Eiichiro Sando
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Parasitology top 10%
- Vector-borne infectious diseases
Papers in
-
- Viral Infections and Vectors 5
- SARS-CoV-2 and COVID-19 Research 2
- Epidemiology 12
- Pneumonia and Respiratory Infections 9
- Respiratory viral infections research 3
- Co-authors
- Motoi Suzuki (15 shared papers)Konosuke Morimoto (13 shared papers)Koya Ariyoshi (10 shared papers)Makito Yaegashi (10 shared papers)Ikkoh Yasuda (9 shared papers)Tadatsugu Imamura (4 shared papers)Naho Tsuchiya (4 shared papers)Yuki Furuse (4 shared papers)
- Journals
- Emerging infectious diseases (4 papers)Vaccine (3 papers)BMC Pulmonary Medicine (2 papers)Frontiers in Pediatrics (1 paper)Tropical Medicine and Infectious Disease (1 paper)
- Partner nations
- JapanUnited StatesSwitzerland
In The Last Decade
Eiichiro Sando
27 papers receiving 394 citations
Peers
Comparison fields: 5 of 66
- Modeling and Simulation 93
- Parasitology 63
- Infectious Diseases 109
- Epidemiology 99
- Health 14
Countries citing papers authored by Eiichiro Sando
This map shows the geographic impact of Eiichiro Sando'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 Eiichiro Sando with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eiichiro Sando more than expected).
Fields of papers citing papers by Eiichiro Sando
This network shows the impact of papers produced by Eiichiro Sando. 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 Eiichiro Sando. The network helps show where Eiichiro Sando may publish in the future.
Co-authors
The 25 scholars most cited alongside Eiichiro Sando, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 155 | |
| 2 | 2018 | 31 | |
| 3 | 2019 | 28 | |
| 4 | 2017 | 25 | |
| 5 | 2021 | 19 | |
| 6 | 2021 | 16 | |
| 7 | 2021 | 16 | |
| 8 | 2022 | 13 | |
| 9 | 2018 | 12 | |
| 10 | 2019 | 12 | |
| 11 | 2020 | 12 | |
| 12 | 2018 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2017 | 6 | |
| 15 | 2020 | 6 | |
| 16 | 2022 | 6 | |
| 17 | 2020 | 5 | |
| 18 | 2022 | 4 | |
| 19 | 2023 | 3 | |
| 20 | 2015 | 3 |
About Eiichiro Sando
Eiichiro Sando is a scholar working on Infectious Diseases, Epidemiology, Parasitology, Public Health, Environmental and Occupational Health and Modeling and Simulation, having authored 29 papers that have together received 402 indexed citations. Recurring topics across this work include Pneumonia and Respiratory Infections (9 papers), Vector-borne infectious diseases (9 papers), Viral Infections and Vectors (5 papers), COVID-19 epidemiological studies (3 papers), Mosquito-borne diseases and control (3 papers), Respiratory viral infections research (3 papers), Vector-Borne Animal Diseases (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Modeling and Simulation (93 citations), Parasitology (63 citations), Infectious Diseases (109 citations), Epidemiology (99 citations) and Health (14 citations). Eiichiro Sando has collaborated with scholars based in Japan, United States and Switzerland. Frequent co-authors include Motoi Suzuki, Konosuke Morimoto, Koya Ariyoshi, Makito Yaegashi, Ikkoh Yasuda, Tadatsugu Imamura, Naho Tsuchiya, Yuki Furuse, Yura K Ko and Hitoshi Oshitani. Their work appears in journals such as Emerging infectious diseases, Vaccine, BMC Pulmonary Medicine, Frontiers in Pediatrics and Tropical Medicine and Infectious Disease.
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.