Kayode Oshinubi
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies 23
- Fractional Differential Equations Solutions 6
- Virology top 5%
- Poxvirus research and outbreaks 4
-
- Mathematical and Theoretical Epidemiology and Ecology Models 12
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research 4
-
- COVID-19 Pandemic Impacts 5
-
- COVID-19 diagnosis using AI 5
-
- Bacteriophages and microbial interactions 4
- Co-authors
- Olumuyiwa James PeterFestus Abiodun OguntoluJacques DemongeotMusa RabiuNitu KumariMustapha RachdiEmmanuel AddaiAdesoye Idowu Abioye
- Journals
- SHILAP Revista de lepidopterología (8 papers)Viruses (1 paper)Frontiers in Public Health (2 papers)
- Partner nations
- FranceNigeriaUnited States
In The Last Decade
Kayode Oshinubi
35 papers receiving 620 citations
Hit Papers
Peers
Comparison fields: 5 of 73
- Modeling and Simulation 318
- Virology 208
- Public Health, Environmental and Occupational Health 234
- Infectious Diseases 134
- Plant Science 108
Countries citing papers authored by Kayode Oshinubi
This map shows the geographic impact of Kayode Oshinubi'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 Kayode Oshinubi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kayode Oshinubi more than expected).
Fields of papers citing papers by Kayode Oshinubi
This network shows the impact of papers produced by Kayode Oshinubi. 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 Kayode Oshinubi. The network helps show where Kayode Oshinubi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kayode Oshinubi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 4 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 0 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 26 | |
| 8 | 2023 | 11 | |
| 9 | 2023 | 30 | |
| 10 | 2023 | 9 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 34 | |
| 13 | 2022 | 7 | |
| 14 | 2021 | 21 | |
| 15 | 2021 | 2 | |
| 16 | 2021 | 14 | |
| 17 | 2021 | 2 | |
| 18 | Transmission dynamics of Monkeypox virus: a mathematical modelling approachbreakdown → | 2021 | 191 |
| 19 | 2021 | 4 | |
| 20 | 2021 | 65 |
About Kayode Oshinubi
Kayode Oshinubi is a scholar working on Modeling and Simulation, Virology and Public Health, Environmental and Occupational Health, having authored 39 papers that have together received 644 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (23 papers), Mathematical and Theoretical Epidemiology and Ecology Models (12 papers), Fractional Differential Equations Solutions (6 papers), COVID-19 Pandemic Impacts (5 papers), COVID-19 diagnosis using AI (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Bacteriophages and microbial interactions (4 papers) and Poxvirus research and outbreaks (4 papers). The work is most often cited by research in Modeling and Simulation (318 citations), Virology (208 citations) and Public Health, Environmental and Occupational Health (234 citations). Kayode Oshinubi has collaborated with scholars based in France, Nigeria and United States. Frequent co-authors include Olumuyiwa James Peter, Festus Abiodun Oguntolu, Jacques Demongeot, Musa Rabiu, Nitu Kumari, Mustapha Rachdi, Emmanuel Addai, Adesoye Idowu Abioye, Abdullahi Ibrahim and Hammed Abiodun Ogunseye. Their work appears in journals such as SHILAP Revista de lepidopterología, Viruses and Frontiers in Public Health.
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.