Arul Nancy
Impact in
- Infectious Diseases top 10%
- Tuberculosis Research and Epidemiology
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
-
- Immune responses and vaccinations
Papers in
-
- Tuberculosis Research and Epidemiology 15
- COVID-19 Clinical Research Studies 9
- SARS-CoV-2 and COVID-19 Research 6
-
- Pneumocystis jirovecii pneumonia detection and treatment 9
- Co-authors
- Subash Babu (28 shared papers)Nathella Pavan Kumar (16 shared papers)Kadar Moideen (12 shared papers)Hardy Kornfeld (9 shared papers)Vijay Viswanathan (9 shared papers)Shanmugam Sivakumar (8 shared papers)Anuradha Rajamanickam (7 shared papers)Nathella Pavan Kumar (11 shared papers)
- Journals
- Frontiers in Immunology (4 papers)Viruses (3 papers)Tuberculosis (2 papers)Cytokine (2 papers)Journal of Infection (2 papers)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Arul Nancy
26 papers receiving 367 citations
Peers
Comparison fields: 5 of 58
- Infectious Diseases 230
- Immunology 138
- Health 31
- Epidemiology 99
- Modeling and Simulation 12
Countries citing papers authored by Arul Nancy
This map shows the geographic impact of Arul Nancy'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 Arul Nancy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arul Nancy more than expected).
Fields of papers citing papers by Arul Nancy
This network shows the impact of papers produced by Arul Nancy. 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 Arul Nancy. The network helps show where Arul Nancy may publish in the future.
Co-authors
The 25 scholars most cited alongside Arul Nancy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1994 | 58 | |
| 2 | 2019 | 48 | |
| 3 | 2021 | 35 | |
| 4 | 2019 | 22 | |
| 5 | 2018 | 21 | |
| 6 | 2020 | 21 | |
| 7 | 2021 | 20 | |
| 8 | 2021 | 15 | |
| 9 | 2021 | 14 | |
| 10 | 2021 | 13 | |
| 11 | 2020 | 13 | |
| 12 | 2019 | 12 | |
| 13 | 2022 | 11 | |
| 14 | 2021 | 10 | |
| 15 | 2022 | 9 | |
| 16 | 2021 | 8 | |
| 17 | 2019 | 8 | |
| 18 | 2021 | 7 | |
| 19 | 2023 | 6 | |
| 20 | 2024 | 5 |
About Arul Nancy
Arul Nancy is a scholar working on Infectious Diseases, Epidemiology, Immunology, Surgery and Health, having authored 30 papers that have together received 371 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (15 papers), Pneumocystis jirovecii pneumonia detection and treatment (9 papers), COVID-19 Clinical Research Studies (9 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Immune responses and vaccinations (6 papers), Vaccine Coverage and Hesitancy (5 papers), Long-Term Effects of COVID-19 (3 papers) and Kawasaki Disease and Coronary Complications (3 papers). The work is most often cited by research in Infectious Diseases (230 citations), Immunology (138 citations), Health (31 citations), Epidemiology (99 citations) and Modeling and Simulation (12 citations). Arul Nancy has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Subash Babu, Nathella Pavan Kumar, Kadar Moideen, Hardy Kornfeld, Vijay Viswanathan, Shanmugam Sivakumar, Anuradha Rajamanickam, Nathella Pavan Kumar, Chandrasekaran Padmapriyadarsini and Syed Hissar. Their work appears in journals such as Frontiers in Immunology, Viruses, Tuberculosis, Cytokine and Journal of Infection.
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.