Anika Singanayagam
- Infectious Diseases top 2%
- Epidemiology top 10%
- Biomedical Engineering
- Modeling and Simulation top 2%
- Molecular Biology
- Co-authors
- Maria ZambonRobin GopalAndré CharlettJamie Lopez BernalVanessa SalibaShamez LadhaniJoanna EllisMonika Patel
- Topics
- Influenza Virus Research Studies (6 papers)Respiratory viral infections research (6 papers)SARS-CoV-2 and COVID-19 Research (4 papers)
- Partner nations
- United KingdomUnited StatesGambia
In The Last Decade
Anika Singanayagam
18 papers receiving 832 citations
Hit Papers
Peers
Comparison fields: 5 of 81
- Infectious Diseases 599
- Epidemiology 250
- Biomedical Engineering 143
- Modeling and Simulation 115
- Molecular Biology 97
Countries citing papers authored by Anika Singanayagam
This map shows the geographic impact of Anika Singanayagam'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 Anika Singanayagam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anika Singanayagam more than expected).
Fields of papers citing papers by Anika Singanayagam
This network shows the impact of papers produced by Anika Singanayagam. 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 Anika Singanayagam. The network helps show where Anika Singanayagam may publish in the future.
Co-authorship network of co-authors of Anika Singanayagam
This figure shows the co-authorship network connecting the top 25 collaborators of Anika Singanayagam. A scholar is included among the top collaborators of Anika Singanayagam 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 Anika Singanayagam. Anika Singanayagam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 35 | |
| 3 | 18 | |
| 4 | 2 | |
| 5 | 5 | |
| 6 | 31 | |
| 7 | Duration of infectiousness and correlation with RT-PCR cycle threshold values in cases of COVID-19, England, January to May 2020breakdown → | 534 |
| 8 | 34 | |
| 9 | 31 | |
| 10 | 42 | |
| 11 | 10 | |
| 12 | 3 | |
| 13 | 0 | |
| 14 | 1 | |
| 15 | 63 | |
| 16 | 6 | |
| 17 | 21 | |
| 18 | 1 | |
| 19 | 6 |
About Anika Singanayagam
Anika Singanayagam is a scholar working on Infectious Diseases, Epidemiology and Modeling and Simulation, having authored 19 papers that have together received 847 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (6 papers), Respiratory viral infections research (6 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). The work is most often cited by research in Infectious Diseases (599 citations), Modeling and Simulation (115 citations) and Epidemiology (250 citations). Anika Singanayagam has collaborated with scholars based in United Kingdom, United States and Gambia. Frequent co-authors include Maria Zambon, Robin Gopal, André Charlett, Jamie Lopez Bernal, Vanessa Saliba, Shamez Ladhani, Joanna Ellis, Monika Patel, William Barclay and Aran Singanayagam. Their work appears in journals such as Nature Communications, Journal of Virology and The Journal of Infectious Diseases.
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.