Shuangsheng Wu
- Epidemiology top 10%
- Infectious Diseases top 5%
- Health top 5%
- Modeling and Simulation top 2%
- Public Health, Environmental and Occupational Health
- Co-authors
- Quanyi WangPeng YangChunna MaYi ZhangDaitao ZhangWeixian ShiYang PanWei Duan
- Topics
- Influenza Virus Research Studies (36 papers)Respiratory viral infections research (26 papers)COVID-19 epidemiological studies (9 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Shuangsheng Wu
57 papers receiving 673 citations
Peers
Comparison fields: 5 of 93
- Epidemiology 436
- Infectious Diseases 246
- Health 186
- Modeling and Simulation 136
- Public Health, Environmental and Occupational Health 91
Countries citing papers authored by Shuangsheng Wu
This map shows the geographic impact of Shuangsheng Wu'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 Shuangsheng Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuangsheng Wu more than expected).
Fields of papers citing papers by Shuangsheng Wu
This network shows the impact of papers produced by Shuangsheng Wu. 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 Shuangsheng Wu. The network helps show where Shuangsheng Wu may publish in the future.
Co-authorship network of co-authors of Shuangsheng Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Shuangsheng Wu. A scholar is included among the top collaborators of Shuangsheng Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shuangsheng Wu. Shuangsheng Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 16 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 73 | |
| 9 | 5 | |
| 10 | 24 | |
| 11 | 20 | |
| 12 | [emm types of mutation in scarlet-fever-related group A streptococcal, among children in Beijing, 2011-2014]. | 3 |
| 13 | [Study on the superantigen gene profiles of group A Streptococcus isolated from children in Beijing, 2014]. | 1 |
| 14 | 1 | |
| 15 | 15 | |
| 16 | 13 | |
| 17 | 1 | |
| 18 | [Analysis of status and influence factors of health literacy related to infectious diseases in residents of Beijing]. | 2 |
| 19 | [Influenza vaccination coverage rates and factors associated with vaccine use among the elderly in Beijing during 2008-2010]. | 4 |
| 20 | 1 |
About Shuangsheng Wu
Shuangsheng Wu is a scholar working on Modeling and Simulation, Infectious Diseases and Epidemiology, having authored 59 papers that have together received 684 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (36 papers), Respiratory viral infections research (26 papers) and COVID-19 epidemiological studies (9 papers). The work is most often cited by research in Modeling and Simulation (136 citations), Health (186 citations) and Infectious Diseases (246 citations). Shuangsheng Wu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Quanyi Wang, Peng Yang, Chunna Ma, Yi Zhang, Daitao Zhang, Weixian Shi, Yang Pan, Wei Duan, Li Zhang and Xiaomin Peng. Their work appears in journals such as PLoS ONE, Emerging infectious diseases and Biosensors and Bioelectronics.
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.