Kun Su
Impact in
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research
- SARS-CoV-2 detection and testing
- COVID-19 Clinical Research Studies
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
Papers in
-
- Influenza Virus Research Studies 6
- Data-Driven Disease Surveillance 2
- Virology 2
- Rabies epidemiology and control 2
- Co-authors
- Ailong Huang (2 shared papers)Jingfu Qiu (2 shared papers)Bo Wu (2 shared papers)Yong Zhang (2 shared papers)Qin Li (2 shared papers)Fan Zhang (1 shared paper)Haijun Deng (1 shared paper)Juan Chen (1 shared paper)
In The Last Decade
Kun Su
19 papers receiving 2.3k citations
Kun Su's Hit Papers
Peers
Comparison fields: 5 of 82
- Infectious Diseases 1.4k
- Modeling and Simulation 156
- General Dentistry 5
- Virology 34
- Neurology 34
Countries citing papers authored by Kun Su
This map shows the geographic impact of Kun Su'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 Kun Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Su more than expected).
Fields of papers citing papers by Kun Su
This network shows the impact of papers produced by Kun Su. 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 Kun Su. The network helps show where Kun Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Su, 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 | Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections Hit paper breakdown → | 2020 | 2098 |
| 2 | 2020 | 59 | |
| 3 | 2019 | 46 | |
| 4 | 2018 | 45 | |
| 5 | 2020 | 27 | |
| 6 | 2018 | 25 | |
| 7 | 2020 | 21 | |
| 8 | 2019 | 16 | |
| 9 | 2021 | 14 | |
| 10 | 2022 | 9 | |
| 11 | 2022 | 9 | |
| 12 | 2014 | 8 | |
| 13 | 2018 | 7 | |
| 14 | 2019 | 6 | |
| 15 | 2022 | 6 | |
| 16 | 2022 | 5 | |
| 17 | 2024 | 5 | |
| 18 | 2024 | 4 | |
| 19 | 2022 | 2 | |
| 20 | 2020 | 1 |
About Kun Su
Kun Su is a scholar working on Epidemiology, Virology, Health, Toxicology and Mutagenesis, Infectious Diseases and Modeling and Simulation, having authored 20 papers that have together received 2.4k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (6 papers), Rabies epidemiology and control (2 papers), Climate Change and Health Impacts (2 papers), Data-Driven Disease Surveillance (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Streptococcal Infections and Treatments (1 paper), COVID-19 epidemiological studies (1 paper) and Vaccine Coverage and Hesitancy (1 paper). The work is most often cited by research in Infectious Diseases (1.4k citations), Modeling and Simulation (156 citations), General Dentistry (5 citations), Virology (34 citations) and Neurology (34 citations). Kun Su has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include Ailong Huang, Jingfu Qiu, Bo Wu, Yong Zhang, Qin Li, Fan Zhang, Haijun Deng, Juan Chen, Jieli Hu and Wei Xü. Their work appears in journals such as International Journal of Infectious Diseases, Nature Medicine, International Journal of Environmental Research and Public Health, Epidemiology and Infection and BMC 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.