Su‐Vui Lo
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
- Infectious Diseases top 2%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral Infections and Outbreaks Research
Papers in
- Epidemiology 14
- Influenza Virus Research Studies 9
- Respiratory viral infections research 5
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- COVID-19 epidemiological studies 9
- Co-authors
- GM Leung (14 shared papers)Thomas Tsang (10 shared papers)LM Ho (10 shared papers)Steven Riley (6 shared papers)Benjamin J. Cowling (12 shared papers)TH Lam (5 shared papers)TQ Thach (2 shared papers)Christl A. Donnelly (2 shared papers)
- Journals
- PLoS Medicine (2 papers)Health Policy (2 papers)Social Science & Medicine (2 papers)PLoS ONE (2 papers)Clinical Infectious Diseases (1 paper)
- Partner nations
- Hong KongChinaUnited Kingdom
In The Last Decade
Su‐Vui Lo
24 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Modeling and Simulation 1.1k
- Infectious Diseases 700
- Epidemiology 834
- Health 136
- Agronomy and Crop Science 125
Countries citing papers authored by Su‐Vui Lo
This map shows the geographic impact of Su‐Vui Lo'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 Su‐Vui Lo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Su‐Vui Lo more than expected).
Fields of papers citing papers by Su‐Vui Lo
This network shows the impact of papers produced by Su‐Vui Lo. 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 Su‐Vui Lo. The network helps show where Su‐Vui Lo may publish in the future.
Co-authors
The 25 scholars most cited alongside Su‐Vui Lo, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Transmission Dynamics of the Etiological Agent of SARS in Hong Kong: Impact of Public Health Interventions Hit paper breakdown → | 2003 | 810 |
| 2 | 2004 | 242 | |
| 3 | 2010 | 182 | |
| 4 | 2010 | 148 | |
| 5 | 2005 | 121 | |
| 6 | 2011 | 96 | |
| 7 | 2011 | 92 | |
| 8 | 2019 | 87 | |
| 9 | 2010 | 80 | |
| 10 | 2011 | 50 | |
| 11 | 2014 | 36 | |
| 12 | 2008 | 31 | |
| 13 | 2012 | 29 | |
| 14 | 2009 | 17 | |
| 15 | 2009 | 17 | |
| 16 | 2005 | 15 | |
| 17 | 2013 | 14 | |
| 18 | 2005 | 11 | |
| 19 | 2006 | 11 | |
| 20 | 2009 | 4 |
About Su‐Vui Lo
Su‐Vui Lo is a scholar working on Epidemiology, Modeling and Simulation, General Health Professions, Infectious Diseases and Health, having authored 24 papers that have together received 2.1k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (9 papers), COVID-19 epidemiological studies (9 papers), Respiratory viral infections research (5 papers), Health disparities and outcomes (4 papers), Healthcare Policy and Management (3 papers), COVID-19 Clinical Research Studies (3 papers), Global Health Care Issues (3 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers). The work is most often cited by research in Modeling and Simulation (1.1k citations), Infectious Diseases (700 citations), Epidemiology (834 citations), Health (136 citations) and Agronomy and Crop Science (125 citations). Su‐Vui Lo has collaborated with scholars based in Hong Kong, China and United Kingdom. Frequent co-authors include GM Leung, Thomas Tsang, LM Ho, Steven Riley, Benjamin J. Cowling, TH Lam, TQ Thach, Christl A. Donnelly, Neil M. Ferguson and Christophe Fraser. Their work appears in journals such as PLoS Medicine, Health Policy, Social Science & Medicine, PLoS ONE and Clinical 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.