaoyan Hua School of Medicine, Nankai University, Tianjin, China;b State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaView further author information
,
Syed Hani Abidie Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, PakistanView further author information
&
Yiming Shaoa School of Medicine, Nankai University, Tianjin, China;b State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaCorrespondence[email protected]
View further author information
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Article: 2014733 | Received 13 Oct 2021, Accepted 01 Dec 2021, Published online: 11 Jan 2022

Figures & data

Table 1. Main information about the retrieved data on HIV-1 genetic diversity from WoSCC database

Figure 1. Annual distribution of publications on HIV-1 genetic diversity from 1998- May 15, 2021.

Figure 1. Annual distribution of publications on HIV-1 genetic diversity from 1998- May 15, 2021.

Table 2. Top 10 most prolific authors ranked by total number of publications

Figure 2. Top 10 most prolific authors’ in HIV-1 genetic diversity.

Figure 2. Top 10 most prolific authors’ in HIV-1 genetic diversity.

Table 3. Top 10 journals in HIV-1 genetic diversity research

Figure 3. Top 10 journals annual distribution of publications on HIV-1 genetic diversity.

Figure 3. Top 10 journals annual distribution of publications on HIV-1 genetic diversity.

Table 4. Top 10 most productive institutions ranked by number of publications

Figure 4. (a) Corresponding authors’ countries annual distribution of publications. (b) Mutual collaboration between the corresponding authors’ countries in HIV-1 genetic diversity research.

Figure 4. (a) Corresponding authors’ countries annual distribution of publications. (b) Mutual collaboration between the corresponding authors’ countries in HIV-1 genetic diversity research.

Table 5. Top 20 prolific corresponding authors countries and their collaborative publications

Table 6. Top 20 highly cited publications on HIV-1 genetic diversity

Figure 5. Coauthorship countries network visualization. Nine clusters between 50 coauthorship countries; Cluster 1 (Countries 14: Belgium, Bulgaria, Denmark, Finland, Greece, India, Israel, Italy, Luxembourg, Mexico, Netherlands, Romania, South Korea, Sweden; Cluster 2 (Countries 8: Burkina Faso, Cameroon, Cote Ivoire, Democratic Republic of Cango, France, Gabon, Republic of Cango, Senegal); Cluster 3 (Countries 6: England, Pakistan, Scotland, Uganda, USA, Zambia); Cluster 4 (Countries 6: Australia, Japan, Malaysia, China, Taiwan, Thailand); Cluster 5 (Countries 5: Angola, Argentina, Brazil, Peru, Portugal); Cluster 6 (Countries 4: Cuba, Russia, Spain, Switzerland); Cluster 7 (Countries 3: Canada, Iran, Kenya); Cluster 8 (Countries 3: Germany, South Africa, Tanzania); Cluster 9 (Countries 1: Nigeria).

Correct the label number...it is not 3
Figure 5. Coauthorship countries network visualization. Nine clusters between 50 coauthorship countries; Cluster 1 (Countries 14: Belgium, Bulgaria, Denmark, Finland, Greece, India, Israel, Italy, Luxembourg, Mexico, Netherlands, Romania, South Korea, Sweden; Cluster 2 (Countries 8: Burkina Faso, Cameroon, Cote Ivoire, Democratic Republic of Cango, France, Gabon, Republic of Cango, Senegal); Cluster 3 (Countries 6: England, Pakistan, Scotland, Uganda, USA, Zambia); Cluster 4 (Countries 6: Australia, Japan, Malaysia, China, Taiwan, Thailand); Cluster 5 (Countries 5: Angola, Argentina, Brazil, Peru, Portugal); Cluster 6 (Countries 4: Cuba, Russia, Spain, Switzerland); Cluster 7 (Countries 3: Canada, Iran, Kenya); Cluster 8 (Countries 3: Germany, South Africa, Tanzania); Cluster 9 (Countries 1: Nigeria).

Figure 6. (a) Author keywords co-occurrence network visualization. Eight clusters were formed; Cluster 1: (13 keywords) Cluster 2: (10 keywords), Cluster 3: (9 keywords), Cluster 4: (9 keywords), Cluster 5: (7 keywords), Cluster 6: (6 keywords), Cluster 7: (4 keywords), cluster 8: (4 keywords). (b) Authors’ keywords wordcloud visualization analysis.

Figure 6. (a) Author keywords co-occurrence network visualization. Eight clusters were formed; Cluster 1: (13 keywords) Cluster 2: (10 keywords), Cluster 3: (9 keywords), Cluster 4: (9 keywords), Cluster 5: (7 keywords), Cluster 6: (6 keywords), Cluster 7: (4 keywords), cluster 8: (4 keywords). (b) Authors’ keywords wordcloud visualization analysis.

Figure 7. Cited sources network visualization. Four clusters were formed; Cluster 1 (sources 66), Cluster 2 (sources 64), Cluster 3 (Sources 29), Cluster 4 (sources 19).

Figure 7. Cited sources network visualization. Four clusters were formed; Cluster 1 (sources 66), Cluster 2 (sources 64), Cluster 3 (Sources 29), Cluster 4 (sources 19).

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