Wilbert Sibanda

33 papers receiving 325 citations

Peers

Wilbert Sibanda
Comparison fields: 5 of 104
  • Applied Microbiology and Biotechnology 22
  • Endocrinology, Diabetes and Metabolism 48
  • Infectious Diseases 50
  • Epidemiology 72
  • Molecular Medicine 10
Replace Fabrice Ruiz with:
Fabrice Ruiz France
Andrés Gaviria‐Mendoza Colombia
Feras Jirjees United Arab Emirates
Dipu T Sathyapalan India
Jessica L. Sturtevant United States
Yusuf Ali Bangladesh
Alpesh Amin United States
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Citations per year

Countries citing papers authored by Wilbert Sibanda

Since Specialization
Citations

This map shows the geographic impact of Wilbert Sibanda's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wilbert Sibanda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wilbert Sibanda more than expected).

Fields of papers citing papers by Wilbert Sibanda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wilbert Sibanda. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wilbert Sibanda. The network helps show where Wilbert Sibanda may publish in the future.

Co-authors

The 25 scholars most cited alongside Wilbert Sibanda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Wilbert Sibanda Line = papers co-authored together Wilbert Sibanda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201779
2 201128
3 202125
4 201824
5 201921
6 201320
7
Artificial Neural Networks- A Review of Applications of Neural Networks in the Modeling of HIV Epidemic
201219
8 200416
9 201714
10 201711
11 200510
12 20119
13 20189
14 20127
15
Comparative Study of the Application of Box Behnken Design (BBD) and Binary Logistic Regression (BLR) to Study the Effect of Demographic Characteristics on HIV Risk in South Africa.
20126
16 20205
17 20224
18 20174
19 20193
20 20233

About Wilbert Sibanda

Wilbert Sibanda is a scholar working on General Health Professions, Epidemiology, Infectious Diseases, Sociology and Political Science and Artificial Intelligence, having authored 37 papers that have together received 340 indexed citations. Recurring topics across this work include Adolescent Sexual and Reproductive Health (3 papers), Bayesian Methods and Mixture Models (3 papers), HIV/AIDS Research and Interventions (3 papers), HIV/AIDS Impact and Responses (3 papers), Statistical Distribution Estimation and Applications (2 papers), Drug Solubulity and Delivery Systems (2 papers), Cervical Cancer and HPV Research (2 papers) and Emergency and Acute Care Studies (2 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (22 citations), Endocrinology, Diabetes and Metabolism (48 citations), Infectious Diseases (50 citations), Epidemiology (72 citations) and Molecular Medicine (10 citations). Wilbert Sibanda has collaborated with scholars based in South Africa, United States and Netherlands. Frequent co-authors include Basil J. Pillay, Thumbi Ndung’u, Sabiha Y. Essack, Viness Pillay, Michael P. Danckwerts, Alain Assounga, Koleka Mlisana, Nomonde R. Mvelase, James C. M. Brust and S Pillay. Their work appears in journals such as BMC Nephrology, Open Forum Infectious Diseases, Sustainability, International Journal of Pharmaceutics and AAPS PharmSciTech.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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