Ding‐Ping Liu
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Endocrinology top 2%
- Vibrio bacteria research studies
Papers in ⓘ
-
- COVID-19 epidemiological studies 8
-
- Viral gastroenteritis research and epidemiology 6
- Viral Infections and Outbreaks Research 6
- Co-authors
- Hao‐Yuan Cheng (7 shared papers)Shu-Wan Jian (5 shared papers)Hsien-Ho Lin (3 shared papers)Ta-Chou Vincent Ng (2 shared papers)Wan‐Ting Huang (3 shared papers)Hin‐chung Wong (3 shared papers)Luan‐Yin Chang (6 shared papers)Chin‐Yun Lee (3 shared papers)
- Journals
- Vaccine (3 papers)International Journal of Infectious Diseases (2 papers)The Journal of Infectious Diseases (2 papers)JAMA Internal Medicine (2 papers)PLoS ONE (2 papers)
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Ding‐Ping Liu
55 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Modeling and Simulation 411
- Endocrinology 209
- Infectious Diseases 599
- Hepatology 141
- Epidemiology 590
Countries citing papers authored by Ding‐Ping Liu
This map shows the geographic impact of Ding‐Ping Liu'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 Ding‐Ping Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ding‐Ping Liu more than expected).
Fields of papers citing papers by Ding‐Ping Liu
This network shows the impact of papers produced by Ding‐Ping Liu. 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 Ding‐Ping Liu. The network helps show where Ding‐Ping Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ding‐Ping Liu, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Contact Tracing Assessment of COVID-19 Transmission Dynamics in Taiwan and Risk at Different Exposure Periods Before and After Symptom Onset Hit paper breakdown → | 2020 | 537 |
| 2 | 2000 | 141 | |
| 3 | 2006 | 129 | |
| 4 | 2015 | 95 | |
| 5 | 1999 | 79 | |
| 6 | 1997 | 66 | |
| 7 | 2004 | 59 | |
| 8 | 2012 | 53 | |
| 9 | 2020 | 52 | |
| 10 | 1998 | 42 | |
| 11 | 2020 | 39 | |
| 12 | 2021 | 38 | |
| 13 | 2012 | 34 | |
| 14 | 2013 | 31 | |
| 15 | 2014 | 30 | |
| 16 | 2017 | 30 | |
| 17 | 2019 | 28 | |
| 18 | Influenza in Taiwan: seasonality and vaccine strain match. | 2005 | 28 |
| 19 | 2022 | 26 | |
| 20 | 2020 | 22 |
About Ding‐Ping Liu
Ding‐Ping Liu is a scholar working on Modeling and Simulation, Infectious Diseases, Endocrinology, Epidemiology and Health, having authored 57 papers that have together received 1.8k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (9 papers), Viral Infections and Immunology Research (8 papers), Respiratory viral infections research (8 papers), COVID-19 epidemiological studies (8 papers), Viral gastroenteritis research and epidemiology (6 papers), Viral Infections and Outbreaks Research (6 papers), Vaccine Coverage and Hesitancy (5 papers) and COVID-19 Digital Contact Tracing (4 papers). The work is most often cited by research in Modeling and Simulation (411 citations), Endocrinology (209 citations), Infectious Diseases (599 citations), Hepatology (141 citations) and Epidemiology (590 citations). Ding‐Ping Liu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Hao‐Yuan Cheng, Shu-Wan Jian, Hsien-Ho Lin, Ta-Chou Vincent Ng, Wan‐Ting Huang, Hin‐chung Wong, Luan‐Yin Chang, Chin‐Yun Lee, Chun‐Yi Lu and Li‐Min Huang. Their work appears in journals such as Vaccine, International Journal of Infectious Diseases, The Journal of Infectious Diseases, JAMA Internal Medicine and PLoS ONE.
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.